o3-pro vs QwQ 32B
Too close to call on our weighted score (QwQ 32B 53, o3-pro 51). The right pick depends on what you value most.
Too close to call
It is close. Our weighted score puts them within 2 points (QwQ 32B 53/100, o3-pro 51/100), so choose by what matters most for your work: o3-pro for raw capability and QwQ 32B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- Capabilityo3-proCapabilities Index (ECI): o3-pro 147.4 · QwQ 32B 137.6
- Lowest priceQwQ 32BQwQ 32B $0.745 · o3-pro $35.00 per 1M tokens (3:1 blend)
- Longest contexto3-proo3-pro 200,000 · QwQ 32B 131,072 tokens
- Widest inputso3-proo3-pro: Text, Images · QwQ 32B: Text
- Self-hostingQwQ 32BPublishes downloadable weights
| Measure | Weight | o3-pro | QwQ 32B |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 75 | 62 |
| Price | 25% | 0 | 56 |
| Inputs & features | 15% | 70 | 35 |
| Context window | 10% | 32 | 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 | ||
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 147.4 (best) | 137.6 |
| ECI rank | #60 of 148 (best) | #109 of 148 |
| GPQA DiamondGraduate-level science questions | — | 65.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 59.2% |
| 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 | 200,000 tokens (best) | 131,072 tokens |
| Max output | 100,000 tokens (best) | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yeslow · medium · high | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Proprietary | Open |
| API model ID | o3-pro | — |
| API providers | 6 (best) | 1 |
| Released | 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.
o3-pro$360.00
QwQ 32B$8.60
Which should you choose?
Which is better: o3-pro or QwQ 32B?
It is close. Our weighted score puts them within 2 points (QwQ 32B 53/100, o3-pro 51/100), so choose by what matters most for your work: o3-pro for raw capability and QwQ 32B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, 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).
Which scores higher on benchmarks?
o3-pro scores higher on the Capabilities Index (ECI): o3-pro 147.4 (#60 of 148) and QwQ 32B 137.6 (#109 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 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. Both support tool calling for agent workflows.
Which has the bigger context window?
o3-pro has the largest context window at 200,000 tokens, against 131,072 for QwQ 32B. Maximum output per response: o3-pro up to 100,000, QwQ 32B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
o3-pro accepts text and images; QwQ 32B accepts text. o3-pro handles the widest range of inputs.
Are any of these open source?
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. 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.