QwQ 32B vs GPT-4.1
Too close to call on our weighted score (GPT-4.1 53, QwQ 32B 53). The right pick depends on what you value most.
Too close to call
It is close. Our weighted score puts them within a point (GPT-4.1 53/100, QwQ 32B 53/100), so choose by what matters most for your work: QwQ 32B for raw capability and GPT-4.1 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwQ 32BCapabilities Index (ECI): QwQ 32B 137.6 · GPT-4.1 136.8
- Lowest priceQwQ 32BQwQ 32B $0.745 · GPT-4.1 $3.50 per 1M tokens (3:1 blend)
- Longest contextGPT-4.1GPT-4.1 1,047,576 · QwQ 32B 131,072 tokens
- Widest inputsGPT-4.1QwQ 32B: Text · GPT-4.1: Text, Images, PDFs
- Self-hostingQwQ 32BPublishes downloadable weights
| Measure | Weight | QwQ 32B | GPT-4.1 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 62 | 61 |
| Price | 25% | 56 | 24 |
| Inputs & features | 15% | 35 | 70 |
| Context window | 10% | 24 | 61 |
| 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) |  GPT-4.1OpenAI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 137.6 (best) | 136.8 |
| ECI rank | #109 of 148 (best) | #111 of 148 |
| GPQA DiamondGraduate-level science questions | 65.3% | 66.9% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | — | 6.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | 59.2% (best) | 38.3% |
| SWE-bench VerifiedFixing real GitHub issues | — | 48.5% |
| SimpleQA VerifiedShort factual questions | — | 31.1% |
| Price per million tokens | ||
| Input | $0.66 (best) | $2.00 |
| Output | $1.00 (best) | $8.00 |
| Cached input | — | $0.50 |
| Blended (3:1) | $0.745 (best) | $3.50 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 1 providers | Official OpenAI API |
| Limits | ||
| Context window | 131,072 tokens | 1,047,576 tokens (best) |
| Max output | 8,192 tokens | 32,768 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | Yes |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | No |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | Open | Proprietary |
| API model ID | — | gpt-4.1 |
| API providers | 1 | 25 (best) |
| Released | Mar 5, 2025 | Apr 14, 2025 |
| Knowledge cutoff | Apr 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.
- QwQ 32B$8.60
- GPT-4.1$36.00
Which should you choose?
Which is better: QwQ 32B or GPT-4.1?
It is close. Our weighted score puts them within a point (GPT-4.1 53/100, QwQ 32B 53/100), so choose by what matters most for your work: QwQ 32B for raw capability and GPT-4.1 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, QwQ 32B or GPT-4.1?
QwQ 32B is cheaper at $0.66 input / $1.00 output per million tokens (median across 1 API provider). GPT-4.1 costs $2.00 input / $8.00 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 $3.50 for GPT-4.1 (4.7× as much).
Which scores higher on benchmarks?
QwQ 32B scores higher on the Capabilities Index (ECI): QwQ 32B 137.6 (#109 of 148) and GPT-4.1 136.8 (#111 of 148). The confidence ranges of the top two overlap (133.1–141.7 vs 133.6–138.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-4.1 66.9%, QwQ 32B 65.3%; OTIS Mock AIME 2024–2025 — QwQ 32B 59.2%, GPT-4.1 38.3%.
Which is better for coding?
There are no published SWE-bench Verified results for QwQ 32B yet, so there is no like-for-like coding score. On overall capability, QwQ 32B 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?
GPT-4.1 has the largest context window at 1,047,576 tokens, against 131,072 for QwQ 32B. Maximum output per response: QwQ 32B up to 8,192, GPT-4.1 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
QwQ 32B accepts text; GPT-4.1 accepts text, images and PDFs. GPT-4.1 handles the widest range of inputs.
Are any of these open source?
QwQ 32B publishes its weights and can be self-hosted; GPT-4.1 is proprietary.
Which is newer?
GPT-4.1 is the newest, released Apr 14, 2025. QwQ 32B came out Mar 5, 2025. Knowledge cutoff: QwQ 32B Apr 2024, GPT-4.1 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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