DeepSeek-R1 vs QwQ 32B
Too close to call on our weighted score (QwQ 32B 53, DeepSeek-R1 51). The right pick depends on what you value most.
DeepSeekDeepSeek-R1
51/100- ECI139.0
- Price$0.70 / $2.60
- Context128K
Alibaba (Qwen)QwQ 32B
53/100- ECI137.6
- Price$0.66 / $1.00
- Context131K
Add a model
Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 2 points (QwQ 32B 53/100, DeepSeek-R1 51/100), so choose by what matters most for your work: DeepSeek-R1 for raw capability, QwQ 32B on price and QwQ 32B for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityDeepSeek-R1Capabilities Index (ECI): DeepSeek-R1 139.0 · QwQ 32B 137.6
- Lowest priceQwQ 32BQwQ 32B $0.745 · DeepSeek-R1 $1.18 per 1M tokens (3:1 blend)
- Longest contextQwQ 32BQwQ 32B 131,072 · DeepSeek-R1 128,000 tokens
- Widest inputsSame inputsDeepSeek-R1: Text · QwQ 32B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | DeepSeek-R1 | QwQ 32B |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 64 | 62 |
| Price | 25% | 47 | 56 |
| Inputs & features | 15% | 35 | 35 |
| Context window | 10% | 24 | 24 |
| Overall | 100% | 51/100 | 53/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek-R1DeepSeek | QwQ 32BAlibaba (Qwen) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 139.0 (best) | 137.6 |
| ECI rank | #104 of 148 (best) | #109 of 148 |
| GPQA DiamondGraduate-level science questions | 71.7% (best) | 65.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | 53.3% | 59.2% (best) |
| Price per million tokens | ||
| Input | $0.70 | $0.66 (best) |
| Output | $2.60 | $1.00 (best) |
| Cached input | — | — |
| Blended (3:1) | $1.18 | $0.745 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 11 providers | Median of 1 providers |
| Limits | ||
| Context window | 128,000 tokens | 131,072 tokens (best) |
| Max output | 32,768 tokens (best) | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | — | — |
| API providers | 12 (best) | 1 |
| Released | Jan 20, 2025 | Mar 5, 2025 |
| Knowledge cutoff | Jul 2024 | Apr 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- DeepSeek-R1$12.20
- QwQ 32B$8.60
Which should you choose?
Which is better: DeepSeek-R1 or QwQ 32B?
It is close. Our weighted score puts them within 2 points (QwQ 32B 53/100, DeepSeek-R1 51/100), so choose by what matters most for your work: DeepSeek-R1 for raw capability, QwQ 32B on price and QwQ 32B for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek-R1 or QwQ 32B?
QwQ 32B is cheaper at $0.66 input / $1.00 output per million tokens (median across 1 API provider). DeepSeek-R1 costs $0.70 input / $2.60 output per million tokens (median across 11 API providers). At a typical mix of three input tokens to one output token, that is $0.745 per million tokens for QwQ 32B versus $1.18 for DeepSeek-R1 (1.6× as much).
Which scores higher on benchmarks?
DeepSeek-R1 scores higher on the Capabilities Index (ECI): DeepSeek-R1 139.0 (#104 of 148) and QwQ 32B 137.6 (#109 of 148). The confidence ranges of the top two overlap (136.2–140.4 vs 133.1–141.7), so treat the gap as small. On individual benchmarks: GPQA Diamond — DeepSeek-R1 71.7%, QwQ 32B 65.3%; OTIS Mock AIME 2024–2025 — QwQ 32B 59.2%, DeepSeek-R1 53.3%.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek-R1 and QwQ 32B yet, so there is no like-for-like coding score. On overall capability, DeepSeek-R1 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
QwQ 32B has the largest context window at 131,072 tokens, against 128,000 for DeepSeek-R1. Maximum output per response: DeepSeek-R1 up to 32,768, QwQ 32B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
DeepSeek-R1 accepts text; QwQ 32B accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
QwQ 32B is the newest, released Mar 5, 2025. DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: DeepSeek-R1 Jul 2024, QwQ 32B Apr 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
Related comparisons
- Add Qwen3 235B-A22BThree-way comparison
- DeepSeek-R1 vs Qwen3 235B-A22BAlibaba (Qwen) · ECI 139.4
- DeepSeek-R1 vs Gemini 2.5 FlashGoogle · ECI 140.8
- DeepSeek-R1 vs GPT-4.1 miniOpenAI · ECI 135.0
- DeepSeek-R1 vs Mistral Medium 3Mistral AI · ECI 134.1
- QwQ 32B vs GPT-4.1 miniOpenAI · ECI 135.0
- QwQ 32B vs Mistral Medium 3Mistral AI · ECI 134.1
