Mistral
Mistral Small 24B
旧版
66.0K下载量958点赞Jan 2025发布日期33K tokens上下文Mistral Research许可证75 优秀质量
Mistral Small 24B (24B parameters) requires approximately 18.9 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 22 GB of VRAM.
快速开始
— 复制粘贴即可本地运行Copy-paste commands to run Mistral Small 24B on your machine.
Run
ollama run mistral-smallQuick specs
Parameters24B
Architecturedense
Context33K tokens
Modalitytext
Min RAM9.4 GB
Rec. RAM14.6 GB (Q4_K_M)
LicenseMistral Research
FamilyMistral Small
✓ Code✓ Chat
About this model
- •Multilingual:: Supports dozens of languages, including English, French, German, Spanish, Italian, Chinese, Japanese, Korean, Portuguese, Dutch,...
- •Agent-Centric:: Offers best-in-class agentic capabilities with native function calling and JSON outputting
- •Advanced Reasoning:: State-of-the-art conversational and reasoning capabilities
- •Apache 2.0 License:: Open license allowing usage and modification for both commercial and non-commercial purposes
- •Context Window:: A 32k context window
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最佳硬件
Mistral Small 24B 的最佳选择
运行此模型
量化选项
各量化级别的 VRAM 估算
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 9.4 GB | Low | — |
Q3_K_S | 3 | 11.8 GB | Low | — |
NVFP4 | 4 | 13.4 GB | Medium | — |
Q4_K_M | 4 | 14.6 GB | Medium | — |
Q5_K_M | 5 | 17.3 GB | High | — |
Q6_K | 6 | 19.7 GB | High | — |
Q8_0 | 8 | 25.7 GB | Very High | — |
F16 | 16 | 49.2 GB | Maximum | — |
Quality benchmarks
Mistral Small 24B benchmark scores
Coding
SWE-bench Verified—
HumanEval+84.8%
Aider Polyglot—
LiveCodeBench—
Reasoning
MMLU-Pro66.3%
GPQA Diamond—
MATH-50070.6%
ARC Challenge—
General
Chatbot Arena—
IFEval82.9%
Source: official · 2025-01-28
硬件兼容性
全部硬件的适配估算
Computing compatibility...
内存详细分析
Reference: RTX 2060 6GB
Weights14.6 GB
KV Cache2.4 GB
Runtime1.2 GB
Headroom0.6 GB
常见问题
FAQ — Mistral Small 24B
另请参阅