ModelRefs / DeepSeek R1 vs QwQ 32B
DeepSeek R1 vs QwQ 32B
DeepSeek R1 vs QwQ 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.
QwQ 32B: QwQ 32B is the reasoning model of Alibaba's Qwen series, a 32.5-billion-parameter causal language model (31.0 billion excluding embeddings) with 64 layers and grouped-query attention using 40 query and 8 key-value heads. It is built to work through a problem before answering rather than responding directly. The full context length is 131,072 tokens, though Qwen notes that prompts beyond 8,192 tokens require YaRN to be enabled. Released under Apache 2.0.
Context window: DeepSeek R1 accepts up to 128,000 tokens, QwQ 32B up to 131,072. Confirm the limit for your specific deployment channel before relying on it.
DeepSeek R1 vs QwQ 32B at a glance
| Attribute | DeepSeek R1 | QwQ 32B |
|---|---|---|
| Provider | DeepSeek | Alibaba |
| Released | 2025-01-20 | 2025-03-06 |
| Context window | 128,000 tokens | 131,072 tokens |
| Input price | $0.55/M tokens | $0.15/M tokens |
| Output price | $2.19/M tokens | $0.6/M tokens |
| Licence | MIT | Apache-2.0 |
| Self-hostable | Yes, open weights | Yes, open weights |
| Modalities | text | text |
Benchmarks reported for both
| Benchmark | DeepSeek R1 | QwQ 32B | Reported |
|---|---|---|---|
| LiveCodeBench (avg@8) | 65.9 | 63.4 | Date not published |
Each row compares the same benchmark, the same reported metric, and the same task set. Scores are as published by their cited sources on the dates shown. Different runs still use different harnesses and prompts, so treat these as directional evidence rather than a head-to-head result.
Where they differ most
- Cost Efficiency: DeepSeek R1 75%, QwQ 32B 91%. QwQ 32B leads on this dimension.
- Coding: DeepSeek R1 66%, QwQ 32B 63%. 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 QwQ 32B.
Frequently asked questions
Which is better, DeepSeek R1 or QwQ 32B?
DeepSeek R1 and QwQ 32B target different workloads — see the benchmark and pricing tables for a side-by-side answer.
Is DeepSeek R1 cheaper than QwQ 32B?
Compare $0.00055 vs $0.00015 on this page.