Which model for PC 64 Go RAM (CPU)?
51 GB usable for the model (80% of RAM, CPU execution). 90 open-weight models fit in memory.
The margin goes to context: count ~1 GB per 8k tokens for a 7B model. A small margin means a short context.
| Model | Elo | Quantization | RAM required | Margin | Memory headroom | Run |
|---|---|---|---|---|---|---|
| Gemma 4 31BGoogle · 31B | 1452 | Q8_0 | 39 Go | +12 Go | slow (CPU) | Hugging Face ↗ |
| Gemma 4 26B-A4BGoogle · 26B | 1438 | Q8_0 | 33 Go | +18 Go | slow (CPU) | Hugging Face ↗ |
| Qwen3.8 27BAlibaba · 27B | 1438 | Q8_0 | 34 Go | +17 Go | slow (CPU) | Hugging Face ↗ |
| Gemma 3 27BGoogle · 27B | 1365 | Q4_K_MQ8_0 also fits · 34 Go | 19 Go | +32 Go | slow (CPU) | ollama run gemma3:27b |
| Mistral Small 3.2Mistral AI · 24B | 1356 | Q4_K_MQ8_0 also fits · 30 Go | 17 Go | +34 Go | slow (CPU) | ollama run mistral-small3.2 |
| Qwen3 32BAlibaba · 32.8B | 1347 | Q4_K_MQ8_0 also fits · 41 Go | 23 Go | +28 Go | slow (CPU) | ollama run qwen3:32b |
| Gemma 3 12BGoogle · 12B | 1342 | Q4_K_MFP16 also fits · 28 Go | 9 Go | +42 Go | slow (CPU) | ollama run gemma3:12b |
| QwQ 32BAlibaba · 32.8B | 1336 | Q4_K_MQ8_0 also fits · 41 Go | 23 Go | +28 Go | slow (CPU) | ollama run qwq |
| Gemma 3n E4BGoogle · 4B | 1318 | Q4_K_MFP16 also fits · 11 Go | 5 Go | +46 Go | slow (CPU) | ollama run gemma3n:e4b |
| Llama 3.3 70BMeta · 70.6B | 1318 | Q4_K_M | 46 Go | +5 Go | slow (CPU) | ollama run llama3.3:70b |
| gpt-oss-20bOpenAI · 21B | 1317 | MXFP4 | 17 Go | +34 Go | slow (CPU) | ollama run gpt-oss:20b |
| Nemotron 3 Nano 30B-A3BNVIDIA · 30B | 1314 | Q8_0 | 37 Go | +14 Go | slow (CPU) | Hugging Face ↗ |
| Granite 4.1 8BIBM · 8B | 1304 | FP16 | 20 Go | +31 Go | slow (CPU) | Hugging Face ↗ |
| Gemma 3 4BGoogle · 4B | 1303 | Q4_K_MFP16 also fits · 11 Go | 5 Go | +46 Go | slow (CPU) | ollama run gemma3:4b |
| Qwen2.5 72BAlibaba · 72.7B | 1303 | Q4_K_M | 48 Go | +3 Go | slow (CPU) | ollama run qwen2.5:72b |
| Llama 3.1 Nemotron 70BNVIDIA · 70.6B | 1299 | Q4_K_M | 46 Go | +5 Go | slow (CPU) | ollama run nemotron:70b |
| Qwen2.5-Coder 32BAlibaba · 32.8B | 1271 | Q4_K_MQ8_0 also fits · 41 Go | 23 Go | +28 Go | slow (CPU) | ollama run qwen2.5-coder:32b |
| Aya Expanse 32BCohere · 32.3B | 1267 | Q4_K_MQ8_0 also fits · 40 Go | 22 Go | +29 Go | slow (CPU) | ollama run aya-expanse:32b |
| Phi-4Microsoft · 14.7B | 1256 | Q4_K_MFP16 also fits · 34 Go | 11 Go | +40 Go | slow (CPU) | ollama run phi4 |
| Phi-4 ReasoningMicrosoft · 14.7B | 1256 | Q4_K_MFP16 also fits · 34 Go | 11 Go | +40 Go | slow (CPU) | ollama run phi4-reasoning |
| OLMo 2 32BAllen AI · 32B | 1252 | Q8_0 | 40 Go | +11 Go | slow (CPU) | Hugging Face ↗ |
| CodestralMistral AI · 22.2B | 1240 | Q4_K_MFP16 also fits · 51 Go | 16 Go | +35 Go | slow (CPU) | ollama run codestral |
| Ministral 8BMistral AI · 8.02B | 1238 | FP16 | 20 Go | +31 Go | slow (CPU) | Hugging Face ↗ |
| Llama 3.1 8BMeta · 8.03B | 1211 | Q4_K_MFP16 also fits · 20 Go | 7 Go | +44 Go | slow (CPU) | ollama run llama3.1:8b |
| Mixtral 8x7BMistral AI · 46.7B | 1197 | Q4_K_M | 31 Go | +20 Go | slow (CPU) | ollama run mixtral:8x7b |
| Llama 3.2 3BMeta · 3.21B | 1167 | Q4_K_MFP16 also fits · 9 Go | 4 Go | +47 Go | slow (CPU) | ollama run llama3.2:3b |
| Llama 3.2 1BMeta · 1.24B | 1111 | Q4_K_MFP16 also fits · 5 Go | 3 Go | +48 Go | slow (CPU) | ollama run llama3.2:1b |
| Mistral 7BMistral AI · 7.25B | 1110 | Q4_K_MFP16 also fits · 18 Go | 7 Go | +44 Go | slow (CPU) | ollama run mistral:7b |
Not yet ranked by the Arena
No Arena Elo linked: recent release, model absent from the Arena, or a match we have not made yet.
| Model | Elo | Quantization | RAM required | Margin | Memory headroom | Run |
|---|---|---|---|---|---|---|
| Qwen3 0.6BAlibaba · 0.6B | — | Q4_K_MFP16 also fits · 3 Go | 2 Go | +49 Go | slow (CPU) | ollama run qwen3:0.6b |
| Gemma 3 1BGoogle · 1B | — | Q4_K_MFP16 also fits · 4 Go | 3 Go | +48 Go | slow (CPU) | ollama run gemma3:1b |
| Phi-4 MiniMicrosoft · 3.8B | — | Q4_K_MFP16 also fits · 10 Go | 4 Go | +47 Go | slow (CPU) | ollama run phi4-mini |
| Qwen3 4BAlibaba · 4.02B | — | Q4_K_MFP16 also fits · 11 Go | 5 Go | +46 Go | slow (CPU) | ollama run qwen3:4b |
| Gemma 4 E2BGoogle · 2B | — | FP16 | 6 Go | +45 Go | slow (CPU) | Hugging Face ↗ |
| CodeGemma 7BGoogle · 8.5B | — | Q4_K_MFP16 also fits · 21 Go | 7 Go | +44 Go | slow (CPU) | ollama run codegemma |
| Command R7BCohere · 8B | — | Q4_K_MFP16 also fits · 20 Go | 7 Go | +44 Go | slow (CPU) | ollama run command-r7b |
| DeepSeek-R1 Distill 8BDeepSeek · 8.03B | — | Q4_K_MFP16 also fits · 20 Go | 7 Go | +44 Go | slow (CPU) | ollama run deepseek-r1:8b |
| Granite 3.3 8BIBM · 8.1B | — | Q4_K_MFP16 also fits · 20 Go | 7 Go | +44 Go | slow (CPU) | ollama run granite3.3:8b |
| Hermes 3 8BNous Research · 8.03B | — | Q4_K_MFP16 also fits · 20 Go | 7 Go | +44 Go | slow (CPU) | ollama run hermes3:8b |
| MiniCPM5-2BOpenBMB · 2.5B | — | FP16 | 7 Go | +44 Go | slow (CPU) | Hugging Face ↗ |
| Qwen3 8BAlibaba · 8.2B | — | Q4_K_MFP16 also fits · 20 Go | 7 Go | +44 Go | slow (CPU) | ollama run qwen3:8b |
| Falcon 3 10BTII · 10.3B | — | Q4_K_MFP16 also fits · 25 Go | 8 Go | +43 Go | slow (CPU) | ollama run falcon3:10b |
| Granite 4.1 3BIBM · 3B | — | FP16 | 9 Go | +42 Go | slow (CPU) | Hugging Face ↗ |
| Ministral 3 3BMistral AI · 3B | — | FP16 | 9 Go | +42 Go | slow (CPU) | Hugging Face ↗ |
| SmolLM3 3BHugging Face · 3.1B | — | FP16 | 9 Go | +42 Go | slow (CPU) | Hugging Face ↗ |
| Mistral Nemo 12BMistral AI · 12.2B | — | Q4_K_MFP16 also fits · 29 Go | 10 Go | +41 Go | slow (CPU) | ollama run mistral-nemo |
| Gemma 4 E4BGoogle · 4B | — | FP16 | 11 Go | +40 Go | slow (CPU) | Hugging Face ↗ |
| Qwen3 14BAlibaba · 14.8B | — | Q4_K_MFP16 also fits · 35 Go | 11 Go | +40 Go | slow (CPU) | ollama run qwen3:14b |
| DeepSeek-Coder-V2 LiteDeepSeek · 15.7B | — | Q4_K_MFP16 also fits · 37 Go | 12 Go | +39 Go | slow (CPU) | ollama run deepseek-coder-v2:16b |
| StarCoder 2BigCode · 16B | — | Q4_K_MFP16 also fits · 37 Go | 12 Go | +39 Go | slow (CPU) | ollama run starcoder2:15b |
| Devstral SmallMistral AI · 24B | — | Q4_K_MQ8_0 also fits · 30 Go | 17 Go | +34 Go | slow (CPU) | ollama run devstral |
| Lucie 7BOpenLLM France · 6.7B | — | FP16 | 17 Go | +34 Go | slow (CPU) | Hugging Face ↗ |
| Magistral SmallMistral AI · 24B | — | Q4_K_MQ8_0 also fits · 30 Go | 17 Go | +34 Go | slow (CPU) | ollama run magistral |
| OLMo 3 7BAllen AI · 7B | — | FP16 | 17 Go | +34 Go | slow (CPU) | Hugging Face ↗ |
| Apertus 8BSwiss AI · 8B | — | FP16 | 20 Go | +31 Go | slow (CPU) | Hugging Face ↗ |
| Ministral 3 8BMistral AI · 8B | — | FP16 | 20 Go | +31 Go | slow (CPU) | Hugging Face ↗ |
| InternLM3 8BShanghai AI Lab · 8.8B | — | FP16 | 21 Go | +30 Go | slow (CPU) | Hugging Face ↗ |
| EuroLLM 9BUTTER Project · 9.15B | — | FP16 | 22 Go | +29 Go | slow (CPU) | Hugging Face ↗ |
| DeepSeek-R1 Distill 32BDeepSeek · 32.8B | — | Q4_K_MQ8_0 also fits · 41 Go | 23 Go | +28 Go | slow (CPU) | ollama run deepseek-r1:32b |
| Gemma 4 12BGoogle · 12B | — | FP16 | 28 Go | +23 Go | slow (CPU) | Hugging Face ↗ |
| Ministral 3 14BMistral AI · 14B | — | FP16 | 33 Go | +18 Go | slow (CPU) | Hugging Face ↗ |
| Qwen3.6 27BAlibaba · 27B | — | Q8_0 | 34 Go | +17 Go | slow (CPU) | Hugging Face ↗ |
| Qwen3.6 35B-A3BAlibaba · 35B | — | Q8_0 | 43 Go | +8 Go | slow (CPU) | Hugging Face ↗ |
Image, video, audio and 3D
These models do not generate text, so the text Arena does not rank them. Indicative order, not a quality ranking.
| Model | Elo | Quantization | RAM required | Margin | Memory headroom | Run |
|---|---|---|---|---|---|---|
| Kokoro-82MHexgrad · 0.08B | — | FP16 | 2 Go | +49 Go | slow (CPU) | Hugging Face ↗ |
| ChatterboxResemble AI · 0.5B | — | FP16 | 3 Go | +48 Go | slow (CPU) | Hugging Face ↗ |
| Parakeet TDT 0.6B v3NVIDIA · 0.6B | — | FP16 | 3 Go | +48 Go | slow (CPU) | Hugging Face ↗ |
| TripoSRStability AI · 0.5B | — | FP16 | 3 Go | +48 Go | slow (CPU) | Hugging Face ↗ |
| Stable Fast 3DStability AI · 1B | — | FP16 | 4 Go | +47 Go | slow (CPU) | Hugging Face ↗ |
| TRELLISMicrosoft · 1.2B | — | FP16 | 5 Go | +46 Go | slow (CPU) | Hugging Face ↗ |
| Whisper large-v3OpenAI · 1.55B | — | FP16 | 5 Go | +46 Go | slow (CPU) | Hugging Face ↗ |
| Dia 1.6BNari Labs · 1.6B | — | FP16 | 6 Go | +45 Go | slow (CPU) | Hugging Face ↗ |
| Hunyuan3D 2.1Tencent · 3B | — | FP16 | 9 Go | +42 Go | slow (CPU) | Hugging Face ↗ |
| Orpheus 3BCanopy Labs · 3B | — | FP16 | 9 Go | +42 Go | slow (CPU) | Hugging Face ↗ |
| Voxtral Mini 3BMistral AI · 3B | — | FP16 | 9 Go | +42 Go | slow (CPU) | Hugging Face ↗ |
| YuE2-3Bm-a-p (Multimodal Art Projection) · 3B | — | FP16 | 9 Go | +42 Go | slow (CPU) | Hugging Face ↗ |
| FLUX.2 [klein] 4BBlack Forest Labs · 4B | — | FP16 | 11 Go | +40 Go | slow (CPU) | Hugging Face ↗ |
| TRELLIS.2Microsoft · 4B | — | FP16 | 11 Go | +40 Go | slow (CPU) | Hugging Face ↗ |
| CogVideoX 5BZhipu AI · 5B | — | FP16 | 13 Go | +38 Go | slow (CPU) | Hugging Face ↗ |
| Wan 2.2 5BAlibaba · 5B | — | FP16 | 13 Go | +38 Go | slow (CPU) | Hugging Face ↗ |
| Ming-Image 0.1 DesignAnt Group · 6B | — | FP16 | 15 Go | +36 Go | slow (CPU) | Hugging Face ↗ |
| Z-Image TurboAlibaba · 6B | — | FP16 | 15 Go | +36 Go | slow (CPU) | Hugging Face ↗ |
| HunyuanVideo 1.5Tencent · 8.3B | — | FP16 | 20 Go | +31 Go | slow (CPU) | Hugging Face ↗ |
| GLM-ImageZhipu AI · 9B | — | FP16 | 22 Go | +29 Go | slow (CPU) | Hugging Face ↗ |
| Mochi 1Genmo · 10B | — | FP16 | 24 Go | +27 Go | slow (CPU) | Hugging Face ↗ |
| FLUX.1 [dev]Black Forest Labs · 12B | — | FP16 | 28 Go | +23 Go | slow (CPU) | Hugging Face ↗ |
| Voxtral Small 24BMistral AI · 24B | — | Q8_0 | 30 Go | +21 Go | slow (CPU) | Hugging Face ↗ |
| Wan 2.2 A14BAlibaba · 27B | — | Q8_0 | 34 Go | +17 Go | slow (CPU) | Hugging Face ↗ |
| HiDream-I1HiDream · 17B | — | FP16 | 39 Go | +12 Go | slow (CPU) | Hugging Face ↗ |
| FLUX.2 [dev]Black Forest Labs · 32B | — | Q8_0 | 40 Go | +11 Go | slow (CPU) | Hugging Face ↗ |
| Qwen-Image 2512Alibaba · 20B | — | FP16 | 46 Go | +5 Go | slow (CPU) | Hugging Face ↗ |
| LTX-2.3Lightricks · 22B | — | FP16 | 50 Go | +1 Go | slow (CPU) | Hugging Face ↗ |
An “ollama run” command without a suffix pulls the Q4_K_M build from the Ollama library: the row then shows that quantization and its memory, and flags whether FP16 or Q8_0 would also fit. Exception: a model published in a native format (MXFP4 for gpt-oss, FP8 for DeepSeek V4.1) exists in one build only, which is what the command loads. via Hugging Face or an explicit Ollama tag.
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