ModelRefs / DeepSeek R1 vs Qwen 2.5 Coder 32B
DeepSeek R1 vs Qwen 2.5 Coder 32B
DeepSeek R1 vs Qwen 2.5 Coder 32B: side-by-side benchmarks, pricing, context windows, coding ability and deployment. Pick the right model for your stack.
Overview
DeepSeek R1: DeepSeek R1 is DeepSeek's open-source reasoning model, trained with reinforcement learning to produce chain-of-thought reasoning before answering. Released in January 2025 under the MIT license, it matched or exceeded closed reasoning models on several math and coding benchmarks.
Qwen 2.5 Coder 32B: Qwen 2.5 Coder 32B Instruct is Alibaba's code-specialised model, 32.5 billion parameters (31.0 billion excluding embeddings) trained on 5.5 trillion tokens of source code, text-code grounding and synthetic data, and released under Apache 2.0. Qwen builds it for code generation, code reasoning and code repair. The published config sets a 32,768-token context by default; reaching the full 131,072 tokens requires YaRN scaling, which Qwen notes can degrade quality on shorter inputs.
Context window: DeepSeek R1 accepts up to 128,000 tokens, Qwen 2.5 Coder 32B up to 131,072. Confirm the limit for your specific deployment channel before relying on it.
DeepSeek R1 vs Qwen 2.5 Coder 32B at a glance
| Attribute | DeepSeek R1 | Qwen 2.5 Coder 32B |
|---|---|---|
| Provider | DeepSeek | Alibaba |
| Released | 2025-01-20 | 2024-11-12 |
| Context window | 128,000 tokens | 131,072 tokens |
| Input price | $0.55/M tokens | $0.18/M tokens |
| Output price | $2.19/M tokens | $0.18/M tokens |
| Licence | MIT | Apache-2.0 |
| Self-hostable | Yes, open weights | Yes, open weights |
| Modalities | text | text |
Reported on different variants
Both models are measured on these benchmarks, but not on the same variant of them, so the two numbers are not a like-for-like comparison. Each side is shown with the variant it was measured on.
| Benchmark | DeepSeek R1 | Qwen 2.5 Coder 32B | Reported |
|---|---|---|---|
| LiveCodeBench | 65.9 (avg@8) | 31.4 (accuracy) | 2024-11-12 |
A different task set or a different reported metric can move a score by more than the gap between two models. Use these as two separate findings, not as a ranking.
Where they differ most
- Cost Efficiency: DeepSeek R1 75%, Qwen 2.5 Coder 32B 96%. Qwen 2.5 Coder 32B leads on this dimension.
- Coding: DeepSeek R1 66%, Qwen 2.5 Coder 32B 50%. DeepSeek R1 leads on this dimension.
Capability scores are ModelRefs' own derived signals, not vendor claims or benchmark results. Validate against your own workload before relying on them.
Continue your research
Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to DeepSeek R1 vs Qwen 2.5 Coder 32B.
Frequently asked questions
Which is better, DeepSeek R1 or Qwen 2.5 Coder 32B?
DeepSeek R1 and Qwen 2.5 Coder 32B target different workloads — see the benchmark and pricing tables for a side-by-side answer.
Is DeepSeek R1 cheaper than Qwen 2.5 Coder 32B?
Compare $0.00055 vs $0.00018 on this page.