DeepSeek-R1-Distill-Qwen-32B vs o3-pro vs QwQ 32B
o3-pro comes out ahead, 68 to 52 and 47 on our weighted score, though QwQ 32B is 47× cheaper per token.
DeepSeekDeepSeek-R1-Distill-Qwen-32B
47/100- ECI137.4
- Price—
- Context131K
- Our pick
OpenAIo3-pro
68/100- ECI147.4
- Price$20.00 / $80.00
- Context200K
Alibaba (Qwen)QwQ 32B
52/100- ECI137.6
- Price$0.66 / $1.00
- Context131K
o3-pro is our pick
o3-pro is the better all-round choice, scoring 68/100 against QwQ 32B (52) and DeepSeek-R1-Distill-Qwen-32B (47). It leads on capability, inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.
- Capabilityo3-proCapabilities Index (ECI): o3-pro 147.4 · QwQ 32B 137.6 · DeepSeek-R1-Distill-Qwen-32B 137.4
- Lowest priceQwQ 32BQwQ 32B $0.745 · o3-pro $35.00 per 1M tokens (3:1 blend) · DeepSeek-R1-Distill-Qwen-32B unpriced
- Longest contexto3-proo3-pro 200,000 · DeepSeek-R1-Distill-Qwen-32B 131,072 · QwQ 32B 131,072 tokens
- Widest inputso3-proDeepSeek-R1-Distill-Qwen-32B: Text · o3-pro: Text, Images · QwQ 32B: Text
- Self-hostingDeepSeek-R1-Distill-Qwen-32B and QwQ 32BPublishes downloadable weights
| Measure | Weight | DeepSeek-R1-Distill-Qwen-32B | o3-pro | QwQ 32B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 62 | 75 | 62 |
| Inputs & features | 20% | 10 | 70 | 35 |
| Context window | 13% | 24 | 32 | 24 |
| Overall | 100% | 47/100 | 68/100 | 52/100 |
Left out because at least one model lacks the data: price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek-R1-Distill-Qwen-32BDeepSeek | o3-proOpenAI | QwQ 32BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 137.4 | 147.4 (best) | 137.6 |
| ECI rank | #110 of 148 | #60 of 148 (best) | #109 of 148 |
| GPQA DiamondGraduate-level science questions | 64.1% | — | 65.3% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 55.6% | — | 59.2% (best) |
| Price per million tokens | |||
| Input | — | $20.00 | $0.66 (best) |
| Output | — | $80.00 | $1.00 (best) |
| Cached input | — | — | — |
| Blended (3:1) | — | $35.00 | $0.745 (best) |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Official OpenAI API | Median of 1 providers |
| Limits | |||
| Context window | 131,072 tokens | 200,000 tokens (best) | 131,072 tokens |
| Max output | 32,768 tokens | 100,000 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yeslow · medium · high | Yes |
| Tool calling | No | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | — | o3-pro | — |
| API providers | — | 6 (best) | 1 |
| Released | Jan 20, 2025 | Jun 10, 2025 | Mar 5, 2025 |
| Knowledge cutoff | — | May 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-Distill-Qwen-32B—
- o3-pro$360.00
- QwQ 32B$8.60
Which should you choose?
Which is better: DeepSeek-R1-Distill-Qwen-32B, o3-pro or QwQ 32B?
o3-pro is the better all-round choice, scoring 68/100 against QwQ 32B (52) and DeepSeek-R1-Distill-Qwen-32B (47). It leads on capability, inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, DeepSeek-R1-Distill-Qwen-32B, o3-pro or QwQ 32B?
QwQ 32B is cheaper at $0.66 input / $1.00 output per million tokens (median across 1 API provider). o3-pro costs $20.00 input / $80.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.745 per million tokens for QwQ 32B versus $35.00 for o3-pro (47× as much). DeepSeek-R1-Distill-Qwen-32B has no published per-token price.
Which scores higher on benchmarks?
o3-pro scores higher on the Capabilities Index (ECI): o3-pro 147.4 (#60 of 148), QwQ 32B 137.6 (#109 of 148) and DeepSeek-R1-Distill-Qwen-32B 137.4 (#110 of 148). Their confidence ranges do not overlap (145.8–149.7 vs 133.1–141.7), so the gap is a real one.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek-R1-Distill-Qwen-32B, o3-pro and QwQ 32B yet, so there is no like-for-like coding score. On overall capability, o3-pro leads, which tends to carry over to coding, but test on your own codebase. Note that DeepSeek-R1-Distill-Qwen-32B does not support tool calling, which most coding agents need.
Which has the bigger context window?
o3-pro has the largest context window at 200,000 tokens, against 131,072 for DeepSeek-R1-Distill-Qwen-32B and 131,072 for QwQ 32B. Maximum output per response: DeepSeek-R1-Distill-Qwen-32B up to 32,768, o3-pro up to 100,000, QwQ 32B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
DeepSeek-R1-Distill-Qwen-32B accepts text; o3-pro accepts text and images; QwQ 32B accepts text. o3-pro handles the widest range of inputs.
Are any of these open source?
DeepSeek-R1-Distill-Qwen-32B and QwQ 32B publishes its weights and can be self-hosted; o3-pro is proprietary.
Which is newer?
o3-pro is the newest, released Jun 10, 2025. QwQ 32B came out Mar 5, 2025; DeepSeek-R1-Distill-Qwen-32B came out Jan 20, 2025. Knowledge cutoff: o3-pro May 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.
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