作者： Jakub Rusinowski · 最后更新： 2024年9月18日
Model library → Qwen 2.5 Family → Qwen 2.5 7B Instruct
The most popular Qwen model for everyday use. Outperforms Llama 3.1 8B in coding and math while using slightly less VRAM. The best general-purpose 7B model available.
Qwen 2.5 7B Instruct needs about 5 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.
| Parameters | 7 Billion |
| Context window | 128,000 |
| Architecture | Dense |
| Provider | Alibaba Cloud |
| Licence | Apache 2.0 |
| Specified at | Q4_K_M |
| System RAM | 16 GB |
| Record updated | 2024-09-18 |
Apache-2.0 — commercial use permitted. Commercial use permitted. No usage restrictions beyond attribution.
Modelled on a reference NVIDIA RTX 4090 (24 GB), at 8K context. Speed figures are ESTIMATES from the memory-bandwidth roofline described on the methodology page, not benchmarks we ran — rows marked measured come from published or reader-submitted runs. VRAM here includes the KV cache, so it reads higher than the headline figure above, which does not.
| Quant | Weights | VRAM needed | Est. speed | Fit on 24 GB |
|---|---|---|---|---|
| Q2_K | 2.5 GB | 3.8 GB | ~171 tok/s (est.) | Fits comfortably |
| Q3_K_M | 3.2 GB | 4.5 GB | ~146 tok/s (est.) | Fits comfortably |
| Q4_K_M | 4.6 GB | 5.9 GB | ~135 tok/s (measured) | Fits comfortably |
| Q5_K_M | 5.4 GB | 6.7 GB | ~103 tok/s (est.) | Fits comfortably |
| Q6_K | 6.2 GB | 7.5 GB | ~93 tok/s (est.) | Fits comfortably |
| Q8_0 | 8.1 GB | 9.3 GB | ~76 tok/s (est.) | Fits comfortably |
| F16 | 15.2 GB | 16.5 GB | ~44 tok/s (est.) | Fits comfortably |
Want the memory numbers alone, at every quantization level and your own context length? Use the Qwen 2.5 7B Instruct VRAM calculator.
or compare on Vast.ai from $0.35/hr (typical low · varies)
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The cheapest catalogued GPU that runs Qwen 2.5 7B Instruct is the Intel Arc B570 (10 GB).
Install Ollama, then run:
ollama run qwen2.5:7bWeights on Hugging Face: Qwen/Qwen2.5-7B-Instruct.
Pick a quantization and open it in LM Studio, Ollama, or Jan, or download the raw .gguf file directly. Quant list and sizes resolved from Hugging Face.
| Quant | Size | Download (.gguf) |
|---|---|---|
| Q3_K_M | 3.24 GB (est.) | Qwen2.5-7B-Instruct-Q3_K_M.gguf |
| Q4_K_M | 4.59 GB (est.) | Qwen2.5-7B-Instruct-Q4_K_M.gguf |
| Q5_K_M | 5.39 GB (est.) | Qwen2.5-7B-Instruct-Q5_K_M.gguf |
| Q6_K | 6.23 GB (est.) | Qwen2.5-7B-Instruct-Q6_K.gguf |
| Q8_0 | 8.07 GB (est.) | Qwen2.5-7B-Instruct-Q8_0.gguf |
Download in LM Studio: lms get bartowski/Qwen2.5-7B-Instruct-GGUF
Want this model on your phone? You can run it on your desktop with LM Studio and chat from your iPhone or iPad over an encrypted link — see Run LM Studio Models on Your Phone (LM Link).
Best for: chat, coding, rag, balanced.
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