Cheapest Cloud GPU to Host Qwen 2.5 Coder 32B Instruct
Qwen 2.5 Coder 32B is the leading open-source code generation model. At FP16, the 65 GB footprint fits on a single A100 80GB. At FP8 (35 GB), it runs on L40S or RTX 6000 with room for 32k context. The model excels at code completion, debugging, and multi-language programming tasks.
VRAM Sizing Matrix
Memory consumption at different quantization levels for Qwen 2.5 Coder 32B Instruct. Includes model weights only — KV-cache adds 2-32 GB depending on context length and batch size.
| Precision | VRAM Required | Fits On | Quality Loss |
|---|---|---|---|
| FP16 / BF16 | 65 GB | Single GPU with headroom | None (full precision) |
| FP8 | 35 GB | Single GPU | <1% perplexity delta |
| INT4 / AWQ | 20 GB | Single consumer GPU | 1-3% quality degradation |
Hardware Bottleneck Advice
KV-cache expansion, tensor parallelism constraints, and production considerations for Qwen 2.5 Coder 32B Instruct.
KV-Cache & Context Scaling
32.5B dense model. At FP16 (65 GB), fits on A100 80GB with 15 GB for KV-cache — supports 16k context at batch=1. At FP8 (35 GB), fits on L40S or RTX 6000 with ample KV-cache headroom.
Tensor Parallelism
TP=1 on A100/H100. The 32B parameter count fits on a single 80GB GPU at FP16. At INT4 (20 GB), even RTX 4090 handles it.
Live Cloud Pricing for A100
Filtered to A100-class hardware — the recommended GPU for hosting Qwen 2.5 Coder 32B Instruct.
| Provider | GPU & VRAM | Interconnect | Spot Rate | On-Demand | Monthly | Status | Action | |
|---|---|---|---|---|---|---|---|---|
Dedicated | N/A | $1.59 / hr | $3.98 / hr | $973 / mo | Instant |
Production Runbook
Ready-to-deploy vLLM / SGLang launch command for Qwen 2.5 Coder 32B Instruct.
vllm serve Qwen/Qwen2.5-Coder-32B-Instruct --tensor-parallel-size 1 --max-model-len 32768 --dtype autoRelated hosting guides