GPT-5.1 vs Qwen3 32B vs Qwen3.6 Max Preview
GPT-5.1 comes out ahead, 60 to 54 and 51 on our weighted score, though Qwen3 32B is 2.8× cheaper per token.
- Our pick
OpenAIGPT-5.1
60/100- ECI149.7
- Price$1.25 / $10.00
- Context400K
Alibaba (Qwen)Qwen3 32B
51/100- ECI138.5
- Price$0.70 / $2.80
- Context131K
- Alibaba (Qwen)
Qwen3.6 Max Preview
54/100- ECI149.2
- Price$1.30 / $7.80
- Context262K
GPT-5.1 is our pick
GPT-5.1 is the better all-round choice, scoring 60/100 against Qwen3.6 Max Preview (54) and Qwen3 32B (51). It leads on inputs & features and context window. Qwen3 32B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-5.1Capabilities Index (ECI): GPT-5.1 149.7 · Qwen3.6 Max Preview 149.2 · Qwen3 32B 138.5
- Lowest priceQwen3 32BQwen3 32B $1.23 · Qwen3.6 Max Preview $2.92 · GPT-5.1 $3.44 per 1M tokens (3:1 blend)
- Longest contextGPT-5.1GPT-5.1 400,000 · Qwen3.6 Max Preview 262,144 · Qwen3 32B 131,072 tokens
- Widest inputsGPT-5.1GPT-5.1: Text, Images · Qwen3 32B: Text · Qwen3.6 Max Preview: Text
- Self-hostingQwen3 32BPublishes downloadable weights
| Measure | Weight | GPT-5.1 | Qwen3 32B | Qwen3.6 Max Preview |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 78 | 64 | 77 |
| Price | 25% | 24 | 46 | 28 |
| Inputs & features | 15% | 70 | 35 | 35 |
| Context window | 10% | 44 | 24 | 37 |
| Overall | 100% | 60/100 | 51/100 | 54/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT-5.1OpenAI | Qwen3 32BAlibaba (Qwen) | Qwen3.6 Max PreviewAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 149.7 (best) | 138.5 | 149.2 |
| ECI rank | #52 of 148 (best) | #106 of 148 | #54 of 148 |
| GPQA DiamondGraduate-level science questions | 87.6% (best) | 65.7% | 87.4% |
| OTIS Mock AIME 2024–2025Competition mathematics | 88.6% | 66.9% | 91.1% (best) |
| SWE-bench VerifiedFixing real GitHub issues | 68.0% | — | 76.7% (best) |
| SimpleQA VerifiedShort factual questions | 48.0% | — | 52.0% (best) |
| Price per million tokens | |||
| Input | $1.25 | $0.70 (best) | $1.30 |
| Output | $10.00 | $2.80 (best) | $7.80 |
| Cached input | $0.125 (best) | — | $0.13 |
| Blended (3:1) | $3.44 | $1.23 (best) | $2.92 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Official Alibaba API | Official Alibaba API |
| Limits | |||
| Context window | 400,000 tokens (best) | 131,072 tokens | 262,144 tokens |
| Max output | 128,000 tokens (best) | 16,384 tokens | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yeslow · medium · high | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | gpt-5.1 | qwen3-32b | qwen3.6-max-preview |
| API providers | 21 (best) | 14 | 10 |
| Released | Nov 13, 2025 | Apr 29, 2025 | Apr 20, 2026 |
| Knowledge cutoff | Sep 30, 2024 | Apr 2025 | Apr 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GPT-5.1$32.50
- Qwen3 32B$12.60
- Qwen3.6 Max Preview$28.60
Which should you choose?
Which is better: GPT-5.1, Qwen3 32B or Qwen3.6 Max Preview?
GPT-5.1 is the better all-round choice, scoring 60/100 against Qwen3.6 Max Preview (54) and Qwen3 32B (51). It leads on inputs & features and context window. Qwen3 32B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GPT-5.1, Qwen3 32B or Qwen3.6 Max Preview?
Qwen3 32B is cheaper at $0.70 input / $2.80 output per million tokens (official Alibaba API price). Qwen3.6 Max Preview costs $1.30 input / $7.80 output per million tokens (official Alibaba API price); GPT-5.1 costs $1.25 input / $10.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $1.23 per million tokens for Qwen3 32B versus $2.92 for Qwen3.6 Max Preview (2.4× as much) and $3.44 for GPT-5.1 (2.8× as much).
Which scores higher on benchmarks?
GPT-5.1 scores higher on the Capabilities Index (ECI): GPT-5.1 149.7 (#52 of 148), Qwen3.6 Max Preview 149.2 (#54 of 148) and Qwen3 32B 138.5 (#106 of 148). The confidence ranges of the top two overlap (148.3–151.1 vs 147.6–152.0), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-5.1 87.6%, Qwen3.6 Max Preview 87.4%, Qwen3 32B 65.7%; OTIS Mock AIME 2024–2025 — Qwen3.6 Max Preview 91.1%, GPT-5.1 88.6%, Qwen3 32B 66.9%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 32B yet, so there is no like-for-like coding score. On overall capability, GPT-5.1 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
GPT-5.1 has the largest context window at 400,000 tokens, against 262,144 for Qwen3.6 Max Preview and 131,072 for Qwen3 32B. Maximum output per response: GPT-5.1 up to 128,000, Qwen3 32B up to 16,384, Qwen3.6 Max Preview up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GPT-5.1 accepts text and images; Qwen3 32B accepts text; Qwen3.6 Max Preview accepts text. GPT-5.1 handles the widest range of inputs.
Are any of these open source?
Qwen3 32B publishes its weights and can be self-hosted; GPT-5.1 and Qwen3.6 Max Preview is proprietary.
Which is newer?
Qwen3.6 Max Preview is the newest, released Apr 20, 2026. GPT-5.1 came out Nov 13, 2025; Qwen3 32B came out Apr 29, 2025. Knowledge cutoff: GPT-5.1 Sep 30, 2024, Qwen3 32B Apr 2025, Qwen3.6 Max Preview Apr 2025.
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.
