👁 Alibaba
Alibaba
Qwen 2.5 Coder 14B
Current
4.5MDownloads167LikesNov 2024Released131K tokensContextApache 2.0License36 BasicQuality
Qwen 2.5 Coder 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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— copy & paste to run locallyCopy-paste commands to run Qwen 2.5 Coder 14B on your machine.
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ollama run qwen2.5-coder:14bQuick specs
Parameters14B
Architecturedense
Context131K tokens
Modalitytext
Min RAM5.5 GB
Rec. RAM8.5 GB (Q4_K_M)
LicenseApache 2.0
FamilyQwen
✓ Code
About this model
- •Significantly improvements in code generation, code reasoning and code fixing. Base on the strong Qwen2.5, we scale up the training...
- •A more comprehensive foundation for real-world applications such as Code Agents. Not only enhancing coding capabilities but also maintaining...
- •Long-context Support: up to 128K tokens
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Quantization options
VRAM estimates by quant level
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 Coder 14B benchmark scores
Coding
SWE-bench Verified27.0%
HumanEval+83.5%
Aider Polyglot—
LiveCodeBench31.5%
Reasoning
MMLU-Pro32.7%
GPQA Diamond7.3%
MATH-50032.5%
ARC Challenge—
General
Chatbot Arena—
IFEval69.1%
Source: official · 2024-11-12
Hardware compatibility
Fit estimates across all hardware
Computing compatibility...
Memory breakdown
Reference: RTX 2060 6GB
Weights8.5 GB
KV Cache2.9 GB
Runtime1.2 GB
Headroom0.6 GB
Frequently asked questions
FAQ — Qwen 2.5 Coder 14B
See also