QwQ 32B vs DeepSeek R1 0528
Too close to call on our weighted score (DeepSeek R1 0528 53, QwQ 32B 53). The right pick depends on what you value most.
Alibaba (Qwen)QwQ 32B
53/100- ECI137.5
- Price$0.53 / $0.70
- Context131K
DeepSeekDeepSeek R1 0528
53/100- ECI141.2
- Price$0.512 / $2.19
- Context164K
Add a model
Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within a point (DeepSeek R1 0528 53/100, QwQ 32B 53/100), so choose by what matters most for your work: DeepSeek R1 0528 for raw capability and QwQ 32B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityDeepSeek R1 0528Capabilities Index (ECI): DeepSeek R1 0528 141.2 · QwQ 32B 137.5
- Lowest priceQwQ 32BQwQ 32B $0.573 · DeepSeek R1 0528 $0.932 per 1M tokens (3:1 blend)
- Longest contextDeepSeek R1 0528DeepSeek R1 0528 163,840 · QwQ 32B 131,072 tokens
- Widest inputsSame inputsQwQ 32B: Text · DeepSeek R1 0528: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | QwQ 32B | DeepSeek R1 0528 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 61 | 66 |
| Price | 25% | 59 | 49 |
| Inputs & features | 15% | 35 | 35 |
| Context window | 10% | 25 | 28 |
| Overall | 100% | 53/100 | 53/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | QwQ 32BAlibaba (Qwen) | DeepSeek R1 0528DeepSeek |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 137.5 | 141.2 (best) |
| ECI rank | #123 of 165 | #108 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 65.3% | 76.3% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 59.2% | 66.4% (best) |
| Price per million tokens | ||
| Input | $0.53 | $0.512 (best) |
| Output | $0.70 (best) | $2.19 |
| Cached input | — | — |
| Blended (3:1) | $0.573 (best) | $0.932 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 2 providers | Median of 16 providers |
| Limits | ||
| Context window | 131,072 tokens | 163,840 tokens (best) |
| Max output | 8,192 tokens | 32,768 tokens (best) |
| 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 | OpenMIT |
| API model ID | — | — |
| API providers | 2 | 16 (best) |
| Released | Mar 5, 2025 | May 28, 2025 |
| Knowledge cutoff | 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.
- QwQ 32B$6.70
- DeepSeek R1 0528$9.50
Which should you choose?
Which is better: QwQ 32B or DeepSeek R1 0528?
It is close. Our weighted score puts them within a point (DeepSeek R1 0528 53/100, QwQ 32B 53/100), so choose by what matters most for your work: DeepSeek R1 0528 for raw capability and QwQ 32B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, QwQ 32B or DeepSeek R1 0528?
QwQ 32B is cheaper at $0.53 input / $0.70 output per million tokens (median across 2 API providers). DeepSeek R1 0528 costs $0.512 input / $2.19 output per million tokens (median across 16 API providers). At a typical mix of three input tokens to one output token, that is $0.573 per million tokens for QwQ 32B versus $0.932 for DeepSeek R1 0528 (1.6× as much).
Which scores higher on benchmarks?
DeepSeek R1 0528 scores higher on the Capabilities Index (ECI): DeepSeek R1 0528 141.2 (#108 of 165) and QwQ 32B 137.5 (#123 of 165). The confidence ranges of the top two overlap (139.0–142.9 vs 133.1–141.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — DeepSeek R1 0528 76.3%, QwQ 32B 65.3%; OTIS Mock AIME 2024–2025 — DeepSeek R1 0528 66.4%, QwQ 32B 59.2%.
Which is better for coding?
There are no published SWE-bench Verified results for QwQ 32B and DeepSeek R1 0528 yet, so there is no like-for-like coding score. On overall capability, DeepSeek R1 0528 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?
DeepSeek R1 0528 has the largest context window at 163,840 tokens, against 131,072 for QwQ 32B. Maximum output per response: QwQ 32B up to 8,192, DeepSeek R1 0528 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
QwQ 32B accepts text; DeepSeek R1 0528 accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights (MIT), so you can self-host them.
Which is newer?
DeepSeek R1 0528 is the newest, released May 28, 2025. QwQ 32B came out Mar 5, 2025. Knowledge cutoff: 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 Nov 2, 2026.
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