Mistral
Mistral Small 4 119B
最先端52.6Kダウンロード380いいねJan 2026公開日256K トークンコンテキストMistral Research Licenseライセンス94 卓越品質
Mistral Small 4 119B (119B parameters) requires approximately 79.5 GB of VRAM with Q4_K_M quantization. As a Mixture of Experts model with 6.5B active parameters, it uses less memory than its total parameter count suggests. For the best balance of quality and speed, we recommend hardware with at least 92 GB of VRAM.
はじめに
— コピー&ペーストでローカル実行Copy-paste commands to run Mistral Small 4 119B on your machine.
Run
lms load Mistral-Small-4-119B-2603 && lms server startQuick specs
Parameters119B (6.5B active)
Architecturemoe (MoE)
Context256K tokens
Modalitytext+vision
Min RAM46.4 GB
Rec. RAM72.6 GB (Q4_K_M)
LicenseMistral Research License
FamilyMistral Small
✓ Vision✓ Code✓ Chat✓ Reasoning
About this model
- •MoE: 128 experts, 4 active
- •119B parameters: , with 6.5B activated per token
- •256k context length:
- •Multimodal input: Accepts both text and image input, with text output
- •Instruct and Reasoning functionalities: with function calls (reasoning effort configurable per request)
関連モデル
おすすめ
最適なハードウェア
Mistral Small 4 119Bのおすすめ
このモデルを実行
量子化オプション
量子化レベル別VRAM推定値
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 46.4 GB | Low | — |
Q3_K_S | 3 | 58.3 GB | Low | — |
NVFP4 | 4 | 66.6 GB | Medium | — |
Q4_K_M | 4 | 72.6 GB | Medium | — |
Q5_K_M | 5 | 85.7 GB | High | — |
Q6_K | 6 | 97.6 GB | High | — |
Q8_0 | 8 | 127.3 GB | Very High | — |
F16 | 16 | 244.0 GB | Maximum | — |
Quality benchmarks
Mistral Small 4 119B benchmark scores
Coding
SWE-bench Verified—
HumanEval+—
Aider Polyglot—
LiveCodeBench63.6%
Reasoning
MMLU-Pro78.0%
GPQA Diamond71.2%
MATH-500—
ARC Challenge—
Source: official · 2026-03-16
ハードウェア互換性
全ハードウェアの適合度推定
Computing compatibility...
メモリ内訳
Reference: RTX 2060 6GB
Weights72.6 GB
KV Cache5.4 GB
Runtime0.9 GB
Headroom0.6 GB
よくある質問
FAQ — Mistral Small 4 119B
関連項目