01What it can do
- HumanEval 89.6
- LiveCodeBench 37.1
- Apache 2.0
- —Worse at general chat
05Install
Install Ollama for your OS. Check the model and its quantization before downloading. Start with 4096 tokens of context, then check placement with ollama ps. A command below is not proof that a test was run on your machine.
02Required memory
Approximate GPU VRAM required to run this model, including 4k tokens of context overhead. For a longer context, add ~1 GB per 8k-token increment.
What hardware do you need for Qwen 2.5 Coder 14B Instruct?
To run Qwen 2.5 Coder 14B Instruct locally with Q4 quantization, you need about 9 GB of VRAM. An option to compare: RTX 5070 12GB (ASUS Prime OC) — leave some headroom for the system and context; check engine compatibility with the GPU.
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On the go: Qwen 2.5 Coder 14B Instruct also runs on a RTX laptop PC (16 GB of VRAM) →
03Expected speed
Tokens generated per second in Q4_K_M, 4k context. Beyond 20 t/s, reading is comfortable. Below 10 t/s, that's just for testing.
04Public benchmarks
Scores reproduced from model cards or MMLU-Pro / community sources. Unit: % correct answers.