Alibaba
Qwen 2.5 14B
当前
2.1M下载量342点赞Sep 2024发布日期131K tokens上下文Apache 2.0许可证73 优秀质量
Qwen 2.5 14B (14B parameters) requires approximately 13.3 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 16 GB of VRAM.
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Run
ollama run qwen2.5Quick specs
Parameters14B
Architecturedense
Context131K tokens
Modalitytext
Min RAM5.5 GB
Rec. RAM8.5 GB (Q4_K_M)
LicenseApache 2.0
FamilyQwen
✓ Chat✓ Reasoning
About this model
- •Significantly more knowledge and has greatly improved capabilities in coding and mathematics, thanks to our specialized expert models...
- •Significant improvements in instruction following, generating long texts (over 8K tokens), understanding structured data (e.g,...
- •Long-context Support: up to 128K tokens and can generate up to 8K tokens
- •Multilingual support: for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean,...
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最佳硬件
Qwen 2.5 14B 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 | 5.5 GB | Low | — |
Q3_K_S | 3 | 6.9 GB | Low | — |
NVFP4 | 4 | 7.8 GB | Medium | — |
Q4_K_M | 4 | 8.5 GB | Medium | — |
Q5_K_M | 5 | 10.1 GB | High | — |
Q6_K | 6 | 11.5 GB | High | — |
Q8_0 | 8 | 15.0 GB | Very High | — |
F16 | 16 | 28.7 GB | Maximum | — |
Quality benchmarks
Qwen 2.5 14B benchmark scores
Coding
SWE-bench Verified—
HumanEval+83.5%
Aider Polyglot—
LiveCodeBench42.6%
Reasoning
MMLU-Pro63.7%
GPQA Diamond45.5%
MATH-50080.0%
ARC Challenge—
General
Chatbot Arena—
IFEval81.0%
Source: official · 2024-09-19
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
Weights8.5 GB
KV Cache2.9 GB
Runtime1.2 GB
Headroom0.6 GB
常见问题
FAQ — Qwen 2.5 14B
另请参阅