Performance ranking (third-party evaluations)
Performance ranking of models that run in 12 GB of VRAM (LMArena)
Scores computed from people voting between two models' answers (Bradley-Terry, with style control). The range is the 95% interval; differences between models whose ranges overlap are not clear.
Only models with a quantization whose estimated memory fits in 12 GB at an 8,192-token context.
Top 24 of 24 models listed on this site
Values as of Nov 9, 2026
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1Qwen3.8-27B
Qwen 27.3B qwen3.8-27b
Score (95% interval) 1,433 1,429–1,438
32,659 votes
IQ2_S 12.9 GB
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2Qwen3.5-27B
Qwen 26.9B qwen3.5-27b
Score (95% interval) 1,409 1,404–1,413
28,424 votes
IQ2_M 12.8 GB
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3Qwen3.5-35B-A3B
Qwen 34.7B qwen3.5-35b-a3b
Score (95% interval) 1,394 1,390–1,398
30,206 votes
UD-IQ2_M 12.7 GB
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4Qwen3-30B-A3B-Instruct-2507
Qwen 30.5B Qwen3-30B-A3B-Instruct (2507)
Score (95% interval) 1,382 1,377–1,387
23,287 votes
Q2_K_L 12.9 GB
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5gemma-3-27b-it
google 27B Gemma 3 27B IT
Score (95% interval) 1,365 1,362–1,369
46,613 votes
UD-IQ2_M 12.0 GB
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6GLM-4.7-Flash
zai-org 29.9B glm-4.7-flash
Score (95% interval) 1,364 1,359–1,370
11,937 votes
Q2_K_L 12.7 GB
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7Qwen3-32B
Qwen 32.8B qwen3-32b
Score (95% interval) 1,347 1,337–1,356
3,926 votes
UD-IQ2_XXS 12.3 GB
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8gemma-3-12b-it
google 11.8B Gemma 3 12B IT
Score (95% interval) 1,342 1,332–1,351
3,829 votes
UD-Q6_K_XL 12.7 GB
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9Qwen3-30B-A3B
Qwen 30.5B qwen3-30b-a3b
Score (95% interval) 1,326 1,322–1,331
26,137 votes
UD-IQ2_M 12.5 GB
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10gpt-oss-20b
openai 20.9B gpt-oss-20b
Score (95% interval) 1,318 1,311–1,324
10,400 votes
Q5_K_S 12.9 GB
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11gemma-3n-E4B-it
google 6.9B Gemma 3n E4B IT
Score (95% interval) 1,317 1,312–1,323
22,106 votes
UD-Q8_K_XL 11.8 GB
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12gemma-3-4b-it
google 3.9B Gemma 3 4B IT
Score (95% interval) 1,303 1,294–1,313
4,171 votes
BF16 9.19 GB
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13gemma-2-27b-it
google 27.2B Gemma 2 27B IT
Score (95% interval) 1,290 1,286–1,293
75,754 votes
IQ2_M 12.9 GB
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14granite-4.2-8b
ibm-granite 8.8B Granite 4.2 8B
Score (95% interval) 1,290 1,278–1,301
3,196 votes
Q8_0 11.4 GB
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15granite-4.2-3b
ibm-granite 3.7B Granite 4.2 3B
Score (95% interval) 1,289 1,277–1,301
3,185 votes
BF16 8.74 GB
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16Mistral-Small-24B-Instruct-2501
mistralai 23.6B Mistral Small 24B Instruct (2501)
Score (95% interval) 1,274 1,268–1,280
14,681 votes
Q3_K_S 12.5 GB
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17Qwen2.5-Coder-32B-Instruct
Qwen 32.8B qwen2.5-coder-32b-instruct
Score (95% interval) 1,271 1,263–1,279
5,432 votes
IQ2_XXS 12.0 GB
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18gemma-2-9b-it
google 9.2B Gemma 2 9B IT
Score (95% interval) 1,267 1,263–1,271
54,611 votes
Q6_K 11.1 GB
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19phi-4
microsoft 14.7B phi-4
Score (95% interval) 1,256 1,252–1,261
24,126 votes
Q5_K_S 12.6 GB
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20gemma-2-2b-it
google 2.6B Gemma 2 2B IT
Score (95% interval) 1,200 1,196–1,204
46,616 votes
F32 12.2 GB
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21Llama-3.2-3B-Instruct
meta-llama 3.2B Llama 3.2 3B Instruct
Score (95% interval) 1,167 1,159–1,175
7,936 votes
F16 8.17 GB
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22Mistral-7B-Instruct-v0.2
mistralai 7.2B Mistral 7B Instruct v0.2
Score (95% interval) 1,149 1,143–1,156
19,402 votes
Q8_0 9.37 GB
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23Llama-3.2-1B-Instruct
meta-llama 1.2B Llama 3.2 1B Instruct
Score (95% interval) 1,111 1,103–1,119
8,045 votes
F16 3.55 GB
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24gemma-2b-it
lmstudio-ai 2.5B Gemma 2B IT
Score (95% interval) 1,094 1,082–1,105
4,780 votes
Q8_0 3.89 GB
Estimated Memory at 8K: Estimated with a formula. Actual usage depends on your setup and settings.
About this ranking
- Values for open-weight models come from the latest version of LMArena's Hugging Face dataset (text, style control, overall). Updated weekly.
- Values are for the original model before quantization. GGUF quantization (especially small quantizations) can lower performance.
- Values are attached only when the model name in the source matches a model listed on this site (its original Hugging Face repository). Fine-tunes and modified versions do not get them.
- Each source is a separate ranking. We do not mix values from different sources or assign our own scores.
- Small and new models are often not evaluated by the source, so they do not appear here.
Values are from LMArena data (CC BY 4.0), shown unchanged (sorting and filtering by this site).