Qwen 2.5 Coder 32B Instruct vs Qwen3 32B
Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.
Quick verdict
Qwen3 32B is more hardware-efficient — it needs 19.9 GB at Q4_K_M vs 20.6 GB for Qwen 2.5 Coder 32B Instruct, fitting on 51 GPUs natively.
VRAM at each quantization (8k context)
| Quant | Qwen 2.5 Coder 32B Instruct | Qwen3 32B | Diff |
|---|---|---|---|
| FP16 | 75.2 GB | 75.0 GB | +0% |
| Q8 | 38.8 GB | 38.2 GB | +1% |
| Q6_K | 29.7 GB | 29.1 GB | +2% |
| Q5_K_M | 25.2 GB | 24.5 GB | +3% |
| Q4_K_M | 20.6 GB | 19.9 GB | +4% |
| Q3_K_M | 17.0 GB | 16.2 GB | +5% |
| Q2_K | 13.3 GB | 12.5 GB | +6% |
Diff is Qwen 2.5 Coder 32B Instruct relative to Qwen3 32B. Green = lower VRAM (fits more GPUs).
Model specifications
| Spec | Qwen 2.5 Coder 32B Instruct | Qwen3 32B |
|---|---|---|
| Org | Alibaba | Alibaba |
| Parameters | 32.5B | 32.8B |
| Architecture | Dense | Dense |
| Context | 125k tokens | 128k tokens |
| Modalities | text | text |
| License | Apache 2.0 | Apache 2.0 |
| Commercial | Yes | Yes |
| Released | 2024-11-12 | 2025-04-29 |
| GPUs (native) | 51 / 67 | 51 / 67 |
Benchmark scores
Green = higher score (better). — = not yet available.
GPUs that run only Qwen 2.5 Coder 32B Instruct(0)
Every GPU that runs Qwen 2.5 Coder 32B Instruct also runs Qwen3 32B.
GPUs that run only Qwen3 32B(0)
Every GPU that runs Qwen3 32B also runs Qwen 2.5 Coder 32B Instruct.
GPUs that run both natively(51)
- NVIDIA RTX 509032 GB
- NVIDIA RTX 409024 GB
- NVIDIA RTX 408016 GB
- NVIDIA RTX 4060 Ti 16GB16 GB
- NVIDIA RTX 309024 GB
- NVIDIA RTX 3090 Ti24 GB
- NVIDIA H100 80GB80 GB
- NVIDIA A100 80GB80 GB
- NVIDIA A100 40GB40 GB
- NVIDIA L40S48 GB
- NVIDIA RTX A600048 GB
- NVIDIA RTX 6000 Ada48 GB
- +39 more GPUs run both
Which should you use?
Choose Qwen 2.5 Coder 32B Instruct if:
- • You have limited VRAM — it's a smaller model needing 20.6 GB vs 19.9 GB
- • You're running coding tasks
Choose Qwen3 32B if:
- • You want maximum capability and have a 20 GB+ GPU
- • Long context matters — it supports 128k tokens vs 125k
- • You need chain-of-thought reasoning
Frequently asked questions
- Which is better, Qwen 2.5 Coder 32B Instruct or Qwen3 32B?
- Qwen 2.5 Coder 32B Instruct has 32.5B parameters vs 32.8B for Qwen3 32B, so Qwen3 32B is the larger model. Qwen3 32B is more hardware-efficient, needing 19.9 GB at Q4_K_M vs 20.6 GB.
- How much VRAM does Qwen 2.5 Coder 32B Instruct need vs Qwen3 32B?
- At Q4_K_M quantization with 8k context, Qwen 2.5 Coder 32B Instruct needs approximately 20.6 GB of VRAM, while Qwen3 32B needs 19.9 GB. At FP16, Qwen 2.5 Coder 32B Instruct requires 75.2 GB vs 75.0 GB for Qwen3 32B.
- Can you run Qwen 2.5 Coder 32B Instruct on the same GPUs as Qwen3 32B?
- Yes, 51 GPUs can run both natively in VRAM, including NVIDIA RTX 5090, NVIDIA RTX 4090, NVIDIA RTX 4080. However, no GPU can run Qwen 2.5 Coder 32B Instruct without also fitting Qwen3 32B, and no GPU can run Qwen3 32B without also fitting Qwen 2.5 Coder 32B Instruct.
- What is the difference between Qwen 2.5 Coder 32B Instruct and Qwen3 32B?
- Qwen 2.5 Coder 32B Instruct has 32.5B parameters (dense) with a 125k context window. Qwen3 32B has 32.8B parameters (dense) with a 128k context window.
- Which model fits in 24 GB of VRAM, Qwen 2.5 Coder 32B Instruct or Qwen3 32B?
- Both fit in 24 GB of VRAM at Q4_K_M — Qwen 2.5 Coder 32B Instruct needs 20.6 GB and Qwen3 32B needs 19.9 GB.