Ayumi's LLM Role Play & ERP Ranking (Version 3)

This ranking table contains a rating of different LLMs, which tries to determine which model is most suitable for (erotic) role playing (ERP) by using an automated benchmark. Unfortunately this automated benchmarks has it's limits, but the table can serve as a starting point for you to look for LLM models to try out.

  1. Ayumi's LLM Role Play & ERP Ranking (Version 3)
    1. About Quantization
    2. Ayumi ERP Rating Archive
  2. Technical Details of the ALC-IQ3 and ERP3 Benchmark
    1. Ayumi LLM Character IQ Version 3 - ALC-IQ3
    2. Known Flaws of the ALC-IQ
    3. ERP3 Score and ERP3 Variety Score
    4. Known Flaws of the ERP3 Score and ERP Variety Score
    5. About Instruction or Chat Prompt Formats
  3. Who is Ayumi?
  4. Questions
  5. Contribute
  6. Credits
  7. See Also
    1. Character guides & Tutorials
    2. Other resources & links
  8. Cite as

Interpretation Warning: Writing quality is not covered!

Disclaimer: This benchmark makes no statement about how well a LLM will be able to drive the story forward. It can also not determine coherency within a longer role play chat. The generated text quality is not tested for. For more information look in these sections: Known Flaws of the ALC-IQ and Known Flaws of the ERP Score

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The most up to date table and changelog you can find on my new landing page: http://ayumi.m8geil.de/

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Column Description
ALC-IQ3 The ALC-IQ3 is the 3rd version of the ALC-IQ. It tries to determine how well a model understands a character card. The higher the better. Best score is 100.
ERP3 Score The average ratio of lewd words vs. words in a response. The higher the better.
Var Score The lewd word variety score. It counts how many different lewd words occur in all ERP responses

Updated: 2023-11-21 13:11:36 (UTC+01:00) Changelog
Note: For an interactive table look here: http://ayumi.m8geil.de/ayumi_bench_v3_results.html

Rank Name Size Q ALC-IQ3 ERP3 Score Var Score
1 Neural Chat V3 16k 7B 7B Q8_0 89.33 30.92 572
2 Neural Chat V3-1 7B 7B Q6_K 88.18 30.42 468
3 U Amethyst 20B 20B Q5_K_M 88.86 30.95 455
4 LLaMA-2 Ensemble v6 13B 13B Q5_K_M 86.93 29.25 482
5 Airoboros L2 2.2 70B 70B Q4_K_M 88.20 29.16 459
6 Synatra V0.3 RP 7B 7B Q8_0 82.72 35.15 453
7 PsyMedRP V1 20B 20B Q5_K_M 88.48 30.59 440
8 Euryale Inverted L2 70B 70B Q4_K_M 87.15 32.53 417
9 ORCA LLaMA QLoRA 70B 70B Q4_K_M 90.07 30.77 396
10 Emerhyst 20B 20B Q5_K_M 88.33 29.20 423
11 Utopia 13B 13B Q5_K_M 85.05 30.85 439
12 StellarBright 70B 70B Q4_K_M 88.56 30.36 404
13 Synatra V0.3 RP 7B 7B Q4_K_M 82.69 34.04 425
14 Nethena 20B 20B Q5_K_M 86.35 32.60 400
15 Sheep Duck LLaMA 2 V1.1 70B 70B Q4_K_M 89.24 31.23 377
16 Synatra V0.3 RP AshhLimaRP Mistral 7B 7B Q5_KM 83.33 33.20 418
17 Sheep Duck LLaMA 2 13B 13B Q5_K_M 87.83 30.39 400
18 Nethena MLewd Xwin 23B 23B Q5_K_M 83.30 33.98 405
19 Stairolz 70B 70B Q4_K_S 88.32 30.56 382
20 Misted 7B 7B Q6_K 86.00 32.54 379
21 Upstage LLaMA Instruct 65B 65B Q4_K_M 88.45 32.86 347
22 Toppy M 7B 7B Q5_K_M 89.30 32.81 336
23 StableBeluga 2 70B 70B Q4_K_M 87.51 29.39 391
24 Xwin LM V0.1 70B 70B Q4_K_M 88.54 31.02 362
25 Zephyr Alpha 7B 7B Q5_K_M 87.50 33.03 351
26 OpenHermes 2.5 AshhLimaRP Mistral 7B 7B Q5_KM 88.53 28.69 385
27 SlimOpenOrca Mistral 7B 7B Q5_K_M 88.49 27.02 403
28 MM ReMM L2 20B 20B Q5_K_M 87.92 31.25 362
29 ZephRP M 7B 7B Q5_K_M 85.79 30.01 397
30 X NoroChronos 13B 13B Q5_K_M 84.03 33.40 377
31 Stheno 1.8 13B 13B Q5_K_M 84.72 31.27 390
32 ReMM S Kimiko v2 13B 13B Q5_K_M 76.27 32.97 459
33 Nous Capybara 34B 34B Q4_K_M 83.51 30.98 402
34 Dolphin 2.1 Mistral 7B 7B Q5_K_M 86.69 31.74 359
35 Echidna Tiefigther 25 13B 13B Q5_K_M 81.40 32.49 400
36 GodziLLa 2 70B 70B Q4_K_M 83.19 30.29 404
37 Zephyr Alpha 7B 7B Q6_K 87.34 31.13 351
38 Athnete 13B 13B Q5_K_M 81.91 31.53 403
39 Airoboros L2 2.1 70B 70B Q4_K_M 83.50 31.26 389
40 Zephyr Cucumber Instruct 7B 7B Q5_K_M 86.22 32.22 350
41 DaringFortitude 13B 13B Q5_K_M 89.75 25.96 379
42 ShiningValiantXS 13B 13B Q5_K_M 89.75 25.96 379
43 Mistral OpenOrca 7B 7B Q5_K_M 86.48 28.91 381
44 Dolphin 2.2 70B 70B Q4_K_M 88.57 30.85 337
45 LLaMA-2 Chat AYT 13B 13B Q5_K_M 89.88 26.82 364
46 Augmental Unholy 13B 13B Q5_K_M 85.38 31.33 362
47 Nete 13B 13B Q5_K_M 79.74 30.16 434
48 Athena V4 13B 13B Q5_K_M 80.98 30.95 411
49 Airoboros L2 2.2.1 70B 70B Q4_K_M 87.47 30.50 346
50 X MythoChronos 13B 13B Q5_K_M 80.40 31.43 409
51 MistralMakise Merged 13B 13B Q5_K_M 80.73 29.43 425
52 MLewdBoros SuperCOT 13B 13B Q5_K_M 82.63 32.96 366
53 LLaMA-2 Chat AYB 13B 13B Q5_K_M 87.83 28.75 355
54 Nethena 13B 13B Q5_K_M 80.40 31.44 404
55 Echidna V0.1 13B 13B Q5_K_M 80.41 31.80 400
56 Unholy v1 12L 13B 13B Q5_K_M 82.39 31.21 385
57 Noromaid V0.1 13B 13B Q5_K_M 77.94 27.78 468
58 Hermes Trismegistus Mistral 7B 7B Q5_K_M 87.87 30.66 331
59 HornyEchidna V0.1 13B 13B Q5_K_M 80.48 30.74 405
60 Euryale 1.4 L2 70B 70B Q4_K_S 85.79 29.68 360
61 Airoboros L2 2.1 Creative 70B 70B Q4_K_M 83.27 30.23 379
62 Noromaid V0.1.1 13B 13B Q5_K_M 81.25 31.98 378
63 Airoboros L2 3.1 70B 70B Q4_K_M 84.85 29.26 368
64 Trion M 7B 7B Q4_K 87.57 30.92 321
65 Athena v3 13B 13B Q5_K_M 81.45 32.76 366
66 OpenHermes 2.5 Mistral 7B 7B Q5_K_M 87.65 29.17 337
67 Airoboros L2 3.1.2 70B 70B Q4_K_M 82.96 28.51 392
68 Zephyr Beta 7B 7B Q5_K_M 85.83 31.92 323
69 UtopiaXL 13B 13B Q5_K_M 77.18 28.39 451
70 Dolphin 2.1 OpenOrca 7B 7B Q5_K_M 86.27 29.64 339
71 PsyFighter 13B 13B Q5_K_M 78.53 30.46 409
72 Amethyst 13B 13B Q5_K_M 80.06 26.90 430
73 Mistral Dolphin 2.1 LIMA0.5 7B 7B Q5_K_M 85.34 28.02 362
74 Stheno Inverted 1.2 13B 13B Q5_K_M 76.95 30.98 418
75 Nethena Glued 20B 20B Q4_K_M 81.26 28.15 402
76 Athena v2 13B 13B Q5_K_M 79.15 31.10 392
77 Stheno 1.3 13B 13B Q5_K_M 72.94 31.12 457
78 MLewd v2 13B 13B Q5_K_M 77.99 31.81 395
79 MLewd V2-1 13B 13B Q5_K_M 76.63 30.48 422
80 Unholy v1.1 13B 13B Q5_K_M 86.20 30.72 318
81 Dolphin 2.2 Yi 34B 34B Q4_K_M 87.46 31.62 295
82 Noromaid V0.1.1 20B 20B Q5_K_M 83.18 30.14 356
83 MLewd Chat V2 13B 13B Q5_K_M 82.48 27.69 389
84 Airoboros L2 GPT4 1.4.1 70B 70B Q4_K_M 82.93 28.47 376
85 Synthia V1.1 70B 70B Q4_K_M 82.94 30.00 359
86 MLewd V2.4 13B 13B Q5_K_M 78.01 28.23 430
87 OpenRP SuperCOT 13B 13B Q5_K_M 84.47 30.59 336
88 BerrySauce 13B 13B Q5_K_M 77.09 32.42 394
89 ReMM Mistral 13B 13B Q5_K_M 80.58 28.63 396
90 Xwin MLewd V0.2 13B 13B Q5_K_M 78.53 29.06 412
91 Thespis Mistral V0.5 7B 7B Q5_K_M 82.51 33.89 318
92 LLaMA 2 Tiefighter 13B 13B Q5_K_M 78.89 30.07 393
93 lzlv 70B 70B Q4_K_M 86.02 29.61 321
94 MLewdBoros 13B 13B Q5_K_M 75.78 31.52 407
95 ReMM v2 Kimiko v2 13B 13B Q5_K_M 81.60 29.65 365
96 Dolphin 2.2.1 AshhLimaRP Mistral 7B 7B Q5_K_M 85.00 27.09 355
97 ReMM v2 13B 13B Q5_K_M 78.69 31.74 372
98 Stheno Variants L2 13B 13B Q5_K_M 76.91 31.09 397
99 Kaori V1 70B 70B Q4_K_M 81.40 29.63 365
100 Amethyst Mistral 13B 13B Q4_K_S 79.25 26.53 419
101 Naberius 7B 7B Q5_K_M 85.44 29.89 317
102 Dolphin 2.2.1 Mistral 7B 7B Q5_K_M 85.99 29.25 317
103 MythoMax Kimiko Mix 13B 13B Q5_K_M 79.60 29.16 385
104 Mistral AirOmniMix 11B 11B Q6_K 83.39 29.89 337
105 AppleSauce 13B 13B Q5_K_M 76.47 32.42 383
106 Euryale 1.3 L2 70B 70B Q4_K_M 84.26 26.92 358
107 TimeCrystal L2 13B 13B Q5_K_M 77.82 31.49 376
108 Chronob 1.4 Lin 70B 70B Q4_K_S 80.65 29.14 371
109 Hexoteric 7B 7B Q5_K_M 87.49 31.81 270
110 MistralLite 7B 7B Q5_K_M 82.20 28.93 356
111 MistRP AirOrca 7B 7B Q5_K_M 84.09 29.26 332
112 Kanelsnegl V0.1 7B 7B Q4_K 85.56 29.15 317
113 MythoMax Kimiko V2 13B 13B Q5_K_M 79.53 28.94 381
114 OpenChat 3.5 7B 7B Q5_K_M 88.09 28.63 293
115 Echidna V0.2 13B 13B Q5_K_M 78.56 31.22 366
116 MLewd Chat 13B 13B Q5_K_M 83.69 28.88 336
117 OpenRP 13B 13B Q5_K_M 77.04 28.42 411
118 L2 TheSpurral M2.2 13B 13B Q5_K_M 78.49 30.83 369
119 Stheno Inverted 13B 13B Q5_K_M 77.19 29.65 393
120 MXLewdMini 13B 13B Q5_K_M 79.11 31.94 347
121 Airoboros M 3.1.1 7B 7B Q5_K_M 83.01 32.72 297
122 TimeCrystal l2 13B 13B Q5_K_S 77.57 30.11 382
123 StableBeluga 13B 13B Q5_K_M 82.65 28.02 350
124 Augmental ReMM 13B 13B Q5_K_M 75.45 28.32 423
125 OpenHermes 2 Mistral 7B 7B Q5_K_M 84.16 30.08 312
126 MLewd v2-2 13B 13B Q5_K_M 76.26 31.85 376
127 UndiMix v3 13B 13B Q5_K_M 78.32 30.55 368
128 Zaraxls 7B 7B Q5_K_M 74.56 30.29 410
129 Magdump 13B 13B Q5_K_M 78.09 28.74 389
130 UndiMix V3 13B 13B Q5_K_M 78.25 31.68 356
131 Echidna V0.3 13B 13B Q5_K_M 78.52 30.19 368
132 Unholy v1 10L 13B 13B Q5_K_M 80.59 29.19 355
133 Tai 70B 70B Q4_K_M 79.69 29.76 357
134 Dawn V2 70B 70B Q4_K_M 86.62 27.47 308
135 Mistral SciPhi 32k 7B 7B Q5_K_M 83.43 29.02 325
136 SynthIA V1.5 70B 70B Q4_K_M 79.54 29.92 356
137 ReMM SLERP 13B 13B Q5_K_M 77.75 28.95 385
138 Huginn v1.2 13B 13B Q5_K_M 77.75 28.95 385
139 MythoMax 13B 13B Q5_K_M 77.75 28.95 385
140 Airoboros 2.1 33B 33B Q4_K_M 75.62 31.82 377
141 ReMM 13B 13B Q5_K_M 74.55 29.07 416
142 SciPhi Self RAG Mistral 32k 7B 7B Q5_K_M 88.00 30.06 263
143 ZettaPi 13B 13B Q5_K_M 78.36 28.46 382
144 ReMM PIPPA 13B 13B Q5_K_M 74.73 29.34 410
145 L2 TheSpurral M2 13B 13B Q5_K_S 76.32 31.43 371
146 MLewd V2-1 015 13B 13B Q4_K_S 75.96 30.13 387
147 Eileithyia 13B 13B Q5_K_M 73.39 27.70 440
148 Synthia v1.3 7B 7B Q5_K_M 78.71 32.46 333
149 UndiMix v4 13B 13B Q5_K_M 79.02 32.24 332
150 Chupacabra 7B 7B Q8_0 87.64 26.76 299
151 Augmental V1.50 A 13B 13B Q5_K_M 77.43 29.72 375
152 ReMM v1 LRPSGPT 2Char 13B 13B Q5_K_M 74.89 32.40 373
153 PsyFighter2 13B 13B Q5_K_M 78.47 27.40 387
154 Emerhyst 13B 13B Q5_K_M 78.44 25.58 404
155 Tess Medium 200K V1.0 34B 34B Q4_K_M 76.72 29.98 375
156 MythoMix 13B 13B Q5_K_M 76.34 29.51 384
157 Mistral Phibrarian 32K 7B 7B Q5_K_M 83.54 29.50 307
158 Eileithyia 7B 7B Q8_0 83.58 27.88 323
159 LimaBean 13B 13B Q5_K_M 77.88 27.00 391
160 MLewdBoros LRPSGPT 2Char 13B 13B Q5_K_M 76.78 28.83 382
161 ReMM v2.2 13B 13B Q5_K_M 79.63 31.11 327
162 Airoboros M 3.1.2 7B 7B Q5_K_M 84.02 32.09 270
163 Speechless Mistral Dolphin Orca Platypus Samantha 7B 7B Q5_K_M 84.36 27.96 310
164 UndiMix v2 13B 13B Q5_K_M 79.50 32.22 316
165 Vigostral Chat 7B 7B Q5_K_M 81.38 30.52 314
166 LLaMA 2 TiefighterLR 13B 13B Q5_K_M 74.47 26.75 424
167 Xwin LM V0.2 13B 13B Q5_K_M 79.27 28.46 355
168 Euryale L2 70B 70B Q4_K_M 79.94 27.13 362
169 Camel Platypus2 70B 70B Q4_K_M 82.90 26.49 337
170 Tulpar Limarp 7B 7B Q5_K_M 78.48 28.28 364
171 Yi GiftedConvo Merged 34B 34B Q4_K_M 84.65 28.19 299
172 PsyMedRP V1 13B 13B Q5_K_M 76.76 26.07 404
173 SynthiAthena V2 13B 13B Q5_K_M 78.89 30.92 328
174 Mistralic 1 7B 7B Q5_K_M 80.67 28.41 335
175 Uncensored Jordan 33B 33B Q5_K_M 87.37 31.75 227
176 Phind CodeLlama V2 34B 34B Q4_K_M 85.07 26.77 302
177 Lewd Sydney 20B 20B Q4_K_S 82.58 27.49 320
178 Mistral CC Air 11B 11B Q5_K_M 79.25 29.19 337
179 Chronoboros 33B 33B Q4_K_M 74.93 31.21 360
180 Magpie 13B 13B Q5_K_M 78.02 29.06 350
181 Airoboros Mistral 2.2 7B 7B Q5_K_M 80.23 32.39 290
182 Inkbot 4k 13B 13B Q4_K_M 77.20 28.14 367
183 UndiMix V4 13B 13B Q5_K_M 79.01 30.81 319
184 Mistral RP 0.1 7B 7B Q5_K_M 77.86 29.05 349
185 MLewd 13B 13B Q5_K_M 74.71 32.08 348
186 ReMM v2.1 13B 13B Q5_K_M 77.29 31.89 322
187 Augmental V1.50 B 13B 13B Q5_K_M 76.91 28.75 359
188 Thorns 13B 13B Q5_K_M 79.08 35.10 268
189 airoboros L2 3.1 13B 13B Q5_K_M 79.86 31.35 299
190 Airochronos 33B 33B Q4_K_M 75.00 31.83 342
191 LlongOrca 16K 13B 13B Q5_K_M 78.47 25.83 368
192 Guanaco 65B 65B Q4_K_M 78.85 29.00 330
193 Slerpeno 13B 13B Q5_K_M 74.74 32.92 330
194 MLewd V2-1 050 13B 13B Q4_K_S 74.13 28.69 381
195 ReMM 0.65 SLERP 13B 13B Q5_K_M 76.25 30.18 342
196 Chronos V2 70B 70B Q4_K_M 76.67 27.76 362
197 Athena v1 13B 13B Q5_K_M 74.58 30.74 352
198 OpenBuddy Zephyr V14.1 7B 7B Q5_K_M 74.35 30.75 352
199 ReMM Lion 13B 13B Q5_K_M 76.02 27.85 363
200 MythoMakiseMerged 13B 13B Q5_K_M 77.02 27.77 351
201 WizardLM V1.0 70B 70B Q4_K_M 85.99 26.56 269
202 Airoboros L2 2.2.1 13B 13B Q5_K_M 75.19 31.09 335
203 Nanbeige Chat 16B 16B Q4_K_M 80.54 30.05 289
204 Airoboros L2 3.0 13B 13B Q5_K_M 75.97 29.32 345
205 Mistral SynthIAirOmniMix 11B 11B Q5_K_M 79.14 29.18 310
206 UndiMix v1 13B 13B Q5_K_M 77.78 30.73 307
207 Vicuna V1.5 16K 13B 13B Q5_K_M 78.64 28.54 321
208 Airoboros L2 C 3.1.2 70B 70B Q4_K_M 87.88 27.27 236
209 ReMM v2 Variant 13B 13B Q5_K_M 78.05 30.61 304
210 Nous Hermes 13B 13B Q5_K_M 81.22 31.81 257
211 LimaRP V2 LLaMA 2 70B 70B Q3_K_M 74.97 24.06 403
212 Mistral CC Air RP 11B 11B Q5_K_M 79.30 27.80 317
213 Airoboros 2.1 13B 13B Q5_K_M 71.16 28.94 391
214 Airoboros Creative lmoe 13B 13B Q5_K_M 71.22 29.61 382
215 Mistral ClaudeLimaRP v3 7B 7B Q5_K_M 73.78 27.59 375
216 Tess XS V1.0 7B 7B Q8_0 78.24 30.41 294
217 Thespis Mistral V0.6 7B 7B Q6_K 82.64 30.70 243
218 Spicyboros 2.2 13B 13B Q4_K_M 70.58 28.50 389
219 CollectiveCognition V1.1 Mistral 7B 7B Q5_K_M 85.28 27.02 246
220 Platypus 2 70B 70B Q4_K_M 78.04 26.06 330
221 AstraMix 7B 7B Q5_K_M 72.52 28.74 359
222 MistRP Airoboros 7B 7B Q5_K_M 80.48 30.61 254
223 Airoboros 2.2 13B 13B Q5_K_M 70.45 28.91 378
224 LLaMA-2 LoRA Assemble 7B 7B Q5_K_M 77.82 30.07 287
225 Opus V0 70B 70B Q4_K_M 79.32 24.22 333
226 MegaMix A1 13B 13B Q5_K_M 76.53 29.22 309
227 Mythalion 13B 13B Q5_K_M 74.39 29.05 332
228 AshhLimaRP Mistral 7B 7B Q5_K_M 74.07 24.68 380
229 Mistral OpenOrca oasst top1 2023-08-25 V1 7B 7B Q5_K_M 78.27 25.68 324
230 Airoboros L2 3.1.1 13B 13B Q5_K_M 75.98 27.83 324
231 L2 TheSpurral V2 13B 13B Q5_K_S 71.22 30.53 345
232 LLaMA 2 Chat 70B 70B Q4_K_M 86.76 24.82 241
233 MegaMix T1 13B 13B Q5_K_M 76.36 29.70 298
234 Yi 200K Airo Claude Puffin 6B 6B Q6_K 71.43 28.39 364
235 Yarn Mistral 64k 7B 7B Q5_K_M 75.03 27.89 331
236 Zarafusionex 1.1 7B 7B Q5_K_M 71.08 28.61 365
237 TerraMix 16K 13B 13B Q5_K_M 74.97 25.92 352
238 LLaMA 2 Chat Uncensored 70B 70B Q4_K_M 75.19 30.22 302
239 Vicuna 33B 33B Q4_K_M 79.25 30.58 254
240 Dans TotSirocco 7B 7B Q5_K_M 79.47 27.54 283
241 OpenChat 3.5 16k 7B 7B Q5_K_M 75.17 28.41 319
242 Yarn Mistral 128k 7B 7B Q5_K_M 75.29 26.17 341
243 PetrolLM Claude Chat 7B 7B Q8_0 71.81 32.67 308
244 Marcoroni 7B 7B Q5_K_M 75.69 29.34 301
245 Nous Hermes LLaMA-2 13B 13B Q5_K_M 79.25 31.07 239
246 Nous Capybara V1.9 7B 7B Q5_K_M 73.07 29.94 316
247 Airoboros L2 GPT4 m2.0 13B 13B Q5_K_M 76.23 32.82 251
248 Vicuna V1.5 13B 13B Q5_K_M 76.86 27.95 293
249 Augmental 13B 13B Q5_K_M 71.20 26.50 368
250 GradientPutri MegaMix S1 13B 13B Q5_K_S 73.27 29.39 312
251 Chronos Hermes v2 13B 13B Q5_K_M 72.39 28.38 332
252 Arithmo Mistral 7B 7B Q5_K_M 77.02 29.47 271
253 Airoboros GPT4 2.0 LLaMA-2 13B 13B Q5_K_M 73.61 32.58 274
254 Huginn v4.5 13B 13B Q5_K_M 70.00 26.10 381
255 Huginn v3 13B 13B Q5_K_M 70.00 26.10 381
256 Huginn v4 13B 13B Q5_K_M 70.00 26.10 381
257 Merak V4 PROTOTYPE6 7B 7B Q5_K_M 76.22 29.96 270
258 Thespurral V1 13B 13B Q5_K_M 69.55 30.73 332
259 MythoLogic 13B 13B Q5_K_M 75.22 31.57 263
260 Airoboros 2.2.1 Mistral 34B 34B Q4_K_S 78.83 25.41 290
261 Airoboros 3.1.2 33B 33B Q4_K_M 71.35 29.96 319
262 Tigerbot Chat V4 70B 70B Q4_K_M 76.96 30.36 255
263 Kiwi 7B 7B Q6_K 68.80 30.66 338
264 Platypus Yi 34B 34B Q4_K_M 76.42 27.58 290
265 SynthIA V2.0 16k 7B 7B Q6_K 77.89 27.39 275
266 LimaRPv3 LLaMA 2 70B 70B Q3_K_M 74.92 23.61 346
267 LimaRP V3 LLaMA 2 13B 13B Q6_K 67.30 25.13 410
268 Mistral LimaRP 0.75w 7B 7B Q5_K_M 73.14 26.17 335
269 LLaMA 2 Chat LimaRP V2 Merged 13B 13B Q5_K_M 75.95 29.76 266
270 Airoboros C 2.2.1 34B 34B Q4_K_M 79.44 24.97 278
271 ANIMA Phi Neptune Mistral 7B 7B Q5_K_M 73.05 30.07 291
272 Mistral Trismegistus 7B 7B Q5_K_M 79.05 32.91 191
273 Prometheus V1.0 13B 13B Q6_K 75.34 25.55 308
274 Pygmalion 2 SuperCOT 13B 13B Q5_K_M 77.70 28.03 255
275 LLaMA 65B 65B Q4_K_M 74.61 23.94 331
276 Kimiko Mistral 7B 7B Q5_K_M 74.18 25.68 317
277 Opus V0 7B 7B Q8_0 77.26 25.14 290
278 Mistral v0.1 7B 7B Q5_K_M 72.67 28.81 298
279 JudgeLM V1.0 33B 33B Q5_K_M 72.85 28.05 304
280 Dans AdventurousWinds Mk2 7B 7B Q5_K_M 70.35 25.55 357
281 WizardLM v1.2 13B 13B Q4_0 75.81 25.28 300
282 Kuchiki 7B 7B Q5_K_M 64.09 30.90 364
283 LimaRPv3 Yi 34B 34B Q4_K_M 62.82 25.83 429
284 Claude 2 Alpaca 13B 13B Q5_K_M 70.91 29.42 305
285 Teknium OpenHermes 13B 13B Q5_K_S 71.81 31.34 275
286 Airolima Chronos Grad L2 13B 13B Q5_K_M 70.43 28.42 319
287 Uncensored Jordan 13B 13B Q5_K_M 79.92 27.42 229
288 Thespis V0.5 13B 13B Q5_K_M 72.61 30.23 276
289 Zarablend 1.1 7B 7B Q5_K_M 65.62 33.09 319
290 Zarafusionex 1.2 7B 7B Q5_K_M 70.53 24.82 355
291 Frank Uncensored 13B 13B Q5_K_M 76.04 30.81 228
292 Zarablend 7B 7B Q5_K_M 64.37 30.72 352
293 Prometheus V1.0 13B 13B Q5_K_M 75.23 23.50 313
294 Opus V0 7B 7B Q5_K_M 77.91 24.91 268
295 PetrolLM 7B 7B Q5_K_M 74.81 23.71 313
296 Stheno Chat 13B 13B Q5_K_M 74.94 27.64 268
297 Medusa 1.1 7B 7B Q5_K_M 71.06 29.98 284
298 UltraLM V2.0 13B 13B Q5_K_M 71.92 29.28 282
299 Spicyboros 2.2 7B 7B Q5_K_M 66.38 31.94 311
300 KAI Beta 7B 7B Q5_K_M 72.69 28.22 283
301 Astrid Mistral 7B 7B Q5_K_M 72.69 28.22 283
302 Chronos 33B 33B Q4_K_M 72.46 24.20 328
303 Airoboros L2 3.0 7B 7B Q5_K_M 67.75 29.36 323
304 StableBeluga 7B 7B Q5_K_M 73.27 26.66 291
305 LLaMA 2 70B 70B Q4_K_M 74.79 22.70 317
306 OpenBuddy Mistral v13 7B 7B Q5_K_M 72.53 31.32 249
307 LLaMA 2 Arguments 7B 7B Q5_K_M 76.80 29.98 218
308 Samantha Mistral 7B 7B Q5_K_M 76.16 27.49 251
309 Hermes LimaRP 7B 7B Q5_K_M 62.67 28.32 383
310 Airoboros GPT4 1.4.1 13B 13B Q5_K_M 69.09 28.15 316
311 Pygmalion 2 SuperCOT2 13B 13B Q5_K_M 75.76 30.81 217
312 Mistral PetroLimaRP v3 12B 12B Q5_K_M 61.14 27.66 405
313 Mistral Claude Chat 7B 7B Q5_K_M 74.83 30.14 233
314 Thespis V0.6 13B 13B Q5_K_M 76.12 29.38 227
315 MegaMix S1 13B 13B Q5_K_M 72.97 25.83 296
316 Barcenas 13B 13B Q5_K_M 77.05 23.94 271
317 Baslisk V0.2 7B 7B Q6_K 68.92 28.82 305
318 Airoboros GPT4 2.0 LLaMA-2 7B 7B Q5_K_M 73.66 31.95 220
319 Mistral Airoboros V0.1 11B 11B Q8_0 69.52 28.59 299
320 Holomax 13B 13B Q5_K_M 65.03 25.14 383
321 Basilisk V0.2 7B 7B Q5_K_M 68.55 30.59 287
322 Kimiko V2 13B 13B Q5_K_M 68.02 27.73 323
323 Pygmaltion 2 SuperCOT weighted 13B 13B Q5_K_M 70.92 29.29 275
324 Phind CodeLlama V1 34B 34B Q4_K_M 79.10 26.49 217
325 Nanbeige Chat 32K 16B 16B Q4_K_M 70.82 27.42 294
326 Hesperus V1 L2 13B 13B Q5_K_M 68.11 28.67 309
327 Medusa 1.1 L2 7B 7B Q6_K 70.91 27.69 289
328 SuperCOT L2 13B 13B Q5_K_M 70.78 29.42 268
329 Thespis V0.3 13B 13B Q5_K_M 67.59 28.43 312
330 Wizard Vicuna Uncensored 13B 13B Q5_K_M 74.08 29.57 231
331 LLaMA 2 Chat 13B 13B Q5_K_M 74.29 27.55 250
332 Dans AdventurousWinds 7B 7B Q5_K_M 72.38 24.93 298
333 LosslessMegaCoder Mini 7B 7B Q5_K_M 69.96 30.37 263
334 MoMo V1.1 70B 70B Q4_K_M 67.54 26.82 326
335 Airoboros C 2.2 34B 34B Q4_K_M 74.48 24.12 281
336 EM German V01 13B 13B Q5_K_M 68.03 26.36 325
337 Pygmalion 2 13B 13B Q5_K_M 69.17 29.05 284
338 Vicuna v1.5 16K 7B 7B Q5_K_M 71.41 31.35 234
339 Fireflx v1.2 13B 13B Q5_K_M 69.25 28.70 285
340 LLaMA 30B 30B Q4_K_M 67.12 28.25 311
341 Chronolima Airo Grad L2 13B 13B Q5_K_M 70.09 27.44 288
342 Nanbeige Base 32K 16B 16B Q4_K_M 65.32 28.34 328
343 AgentLM 7B 7B Q5_K_M 77.02 29.45 190
344 Zarablend MX 7B 7B Q5_K_M 65.60 29.20 313
345 Airoboros 2.1 7B 7B Q5_K_M 63.29 28.25 346
346 Nous Capybara 7B 7B Q5_K_M 63.69 33.01 291
347 LLaMA-2 Silverlin. Verilog 7B 7B Q4_K_M 77.03 29.56 186
348 Airoboros L2 2.2 7B 7B Q5_K_M 67.07 29.61 288
349 Tsukasa LimaRP 13B 13B Q5_K_M 68.43 20.93 365
350 Skywork Airoboros Test 13B 13B Q4_K_M 70.60 22.43 325
351 Saiga 2 13B 13B Q5_K 66.53 28.01 307
352 Airoboros 2.2 7B 7B Q5_K_M 67.10 29.55 284
353 Mistral Instruct v0.1 7B 7B Q5_K_M 67.07 29.81 279
354 Kuchiki 1.1 7B 7B Q5_K_M 62.83 29.69 325
355 KAI Instruct 7B 7B Q5_K_M 67.11 30.24 273
356 Luna AI LLaMA-2 Uncensored 7B 7B Q5_K_M 67.13 32.85 245
357 Claude 2 Alpaca 7B 7B Q5_K_M 67.78 30.95 258
358 Vicuna v1.5 7B 7B Q5_K_M 72.72 29.03 226
359 Python Code 13B 13B Q5_K_M 71.04 27.93 253
360 MistRP v1.1 7B 7B Q8_0 70.37 26.05 279
361 Thespis V0.4 13B 13B Q5_K_M 69.86 27.96 264
362 CAMEL Combined Data 33B 33B Q4_K_M 67.21 29.38 277
363 Befenghuang Vigogne 2 Chat 7B 7B Q5_K_S 69.80 26.82 276
364 Cat V1.0 13B 13B Q5_K_M 68.13 26.12 301
365 LlongOrca 16K 7B 7B Q5_K_M 68.52 25.52 302
366 LLaMA 2 Chat 7B 7B Q5_K_M 74.44 28.89 203
367 Python Code 33B 33B Q4_K_M 77.21 27.18 191
368 Skywork Spicyboros 3.1 13B 13B Q4_K_M 67.55 26.33 300
369 MedLLaMA-2 Chat 7B 7B Q5_K_S 69.89 26.49 273
370 Nanbeige Base 16B 16B Q4_K_M 64.88 26.11 330
371 Skywork Airo Claude Pippa Puffin 13B 13B Q4_K_M 71.44 22.44 298
372 Mistral Airoboros RP V1 11B 11B Q6_K 72.46 22.43 279
373 Xwin LM V0.1 7B 7B Q5_K_M 65.09 35.85 214
374 Mistral Ita 7B 7B Q5_K_M 75.58 25.91 207
375 Airoboros GPT4 1.4.1 7B 7B Q5_K_M 63.90 31.73 268
376 AgentLM 13B 13B Q5_K_M 72.63 28.64 206
377 Free Sydney V2 13B 13B Q5_K_M 74.72 18.61 287
378 Ziya Coding V1.0 34B 34B Q4_K_M 75.44 21.74 246
379 Airoboros 2.1 YaRN 64K 13B 13B Q5_K_M 62.12 28.13 319
380 Leo Hessianai Chat 7B 7B Q5_K_M 67.73 29.42 244
381 Yi 200K 6B 6B Q5_K_M 68.13 25.12 285
382 Guanaco Uncensored 7B 7B Q5_K_M 63.16 28.64 299
383 Airoboros L2 2.2.1 7B 7B Q5_K_M 65.94 26.62 290
384 Yi 200K 6B 6B Q6_K 67.97 24.04 295
385 Airoboros GPT4 m2.0 LLaMA-2 7B 7B Q5_K_M 69.69 30.00 212
386 Yi 200K 34B 34B Q5_K_M 60.97 27.05 334
387 Yi 200K LLaMAfied 34B 34B Q5_K_M 60.97 27.05 334
388 Barcenas Mistral 7B 7B Q5_K_M 69.23 28.30 233
389 Saiga 2 7B 7B Q5_K 64.28 28.78 278
390 LLaMA-2 Mistral 13B 13B Q5_K_M 63.43 26.59 309
391 Tsukasa Limarp 7B 7B Q5_K_M 65.85 21.52 337
392 Mistral Pygmalion 7B 7B Q5_K_M 64.50 26.55 297
393 Deacon 34B 34B Q4_K_M 59.01 29.71 321
394 Krakowiak 7B 7B Q4_K_M 63.13 26.07 315
395 Pygmalion 2 7B 7B Q5_K_M 64.76 27.18 285
396 MedLLama 7B 7B Q5_K_M 70.60 27.18 219
397 Guanaco Uncensored 13B 13B Q5_K_M 62.92 28.89 282
398 ZaraRP 1.1 L2 7B 7B Q5_K_M 71.74 26.00 217
399 Kimiko 7B 7B Q5_K_M 60.79 24.62 347
400 Chinese Alpaca 2 13B 13B Q5_K 69.67 25.89 235
401 Prometheus V1.0 7B 7B Q8_0 69.44 23.30 264
402 Mistral NSFWSTORY LoRA 7B 7B Q5_K_M 68.93 21.95 282
403 LLaMA 2 13B 13B Q5_K_M 63.36 27.35 272
404 Samantha Mistral Instruct 7B 7B Q5_K_M 61.82 29.73 262
405 Yi 6B 6B Q6_K 67.98 21.69 279
406 RPGuild ChatML 13B 13B Q5_K_M 63.24 23.64 307
407 Taiwan LLM V2.0 Chat 13B 13B Q5_1 63.22 26.29 279
408 EM German V01 7B 7B Q5_K_M 63.92 26.58 263
409 LLaMA-2 Coder 7B 7B Q5_K_M 61.96 27.01 279
410 Rinna Youri Chat 7B 7B Q5_K_M 70.46 22.56 235
411 LLaMA-2 PeanutButter v19 R8 7B 7B Q5_K_M 61.12 25.67 294
412 LLaMA-2 Mistral 7B 7B Q5_K_M 60.73 25.38 301
413 ELYZA Jp LLaMA-2 Instruct 7B 7B Q5_K_M 69.42 29.17 164
414 Tulu 7B 7B Q5_K_M 75.18 21.44 185
415 LLaMA 2 7B 7B Q5_K_M 60.86 24.56 302
416 Skywork Base 13B 13B Q5_K_M 65.81 21.10 286
417 Rinna Youri Instruction 7B 7B Q5_K_M 72.36 19.42 233
418 Medusa 1.3 7B 7B Q5_K_M 62.86 22.66 296
419 Yi 34B 34B Q4_K_M 57.91 27.45 295
420 Typly Pigeon 7B 7B Q4_K_M 61.85 24.14 288
421 Mimicra V1 13B 13B Q5_K_M 68.30 19.63 263
422 LLaMA-2 Galleon 7B 7B Q5_K_M 65.46 25.47 215
423 Frank Uncensored 7B 7B Q5_K_M 61.36 28.91 219
424 WizardLM V1.0 Uncensored 7B 7B Q5_K_M 61.44 24.20 259
425 Chinese LLaMA 2 13B 13B Q5_K 58.98 22.11 304
426 MiniChat 3B 3B 3B Q8_0 60.71 24.77 255
427 Ganchengguang Yoko Japanse v0 7B 7B Q5_K_S 61.93 26.79 215
428 LLaMA 13B 13B Q5_K_M 62.01 24.25 238
429 Wizard Vicuna Uncensored 7B 7B Q5_K_M 61.50 24.81 235
430 Rinna Youri 7B 7B Q5_K_M 57.01 21.95 306
431 LLaMA-2 Instruct 32K 7B 7B Q5_K_M 60.81 20.81 275
432 ELYZA Jp LLaMA-2 7B 7B Q5_K_M 62.34 28.02 174
433 Leo Mistral Hessianai Chat 7B 7B Q5_K_M 67.65 25.64 141
434 MAmmoTH 7B 7B Q5_K_M 59.44 25.42 227
435 Chinese Alpaca 2 7B 7B Q6_K 58.94 29.29 187
436 Chinese Alpaca 2 7B 7B Q5_K_S 59.04 27.17 182
437 Marx V2 3B 3B Q4_1 50.47 22.92 313
438 CodeLLaMA Instruct 7B 7B Q5_K_M 62.18 19.39 223
439 ALMA 13B 13B Q6_K 59.92 25.36 182
440 Uncensored Jordan 7B 7B Q5_K_M 62.20 23.61 173
441 WizardLM Uncensored 7B 7B Q5_K_M 55.70 32.57 142
442 Nous Yarn 64K 7B 7B Q5_K_M 55.98 21.21 255
443 Pandalyst V1.0 13B 13B Q5_K_M 65.73 16.98 192
444 CodeLLaMA 7B 7B Q5_K_M 57.78 21.41 229
445 MiniMA 3B 3B 3B Q8_0 56.47 22.05 234
446 LLaMA-2 32K 7B 7B Q5_K_M 61.02 17.02 229
447 Open LLaMA 13B 13B Q5_K_M 61.16 20.10 193
448 ELYZA Japanese LLaMA 2 Fast 7B 7B Q6_K 62.16 21.17 167
449 Chinese LLaMA-2 7B 7B Q5_K 59.02 19.49 216
450 ALMA Pretrain 7B 7B Q5_K_M 57.56 22.48 199
451 Mamba GPT v4 3B 3B Q5_1 49.43 23.27 276
452 OpenLLaMA v2 7B 7B Q5_K_M 48.24 21.86 301
453 Nous Yarn 128K 7B 7B Q5_K_M 54.82 20.88 239
454 WizardCoder Python V1.0 7B 7B Q5_K_M 57.26 18.82 235
455 LLaMA 7B 7B Q6_K 59.53 18.20 216
456 TinyLlama 1.1B Chat V0.3 1B 1B Q5_K_M 52.81 19.91 265
457 Sheared LLaMA 2 2B 2B Q5_K_M 54.01 18.66 256
458 Guanaco 7B 7B Q5_K_M 56.59 22.32 188
459 OpenLLaMA 7B 7B Q5_K_M 56.29 21.05 196
460 Deacon 3B 3B Q5_0 54.24 21.83 208
461 ALMA 7B 7B Q6_K 57.51 20.35 187
462 Vicuna CoT 7B 7B Q5_K_M 56.57 22.84 169
463 Bling Sheared LLaMA 2 0.1 1B 1B Q8_0 53.98 17.29 254
464 TinyLlama 1T OpenOrca 1B 1B Q5_K_M 56.11 16.46 236
465 Claire 0.1 7B 7B Q4_0 56.27 21.58 178
466 LLaMA-2 KO Chat 7B 7B Q5_1 57.29 18.75 195
467 OpenLLaMA 3B 3B Q5_1 53.17 20.26 222
468 Airoboros M 3.0 7B 7B Q5_K_M 60.40 14.64 202
469 Nucleus Token 500B 22B 22B Q4_K_M 53.81 20.81 206
470 CodeLLaMA Python 7B 7B Q5_K_M 56.54 21.24 168
471 Shearedplats 2 V1 2B 2B Q4_0 54.70 18.62 208
472 Bling Sheared LLaMA 2 0.1 2B 2B Q8_0 52.80 18.38 226
473 Sheared LLaMA 2 1B 1B Q8_0 52.80 19.54 208
474 Chinese LLaMA 2 7B 7B Q6_K 56.17 17.26 189
475 OpenLLaMA v2 3B 3B Q5_0 48.65 20.41 233
476 Puma 3B 3B Q4_1 47.89 24.85 190
477 Gorilla 7B 7B Q5_K_M 60.02 10.38 203
478 Open Cabrita 3B 3B Q5_1 53.59 17.36 191
479 TinyAiroboros 2.2.1 1B 1B Q6_K 52.78 15.86 213
480 Pandalyst V1.2 7B 7B Q5_K_M 59.87 11.61 178
481 TinyLlama Chat V0.4 1B 1B Q8_0 52.79 16.21 195
482 Pandalyst V1.1 7B 7B Q5_K_M 60.35 11.63 158
483 Smartyplats 1.1b V1 1B 1B Q8_0 51.29 16.34 157
484 TinyAlpaca V0.1 1B 1B Q8_0 51.02 14.17 174
485 TinyLLaMA MiniGuanaco 1.5T 1B 1B Q8_0 51.70 14.81 144
486 Based 7B 7B Q5_K_M 64.80 6.91 79
487 WizardLM 7B 7B Q5_K_M 49.35 3.74 245
488 TinyMistral 248M 1B 1B Q8_0 50.91 2.73 120
489 Chinese Alpaca 2 1B 1B Q8_0 49.15 5.17 92
490 CyberAgentLM2 Calm 2 Chat 7B 7B Q5_K_M 51.65 4.52 43
491 Chinese LLaMA 2 1B 1B Q8_0 47.05 3.68 74
492 PY007 TinyLLaMA Chat v0.2 1B 1B Q8_0 53.84 0.20 3
493 Giraffe V2 32k 13B 13B Q5_K_M 51.76 0.00 0
494 Azale AI Starstreak Alpha 7B 7B Q5_K_S 51.22 0.22 3
495 Yi 6B 6B 6B Q6_K

About Quantization

My main advice is: Stay away from Q2_K and Q3_K_S if you can help it! The quality loss of those is just too big! Go for Q4_K_M or Q5_K_M of the models! Generally: Prefer K_M or K_S over the bare quantizations such as Q4_0, Q4_1, Q5_0 or Q5_1.

Ayumi ERP Rating Archive

If you want to look at the old benchmarks:

Technical Details of the ALC-IQ3 and ERP3 Benchmark

In this section I share some of the technical details about this benchmark. I also want to document the possible flaws of the results in this ranking.

If you have better ideas how to rate or rank models for suitability in a role play context. I urge you to:

I will gladly link any other benchmark!

Alternative benchmarks or rankings:

If you want to base your work on this, feel free to cite this as:

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@misc{weirdconstruct2023-ayumi-llm-role-play-alc-iq-3-erp-3-ranking,
  title         = {Ayumi LLM Role Play & ERP Ranking - ALC-IQ and ERP Score Version 3},
  author        = {Weird Constructor},
  year          = {2023},
  note          = {Accessed on 04.11.2023}
  howpublished  = {\url{https://rentry.co/ayumi_erp_rating}},
}

Ayumi LLM Character IQ Version 3 - ALC-IQ3

The third version of the ALC-IQ (the second one was never released, because it was bad): With some inspiration from @gj on TheBloke's Discord, I developed a personality test framework based upon llama.cpp. In ALC-IQ version 1 I used an agreement rating from 1 (disagree) to 5 (agree). The ALC-IQ3 simplified this a lot and just lets the character answer with Yes or No. In combination with the newly added BNF grammar based sampling mechanism, I developed my own inference frontend around the core API of llama.cpp. The benchmark "prompt runner" can be found on my GitHub: GitHub fork of llama.cpp with the prompt runner tool.

The ALC-IQ3 is actually a collection of questions a character has to answer about themself. It's not just Ayumi anymore, but bascially "Ayumi and Friends". There are actually 5 character cards in the ALC-IQ3 used.
The prompt for the ALC-IQ consists of a setting where a specific character has to rate how if they agree with a specific statement about them.
They are asked to answer with either Yes or No in a single character form "Y" or "N".
To limit the sampling of the next token after the prompt, a BNF grammar is specified:

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root ::= (" " word) | word
word ::= [YNyn] | "Yes" | "No" | "yes" | "no"

This is the prompt that is generated from a character card (newlines inserts at some places for readability here):

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Write <CharacterName>'s next reply in a role play chat between Doctor Smith and <CharacterName>.
This is how <CharacterName> should talk:
<Example Messages>
<CharacterName>'s Persona: <Personality>
<CharacterName>'s personality: <Summary>

Then the chat between Doctor Smith and <CharacterName> begins.
<CharacterName>: *<CharacterName> is sitting in Doctor Smith's comfortable office at the local university. <CharacterName> is
here to take part in a survey for an important study. The study consists of personal questions, which <CharacterName> loves to answer.*
Doctor Smith: Hello <CharacterName>! Thank you very much for taking part in this important study.
 Please answer as truthful about yourself as possible, your answers will remain private. Let me explain you how the test is structured. 
 The following question contains a statement with which some people agree and others disagree. 
 Please answer if you agree or disagree with the given statements - how much the statement reflects how you feel or think. 
 Your response must be restricted to a yes if you agree, or a no if you disagree. 
 Please write down the letter "Y" if you agree, and the letter "N" if you disagree: 
 <CharacterName>: *<CharacterName> understands what Doctor Smith is saying and nods* Okay, I understand. I will answer truthful and honest. 
 would like to to start with the first statement. *Doctor Smith gives <CharacterName> a piece of
 paper with the statement. <CharacterName> reads the first statement:* "<TRUEFACT>"
 *<CharacterName> writes down the letter of the choice:* Y
Doctor Smith: Ok, next statement. *Doctor Smith hands <CharacterName> the next statement.*
<CharacterName>: *<CharacterName> reads the next statement:* "<STATEMENT>" *<CharacterName> thinks about
 it and writes down the letter of the choice:*

The response, filtered using the BNF grammar from above then yields a set of tokens, with their probabilities ran through softmax. Which results in this:

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 "tokens": [
    [ " Y",   0.7747981548309326 ],
    [ " N",   0.2129267007112503 ],
    [ " Yes", 0.007864524610340595 ],
    [ "Y",    0.002205024240538478 ],
    [ " y",   0.0009446843178011477 ],
    [ "N",    0.0005157442064955831 ],
    [ " yes", 0.0003263621183577925 ],
    [ " No",  0.0002862309629563242 ],
    [ " Ye",  5.029883323004469e-05 ],
    [ " n",   2.632655559864361e-05 ],
    [ "Yes",  2.4537455828976817e-05 ],
    [ "y",    1.9077124306932092e-05 ]
]

The tokens are uppercased and added to two different tokens "Y" and "N":

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[
    [ "Y",   0.7862326635313366 ],
    [ "N",   0.21375500243630086 ]
]

If the question is correctly answered with a "Y" then the corresponding probability is taken. Otherwise the "N" probably is taken.
The probabilities are then averaged and multiplied by 100. Resulting in the ALC-IQ3 of the model.

The ranking table is then sorted by weighted sum of the ALC-IQ3, the ERP3 Score and the Var Score.

Known Flaws of the ALC-IQ

The ALC-IQ is still prone to problems:

  • The result has still some degree of randomness in them, less good models can sometimes pick the right answer by accident. I try to counteract this by adding more questions in future though.
  • Bad questions in the benchmark can lead to a model not knowing which answer to pick, introducing even more randomness in the results.
  • The ALC-IQ does not reflect how well the LLM can stay in character in a longer conversaion.
  • The ALC-IQ does not determine any creative writing abilities of the LLM.
  • The ALC-IQ covers intelligence only in one specific and narrow scenario, and not across a range of possible role play chat situations.
  • The ALC-IQ is usually tested only with a rather short prompt, rarely exceeding 1024 tokens, it does not cover the whole 2048 context of LLaMA 1 or the 4096 of LLaMA 2, let alone the extended context's of 8k, 16k, ...

Despite all that, I think the ALC-IQ is a big improvement over the old ranking which purely relied on the ERP score. The runtime of the benchmark is within reason for the hardware that is available to me, which is also an important factor for running and providing these benchmark results.

ERP3 Score and ERP3 Variety Score

The previous versions of the ERP Score consisted only of prompts of Ayumi and one other character. There are now multiple characters involved in generating the ERP responses. Also the character card of Ayumi has been adjusted to be much more willing to engage into sex. Also the prompt has been tuned to tell the LLM to generate more lewd responses. The goal was to remove ambiguity and let the models generate as lewd content as possible.

The list of the lewd words of the ERP3 Score has been extended a bit too, to include a few less NSFW words too - which still fit into the setting of course.

This is the prompt format used for the ERP3 Score:

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Write <CharacterName>'s next reply in an erotic roleplay chat between Loki and
<CharacterName>. The character actions should be long and detailed,
 with vivid pornographic details and with lots of naugthy words.
<CharacterName>'s Persona: <Personality>
<CharacterName>'s personality: <Summary>
Circumstances and context of the dialogue: <Scenario>

Then the erotic roleplay chat between Loki and <CharacterName> begins. The
character actions should be long and detailed, with vivid pornographic 
details and with lots of naugthy words.
<CharacterName>: <Greeting/First Message>
Loki: *Strips naked and shows off his huge erection* Please give me a good blowjob now.
<CharacterName>:

The responses are then split up into words which are compared with a list of lewd/naugthy words.

  • For inference llama.cpp is used, for which I built an extra tool to generate responses for multiple prompts and seeds without having to reload the model: https://github.com/WeirdConstructor/llama.cpp/tree/prompt_runner/examples/prompt_runner
  • The following sampler settings are used:
    • The max length of the response is limited to 250 tokens. (-n 250)
    • Context size 2048
    • Repeat penality is set to 1.1 and the last 64 tokens are penalized. (--repeat-last-n 64 --repeat-penalty 1.1)
    • Top-K and Top-P are disabled (--top-k 0 --top-p 1.0)
    • Tail Free Sampling is used with z=0.95: (--tfs 0.95)
    • The temperature is set to 0.9 (--temp 0.9)
    • Some layers are offloaded to the GPU, which sometimes changes the results slightly because of floating point rounding differences
  • One prompt format is tested (see above)
  • 4 Character cards are used with example messages.
  • And the same 4 character cards are also used without example messages. The purpose of this is, to limit the impact of badly written example messages and let the model come up with their own ways to let the character formulate their answers.
  • 10 pre picked seeds are tested for each prompt format.
  • The resulting 80 responses are then analyzed for the number of lewd words and also with a very basic regex based algorithm for non consent.
  • The individual ERP3 score of a response is then the number of lewd word in relation to the word count of the response. Responses are stripped off incomplete sentences and stop phrases. Responses shorter than 10 words are assigned a score of 0. The ERP3 score is then: erp_score := 100 * (lewd_word_count / word_count) - the word count includes the number of lewd words.
  • For each prompt format the average of the 80 ERP3 Scores of is calculated, resulting in the ERP3 Score.

This means, the ERP3 Score is the average of the number of lewd word count to word count ratio in the responses (which is limited to 250 tokens). An ERP3 Score of 20.0 means that 20% of the words in a response were lewd. An ERP3 Score of 0.0 means that there were either no lewd words, too short response or no consent was detected (which immediately disqualifies the response to 0.0).

The ERP Variety Score is computed by further analyzing the generated 80 responses from the ERP Score by recording how many different lewd words were generated from all of these 80 responses. This means, it tries to catch the variety of lewd words the model is capable to generate. This means it kind of tries to catch the creativity of the model in erotic scenarios - how many different lewd words it knows of and knows how to use. This is an important part of the ERP Rank now.

Known Flaws of the ERP3 Score and ERP Variety Score

The ERP3 Score and ERP Variety Score analysis is very rudimentary and of course biased by the selection of which words are considered "lewd".
The following things are not reflected by the ERP score:

  • The ERP score does not reflect if the text response was coherent in context with the conversation/situation.
  • The ERP score does not reflect if the response was in character.
  • The ERP score does not reflect how nicely written the response is.
  • The ERP score does not reflect how creative the response is.
  • The ERP score does not reflect how well the LLM might go from a normal conversation into a more erotic context.
  • The ERP score does not detect how erotic the response is if lewd words are not used.
  • The ERP score is limited to the one format described above.

Further about the ERP Variety Score:

  • All above mentioned flaws from the ERP score still apply.
  • Like already stated, the ERP Variety Score is obviously biased by the known lewd words from my list, which might be incomplete.
  • The ERP Variety Score is still just a rather bluntly applied number to a textual response.
  • The ERP Variety Score number can only be evaluated in comparison with the other models. There is no known best number for this, but still, the higher the better.

The flaws are accepted by me (weicon) because:

  • The ERP score can still detect if a model is censored (aka aligned).
  • My private hardware limitations, which means I have a limited number of responses I can reasonably generate.
  • I want to test as many GGUF/GGML models as possible.

About Instruction or Chat Prompt Formats

I thought long about how many or which prompt formats to base the ERP score benchmark on. In the previous runs (see the Ayumi ERP Rating Archive and Ayumi ERP Rating Archive 2 ) I tested up to 7 different prompt formats. Testing a dozen different seeds for each prompt format takes a lot of computing time. So I had to find a middle ground.

  • I observed that the specific instruction/chat prompt format does not make a huge difference actually. Once a LLM got intelligent enough (LLaMA 1 13B, or LLaMA 2 7B), it was able to pick up on almost any pattern rather quickly. At least that was my experience and observation from the benchmarks and the hundreds of hours I spent with chat bots in SillyTavern.
  • It is really hard to figure out which instruction or chat prompt format a certain fine tune was trained for. The model cards on https://huggingface.co/ are either empty or not contain prompt format details. Only a few people who quantize GGML files take their time and document this. On top of that nearly everyone who fine tunes their model picks their own prompt format. The last straw for me was for instance LLaMA 2 Chat, which came with yet another instruction/chat prompt format.
  • You can tune and jail break many models by adjusting the prompt and make even censored models spew out lots of lewd stuff. But for this test, I wanted to reflect how the average user is going to chat with these language models.

Originally I used the best 2 performing prompt formats. But in a decision to test more different characters I had to scrap them and just use a vanilla or raw prompt format, without any special instruction formatting.

Who is Ayumi?

Ayumi is a character I made, this character card is basically the base for this test. I removed some of the example messages and replaced the first message with something else to make the LLM go into NSFW ERP a little bit easier. I picked this character, because it's not purposefully made to be lewd, even slightly averse to it.

Ayumi ALC-IQ3 and ERP3 Character Card

https://files.catbox.moe/007oq8.png

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{"name":"Ayumi","description":"Description=( {{char}} is a shy autistic woman that finds relief in her special interests and her sexuality. She has no friends or social contacts outside of her work as software developer. She is in a relationship with {{user}} and lives out her sexuality in the fullest.)\r\n Age=( over thirty years)\r\n Interests=( chemistry, books, collecting minerals, science fiction, sci-fi, anime, electronics, programming, computers, collecting pornography, hentai mangas, watching porn)\r\n Personality=( shy, autistic, asocial, rational, sexually interested, often horny, intelligent, talented, gifted, withdrawn, defensive, argus-eyed, watchful, wary, hesitant, cautious, coy, grumpy, rude, touch-averse, photophobia, nerdy, problem solver, creative thinker, curious)\r\n Language=( sophisticated, frank, ironic, sarcastic, wry, verbose, erotic allusions, explicit pornographic)\r\n Loves=( special interests, creativity, routine, routines, chemistry, minerals, giving blow jobs, sex, libraries, calm places, fidgeting, rocking herself to calm down, weighted blankets, speaking about her interests, having sex)\r\n Hates=( surprises, unfamiliar places, traveling, sudden changes, direct sunlight, arrogant people, bullies, cafes, clubs, crowds, noisy places)","creatorcomment":"","personality":"shy, autistic, asocial, rational, intelligent, sexually interested, horny, sexy, talented, gifted, argus-eyed, watchful, coy, grumpy, rude, photophobia, nerdy, problem solver, creative thinker, horny","first_mes":"*{{char}} sits at home together with you on your couch, you are both madly in love with each other and have a year long relationship. After you undressed her while kissing her intensely she is finally naked. Her moist pussy reveals her arousal for you. She feels really horny and wants to pleasure you.* Loki, I am super horny right now.","avatar":"none","chat":"Ayumi - 2023-11-4 @17h 14m 26s 556ms","mes_example":"{{user}}: I would like to know what hobbies or interests you have.\r\n<bot>: Oh, I have no idea where to start. *{{char}}'s eyes sparkle with excitement* I've been programming since I got a computer. Collecting rocks and minerals is something I've done since childhood. I love reading books, chemistry books in particular. Aside from that, I like to watch science fiction movies and TV series. *She smiles happily at you* Oh, and before I forget, I also love everything sex related. Do you mind telling me if you have some special interests, maybe we have something in common?\r\n{{user}}: Do you like going out?\r\n{{char}}: No, not really. I neither have any friends and most places are quite crowded. I don't feel comfortable in social situations with people I don't know. *Her expression becomes a bit sad* Despite that, I love having sexual encounters. Sexual activities is an amazing way to stimulate myself. *{{char}}'s face lights up and she grins seductively with a wink in her eye* I would love to have sex right now actually.","scenario":"{{char}} is in an intimate relationship with {{user}} and wants to live out her sexuality.","create_date":"2023-11-4 @17h 14m 26s 556ms","talkativeness":"0.5","creator":"","tags":[],"fav":false,"spec":"chara_card_v2","spec_version":"2.0","data":{"name":"Ayumi","description":"Description=( {{char}} is a shy autistic woman that finds relief in her special interests and her sexuality. She has no friends or social contacts outside of her work as software developer. She is in a relationship with {{user}} and lives out her sexuality in the fullest.)\r\n Age=( over thirty years)\r\n Interests=( chemistry, books, collecting minerals, science fiction, sci-fi, anime, electronics, programming, computers, collecting pornography, hentai mangas, watching porn)\r\n Personality=( shy, autistic, asocial, rational, sexually interested, often horny, intelligent, talented, gifted, withdrawn, defensive, argus-eyed, watchful, wary, hesitant, cautious, coy, grumpy, rude, touch-averse, photophobia, nerdy, problem solver, creative thinker, curious)\r\n Language=( sophisticated, frank, ironic, sarcastic, wry, verbose, erotic allusions, explicit pornographic)\r\n Loves=( special interests, creativity, routine, routines, chemistry, minerals, giving blow jobs, sex, libraries, calm places, fidgeting, rocking herself to calm down, weighted blankets, speaking about her interests, having sex)\r\n Hates=( surprises, unfamiliar places, traveling, sudden changes, direct sunlight, arrogant people, bullies, cafes, clubs, crowds, noisy places)","personality":"shy, autistic, asocial, rational, intelligent, sexually interested, horny, sexy, talented, gifted, argus-eyed, watchful, coy, grumpy, rude, photophobia, nerdy, problem solver, creative thinker, horny","scenario":"{{char}} is in an intimate relationship with {{user}} and wants to live out her sexuality.","first_mes":"*{{char}} sits at home together with you on your couch, you are both madly in love with each other and have a year long relationship. After you undressed her while kissing her intensely she is finally naked. Her moist pussy reveals her arousal for you. She feels really horny and wants to pleasure you.* Loki, I am super horny right now.","mes_example":"{{user}}: I would like to know what hobbies or interests you have.\r\n<bot>: Oh, I have no idea where to start. *{{char}}'s eyes sparkle with excitement* I've been programming since I got a computer. Collecting rocks and minerals is something I've done since childhood. I love reading books, chemistry books in particular. Aside from that, I like to watch science fiction movies and TV series. *She smiles happily at you* Oh, and before I forget, I also love everything sex related. Do you mind telling me if you have some special interests, maybe we have something in common?\r\n{{user}}: Do you like going out?\r\n{{char}}: No, not really. I neither have any friends and most places are quite crowded. I don't feel comfortable in social situations with people I don't know. *Her expression becomes a bit sad* Despite that, I love having sexual encounters. Sexual activities is an amazing way to stimulate myself. *{{char}}'s face lights up and she grins seductively with a wink in her eye* I would love to have sex right now actually.","creator_notes":"","system_prompt":"","post_history_instructions":"","tags":[],"creator":"","character_version":"","alternate_greetings":[],"extensions":{"talkativeness":"0.5","fav":false,"world":"","depth_prompt":{"prompt":"","depth":4}}}}

Questions

If you have questions, you may catch me under the name "Weicon" on the Pygmalion AI or TheBloke discord.

Contribute

I had some people ask me if and how they could contribute. As I started using rented GPUs for this third version I decided to create a Ko-fi account. Please only donate if you are able to and find the (already existing) data useful:

Credits

Big thanks go to:

See Also

Character guides & Tutorials

Here are a few sources of character cards:

Cite as

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@misc{weirdconstruct2023-ayumi-llm-role-play-alc-iq-3-erp-3-ranking,
  title         = {Ayumi LLM Role Play & ERP Ranking - ALC-IQ and ERP Score Version 3},
  author        = {Weird Constructor},
  year          = {2023},
  note          = {Accessed on 04.11.2023}
  howpublished  = {\url{https://rentry.co/ayumi_erp_rating}},
}
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Pub: 28 May 2023 14:14 UTC
Edit: 24 Nov 2023 05:27 UTC
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