GPT-4.1 vs Qwen3 Max vs Claude Sonnet 3.7
Too close to call on our weighted score (GPT-4.1 53, Claude Sonnet 3.7 50, Qwen3 Max 50). The right pick depends on what you value most.
OpenAIGPT-4.1
53/100- ECI136.8
- Price$2.00 / $8.00
- Context1.05M
Alibaba (Qwen)Qwen3 Max
50/100- ECI142.4
- Price$1.20 / $6.00
- Context262K
AnthropicClaude Sonnet 3.7
50/100- ECI141.2
- Price$3.00 / $15.00
- Context200K
Too close to call
It is close. Our weighted score puts them within 3 points (GPT-4.1 53/100, Claude Sonnet 3.7 50/100, Qwen3 Max 50/100), so choose by what matters most for your work: Qwen3 Max for raw capability and GPT-4.1 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3 MaxCapabilities Index (ECI): Qwen3 Max 142.4 · Claude Sonnet 3.7 141.2 · GPT-4.1 136.8
- Lowest priceQwen3 MaxQwen3 Max $2.40 · GPT-4.1 $3.50 · Claude Sonnet 3.7 $6.00 per 1M tokens (3:1 blend)
- Longest contextGPT-4.1GPT-4.1 1,047,576 · Qwen3 Max 262,144 · Claude Sonnet 3.7 200,000 tokens
- Widest inputsGPT-4.1 and Claude Sonnet 3.7GPT-4.1: Text, Images, PDFs · Qwen3 Max: Text · Claude Sonnet 3.7: Text, Images, PDFs
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | GPT-4.1 | Qwen3 Max | Claude Sonnet 3.7 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 61 | 68 | 67 |
| Price | 25% | 24 | 32 | 13 |
| Inputs & features | 15% | 70 | 25 | 70 |
| Context window | 10% | 61 | 37 | 32 |
| Overall | 100% | 53/100 | 50/100 | 50/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT-4.1OpenAI | Qwen3 MaxAlibaba (Qwen) | Claude Sonnet 3.7Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 136.8 | 142.4 (best) | 141.2 |
| ECI rank | #111 of 148 | #91 of 148 (best) | #96 of 148 |
| GPQA DiamondGraduate-level science questions | 66.9% | 72.6% | 79.7% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 6.0% | 19.0% (best) | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 38.3% | 73.3% (best) | 57.8% |
| SWE-bench VerifiedFixing real GitHub issues | 48.5% | — | 61.0% (best) |
| SimpleQA VerifiedShort factual questions | 31.1% | 48.8% (best) | — |
| Price per million tokens | |||
| Input | $2.00 | $1.20 (best) | $3.00 |
| Output | $8.00 | $6.00 (best) | $15.00 |
| Cached input | $0.50 | — | — |
| Blended (3:1) | $3.50 | $2.40 (best) | $6.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Official Alibaba API | Median of 3 providers |
| Limits | |||
| Context window | 1,047,576 tokens (best) | 262,144 tokens | 200,000 tokens |
| Max output | 32,768 tokens | 65,536 tokens (best) | 64,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | Yes | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | gpt-4.1 | qwen3-max | — |
| API providers | 25 (best) | 16 | 3 |
| Released | Apr 14, 2025 | Sep 23, 2025 | Feb 19, 2025 |
| Knowledge cutoff | Apr 2024 | Apr 2025 | Oct 31, 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GPT-4.1$36.00
- Qwen3 Max$24.00
- Claude Sonnet 3.7$60.00
Which should you choose?
Which is better: GPT-4.1, Qwen3 Max or Claude Sonnet 3.7?
It is close. Our weighted score puts them within 3 points (GPT-4.1 53/100, Claude Sonnet 3.7 50/100, Qwen3 Max 50/100), so choose by what matters most for your work: Qwen3 Max 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, GPT-4.1, Qwen3 Max or Claude Sonnet 3.7?
Qwen3 Max is cheaper at $1.20 input / $6.00 output per million tokens (official Alibaba API price). GPT-4.1 costs $2.00 input / $8.00 output per million tokens (official OpenAI API price); Claude Sonnet 3.7 costs $3.00 input / $15.00 output per million tokens (median across 3 API providers). At a typical mix of three input tokens to one output token, that is $2.40 per million tokens for Qwen3 Max versus $3.50 for GPT-4.1 (1.5× as much) and $6.00 for Claude Sonnet 3.7 (2.5× as much).
Which scores higher on benchmarks?
Qwen3 Max scores higher on the Capabilities Index (ECI): Qwen3 Max 142.4 (#91 of 148), Claude Sonnet 3.7 141.2 (#96 of 148) and GPT-4.1 136.8 (#111 of 148). The confidence ranges of the top two overlap (140.0–144.6 vs 138.7–142.9), so treat the gap as small. On individual benchmarks: GPQA Diamond — Claude Sonnet 3.7 79.7%, Qwen3 Max 72.6%, GPT-4.1 66.9%; OTIS Mock AIME 2024–2025 — Qwen3 Max 73.3%, Claude Sonnet 3.7 57.8%, GPT-4.1 38.3%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 Max yet, so there is no like-for-like coding score. On overall capability, Qwen3 Max 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-4.1 has the largest context window at 1,047,576 tokens, against 262,144 for Qwen3 Max and 200,000 for Claude Sonnet 3.7. Maximum output per response: GPT-4.1 up to 32,768, Qwen3 Max up to 65,536, Claude Sonnet 3.7 up to 64,000 tokens.
Which can read images, PDFs, audio or video?
GPT-4.1 accepts text, images and PDFs; Qwen3 Max accepts text; Claude Sonnet 3.7 accepts text, images and PDFs. GPT-4.1 handles the widest range of inputs.
Are any of these open source?
No. GPT-4.1, Qwen3 Max and Claude Sonnet 3.7 are proprietary and only available through APIs and apps.
Which is newer?
Qwen3 Max is the newest, released Sep 23, 2025. GPT-4.1 came out Apr 14, 2025; Claude Sonnet 3.7 came out Feb 19, 2025. Knowledge cutoff: GPT-4.1 Apr 2024, Qwen3 Max Apr 2025, Claude Sonnet 3.7 Oct 31, 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.
