Qwen2.5-Coder 32B Instruct

Running Qwen2.5-Coder 32B Instruct locally

At Q4_K_M and 4K of context, Qwen2.5-Coder 32B Instruct needs about 21.7 GB — 18.7 GB of weights, 1.00 GB of KV cache and a 2.0 GB activation buffer. The smallest cards in this index that clear that comfortably are 32 GB ones — 4 of them, from the RTX 5090 up — and 26 of the 78 cards here do. These are calculated figures, not measurements: the estimate stops counting a card as comfortable at 88% of its VRAM, which is roughly the room a desktop session needs.

What longer context costs

Going from 4K to 32K adds about 7.00 GB, taking the total to 29.4 GB. Weights do not move with context — only the KV cache does, and it grows linearly, so this is the number to watch when planning for long documents. The model's native window is 128K; holding all of it at Q4_K_M would need about 56 GB.

Which build to download

This index tracks 3 formats for it — GGUF, EXL2, AWQ — across 3 levels. Q4_K_M carries the lowest published perplexity loss at 2.5%. The fastest level listed is EXL2 3.5bpw at about 65 tok/s on an RTX 4090, batch 1 — an estimate, not a run on this site's hardware. GGUF runs on llama.cpp and Ollama across NVIDIA, AMD and Apple silicon; AWQ and GPTQ target vLLM on CUDA and ROCm; EXL2 is ExLlamaV2 — CUDA only, and now archived, so local use rather than serving.

Common questions

How much VRAM does Qwen2.5-Coder 32B Instruct need?

About 21.7 GB at Q4_K_M with 4K of context and batch 1, rising to roughly 29.4 GB at 32K. That figure is weights plus KV cache plus a 10% activation buffer, calculated from the model's architecture rather than measured on a card.

Will Qwen2.5-Coder 32B Instruct run on a 32GB GPU?

Yes — at Q4_K_M and 4K context it needs about 21.7 GB, which leaves 10.3 GB spare on a RTX 5090, or on any of the other 32 GB cards here (4 in all). That is the smallest size in this index that clears it comfortably; 26 of 78 do.

Which quantization of Qwen2.5-Coder 32B Instruct should I use?

Q4_K_M has the lowest published quality loss (2.5%), and Q4_K_M is the level most people run. All 3 levels in the index are Q4_K_M, EXL2 3.5bpw, AWQ INT4.