Mistral
Magistral Small 2507
旧版
1.7K下载量104点赞Jul 2025发布日期131K tokens上下文Apache 2.0许可证96 卓越质量
Magistral Small 2507 (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 Magistral Small 2507 on your machine.
Run
ollama run magistralQuick specs
Parameters24B
Architecturedense
Context131K tokens
Modalitytext
Min RAM9.4 GB
Rec. RAM14.6 GB (Q4_K_M)
LicenseApache 2.0
FamilyMagistral
✓ Chat✓ Reasoning
About this model
- •Reasoning:: Capable of long chains of reasoning traces before providing an answer
- •Multilingual:: Supports dozens of languages, including English, French, German, Greek, Hindi, Indonesian, Italian, Japanese, Korean, Malay,...
- •Apache 2.0 License:: Open license allowing usage and modification for both commercial and non-commercial purposes
- •Context Window:: A 128k context window, but performance might degrade past 40k. Hence we recommend setting the maximum model length to 40k
相关模型
快速推荐
最佳硬件
Magistral Small 2507 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
Magistral Small 2507 benchmark scores
Reasoning
MMLU-Pro—
GPQA Diamond68.2%
MATH-50095.9%
ARC Challenge—
General
Chatbot Arena—
IFEval87.4%
Source: official · 2025-07-01
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 — Magistral Small 2507
另请参阅