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 (24.6 GB) at their recommended builds. The choice comes down to benchmarks and architecture.
VRAM at each quantization (8k context)
FP32
Qwen 2.5 Coder 32B Instruct
148.0 GB
DeepSeek R1 Distill Qwen 32B
148.0 GB
BF16
Qwen 2.5 Coder 32B Instruct
75.2 GB
DeepSeek R1 Distill Qwen 32B
75.2 GB
FP16
Qwen 2.5 Coder 32B Instruct
75.2 GB
DeepSeek R1 Distill Qwen 32B
75.2 GB
Q8_0
Qwen 2.5 Coder 32B Instruct
41.1 GB
DeepSeek R1 Distill Qwen 32B
41.1 GB
Q6_K
Qwen 2.5 Coder 32B Instruct
32.3 GB
DeepSeek R1 Distill Qwen 32B
32.3 GB
Q5_K_M
Qwen 2.5 Coder 32B Instruct
28.3 GB
DeepSeek R1 Distill Qwen 32B
28.3 GB
Q4_K_M
Qwen 2.5 Coder 32B Instruct
24.6 GB
DeepSeek R1 Distill Qwen 32B
24.6 GB
Q3_K_M
Qwen 2.5 Coder 32B Instruct
19.9 GB
DeepSeek R1 Distill Qwen 32B
19.9 GB
Q2_K
Qwen 2.5 Coder 32B Instruct
16.3 GB
DeepSeek R1 Distill Qwen 32B
16.3 GB
NVFP4
Qwen 2.5 Coder 32B Instruct
20.6 GB
DeepSeek R1 Distill Qwen 32B
20.6 GB
| Quant | Qwen 2.5 Coder 32B Instruct | DeepSeek R1 Distill Qwen 32B | Diff |
|---|---|---|---|
| FP32 | 148.0 GB | 148.0 GB | +0% |
| BF16 | 75.2 GB | 75.2 GB | +0% |
| FP16 | 75.2 GB | 75.2 GB | +0% |
| Q8_0 | 41.1 GB | 41.1 GB | +0% |
| Q6_K | 32.3 GB | 32.3 GB | +0% |
| Q5_K_M | 28.3 GB | 28.3 GB | +0% |
| Q4_K_M | 24.6 GB | 24.6 GB | +0% |
| Q3_K_M | 19.9 GB | 19.9 GB | +0% |
| Q2_K | 16.3 GB | 16.3 GB | +0% |
| NVFP4 | 20.6 GB | 20.6 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 | 128k tokens | 125k tokens |
| Modalities | text | text |
| License | Apache 2.0 | MIT |
| Commercial | Yes | Yes |
| Released | 2024-11-12 | 2025-01-20 |
| GPUs (native) | 70 / 119 | 70 / 119 |
Benchmark scores
| Benchmark | Qwen 2.5 Coder 32B Instruct | DeepSeek R1 Distill Qwen 32B |
|---|---|---|
| MMLU-Pro | 62.3 | 65.0 |
| GPQA Diamond | 41.8 | 62.1 |
| IFEval | 79.9 | N/A |
| MATH | 76.4 | 94.3 |
| LiveCodeBench | 31.4 | N/A |
Green = higher score (better). N/A = not yet available. ~ = inherited from a base model, not independently reported for that release itself.
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(70)
- NVIDIA RTX 509032 GB
- NVIDIA RTX 409024 GB
- NVIDIA RTX 309024 GB
- NVIDIA RTX 3090 Ti24 GB
- NVIDIA B300 288GB288 GB
- NVIDIA B200 180GB180 GB
- NVIDIA H200 141GB141 GB
- NVIDIA H100 80GB80 GB
- NVIDIA A100 80GB80 GB
- NVIDIA A100 40GB40 GB
- NVIDIA L40S48 GB
- NVIDIA RTX A600048 GB
- +58 more GPUs run both
Which should you use?
Choose Qwen 2.5 Coder 32B Instruct if:
- • Long context matters: it supports 128k tokens vs 125k
- • You're running coding tasks
Choose DeepSeek R1 Distill Qwen 32B if:
- • Benchmark quality matters: scores 65.0 vs 62.3 on MMLU-Pro
- • You need chain-of-thought reasoning
- • It's the newer release (2025-01-20 vs 2024-11-12); check the benchmark table above for what actually improved
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 62.3).
- How much VRAM does Qwen 2.5 Coder 32B Instruct need vs DeepSeek R1 Distill Qwen 32B?
- At 8k context, Qwen 2.5 Coder 32B Instruct needs approximately 24.6 GB of VRAM at its Q4_K_M build, while DeepSeek R1 Distill Qwen 32B needs 24.6 GB at its Q4_K_M build. At the largest build each ships, Qwen 2.5 Coder 32B Instruct requires 75.2 GB (FP16) vs 75.2 GB (FP16) 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, 70 GPUs can run both natively in VRAM, including NVIDIA RTX 5090, NVIDIA RTX 4090, NVIDIA RTX 3090. 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 128k 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?
- Neither fits in 24 GB: Qwen 2.5 Coder 32B Instruct needs 24.6 GB at Q4_K_M and DeepSeek R1 Distill Qwen 32B needs 24.6 GB at Q4_K_M. Both require at least a 32 GB GPU.