Qwen 2.5 Coder 32B Instruct vs DeepSeek R1 Distill Qwen 32B
Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.
Quick verdict
Both models need similar VRAM at Q4_K_M (20.6 GB). The choice comes down to benchmarks and architecture.
VRAM at each quantization (8k context)
| Quant | Qwen 2.5 Coder 32B Instruct | DeepSeek R1 Distill Qwen 32B | Diff |
|---|---|---|---|
| FP16 | 75.2 GB | 75.2 GB | +0% |
| Q8 | 38.8 GB | 38.8 GB | +0% |
| Q6_K | 29.7 GB | 29.7 GB | +0% |
| Q5_K_M | 25.2 GB | 25.2 GB | +0% |
| Q4_K_M | 20.6 GB | 20.6 GB | +0% |
| Q3_K_M | 17.0 GB | 17.0 GB | +0% |
| Q2_K | 13.3 GB | 13.3 GB | +0% |
Diff is Qwen 2.5 Coder 32B Instruct relative to DeepSeek R1 Distill Qwen 32B. Green = lower VRAM (fits more GPUs).
Model specifications
| Spec | Qwen 2.5 Coder 32B Instruct | DeepSeek R1 Distill Qwen 32B |
|---|---|---|
| Org | Alibaba | DeepSeek |
| Parameters | 32.5B | 32.5B |
| Architecture | Dense | Dense |
| Context | 125k tokens | 125k tokens |
| Modalities | text | text |
| License | Apache 2.0 | MIT |
| Commercial | Yes | Yes |
| Released | 2024-11-12 | 2025-01-20 |
| GPUs (native) | 51 / 67 | 51 / 67 |
Benchmark scores
| Benchmark | Qwen 2.5 Coder 32B Instruct | DeepSeek R1 Distill Qwen 32B |
|---|---|---|
| MMLU-Pro | 50.4 | 65.0 |
| HumanEval | 92.7 | 87.2 |
| MATH | 62.0 | 94.3 |
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 DeepSeek R1 Distill Qwen 32B.
GPUs that run only DeepSeek R1 Distill Qwen 32B(0)
Every GPU that runs DeepSeek R1 Distill Qwen 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're running coding tasks
Choose DeepSeek R1 Distill Qwen 32B if:
- • Benchmark quality matters — scores 65.0 vs 50.4 on MMLU-Pro
- • You need chain-of-thought reasoning
Frequently asked questions
- Which is better, Qwen 2.5 Coder 32B Instruct or DeepSeek R1 Distill Qwen 32B?
- On MMLU-Pro, DeepSeek R1 Distill Qwen 32B scores higher (65.0 vs 50.4).
- How much VRAM does Qwen 2.5 Coder 32B Instruct need vs DeepSeek R1 Distill Qwen 32B?
- At Q4_K_M quantization with 8k context, Qwen 2.5 Coder 32B Instruct needs approximately 20.6 GB of VRAM, while DeepSeek R1 Distill Qwen 32B needs 20.6 GB. At FP16, Qwen 2.5 Coder 32B Instruct requires 75.2 GB vs 75.2 GB for DeepSeek R1 Distill Qwen 32B.
- Can you run Qwen 2.5 Coder 32B Instruct on the same GPUs as DeepSeek R1 Distill Qwen 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 DeepSeek R1 Distill Qwen 32B, and no GPU can run DeepSeek R1 Distill Qwen 32B without also fitting Qwen 2.5 Coder 32B Instruct.
- What is the difference between Qwen 2.5 Coder 32B Instruct and DeepSeek R1 Distill Qwen 32B?
- Qwen 2.5 Coder 32B Instruct has 32.5B parameters (dense) with a 125k context window. DeepSeek R1 Distill Qwen 32B has 32.5B parameters (dense) with a 125k context window. Licensing differs: Qwen 2.5 Coder 32B Instruct is Apache 2.0 while DeepSeek R1 Distill Qwen 32B is MIT.
- Which model fits in 24 GB of VRAM, Qwen 2.5 Coder 32B Instruct or DeepSeek R1 Distill Qwen 32B?
- Both fit in 24 GB of VRAM at Q4_K_M — Qwen 2.5 Coder 32B Instruct needs 20.6 GB and DeepSeek R1 Distill Qwen 32B needs 20.6 GB.