Qwen3 235B-A22B vs GPT-4.1 vs DeepSeek-R1
Too close to call on our weighted score (GPT-4.1 53, Qwen3 235B-A22B 51, DeepSeek-R1 51). The right pick depends on what you value most.
Alibaba (Qwen)Qwen3 235B-A22B
51/100- ECI139.4
- Price$0.70 / $2.80
- Context131K
OpenAIGPT-4.1
53/100- ECI136.8
- Price$2.00 / $8.00
- Context1.05M
DeepSeekDeepSeek-R1
51/100- ECI139.0
- Price$0.70 / $2.60
- Context128K
Too close to call
It is close. Our weighted score puts them within 2 points (GPT-4.1 53/100, Qwen3 235B-A22B 51/100, DeepSeek-R1 51/100), so choose by what matters most for your work: Qwen3 235B-A22B for raw capability, DeepSeek-R1 on price and GPT-4.1 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3 235B-A22BCapabilities Index (ECI): Qwen3 235B-A22B 139.4 · DeepSeek-R1 139.0 · GPT-4.1 136.8
- Lowest priceDeepSeek-R1DeepSeek-R1 $1.18 · Qwen3 235B-A22B $1.23 · GPT-4.1 $3.50 per 1M tokens (3:1 blend)
- Longest contextGPT-4.1GPT-4.1 1,047,576 · Qwen3 235B-A22B 131,072 · DeepSeek-R1 128,000 tokens
- Widest inputsGPT-4.1Qwen3 235B-A22B: Text · GPT-4.1: Text, Images, PDFs · DeepSeek-R1: Text
- Self-hostingQwen3 235B-A22B and DeepSeek-R1Publishes downloadable weights
| Measure | Weight | Qwen3 235B-A22B | GPT-4.1 | DeepSeek-R1 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 65 | 61 | 64 |
| Price | 25% | 46 | 24 | 47 |
| Inputs & features | 15% | 35 | 70 | 35 |
| Context window | 10% | 24 | 61 | 24 |
| Overall | 100% | 51/100 | 53/100 | 51/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3 235B-A22BAlibaba (Qwen) | GPT-4.1OpenAI | DeepSeek-R1DeepSeek |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 139.4 (best) | 136.8 | 139.0 |
| ECI rank | #103 of 148 (best) | #111 of 148 | #104 of 148 |
| GPQA DiamondGraduate-level science questions | 70.7% | 66.9% | 71.7% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | — | 6.0% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 38.3% | 53.3% (best) |
| SWE-bench VerifiedFixing real GitHub issues | — | 48.5% | — |
| SimpleQA VerifiedShort factual questions | — | 31.1% | — |
| Price per million tokens | |||
| Input | $0.70 (best) | $2.00 | $0.70 (best) |
| Output | $2.80 | $8.00 | $2.60 (best) |
| Cached input | — | $0.50 | — |
| Blended (3:1) | $1.23 | $3.50 | $1.18 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official OpenAI API | Median of 11 providers |
| Limits | |||
| Context window | 131,072 tokens | 1,047,576 tokens (best) | 128,000 tokens |
| Max output | 16,384 tokens | 32,768 tokens (best) | 32,768 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | qwen3-235b-a22b | gpt-4.1 | — |
| API providers | 7 | 25 (best) | 12 |
| Released | Apr 28, 2025 | Apr 14, 2025 | Jan 20, 2025 |
| Knowledge cutoff | Apr 2025 | Apr 2024 | Jul 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3 235B-A22B$12.60
- GPT-4.1$36.00
- DeepSeek-R1$12.20
Which should you choose?
Which is better: Qwen3 235B-A22B, GPT-4.1 or DeepSeek-R1?
It is close. Our weighted score puts them within 2 points (GPT-4.1 53/100, Qwen3 235B-A22B 51/100, DeepSeek-R1 51/100), so choose by what matters most for your work: Qwen3 235B-A22B for raw capability, DeepSeek-R1 on price and GPT-4.1 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3 235B-A22B, GPT-4.1 or DeepSeek-R1?
DeepSeek-R1 is cheaper at $0.70 input / $2.60 output per million tokens (median across 11 API providers). Qwen3 235B-A22B costs $0.70 input / $2.80 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). At a typical mix of three input tokens to one output token, that is $1.18 per million tokens for DeepSeek-R1 versus $1.23 for Qwen3 235B-A22B (1× as much) and $3.50 for GPT-4.1 (3× as much).
Which scores higher on benchmarks?
Qwen3 235B-A22B scores higher on the Capabilities Index (ECI): Qwen3 235B-A22B 139.4 (#103 of 148), DeepSeek-R1 139.0 (#104 of 148) and GPT-4.1 136.8 (#111 of 148). The confidence ranges of the top two overlap (135.2–140.8 vs 136.2–140.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — DeepSeek-R1 71.7%, Qwen3 235B-A22B 70.7%, GPT-4.1 66.9%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 235B-A22B and DeepSeek-R1 yet, so there is no like-for-like coding score. On overall capability, Qwen3 235B-A22B 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 131,072 for Qwen3 235B-A22B and 128,000 for DeepSeek-R1. Maximum output per response: Qwen3 235B-A22B up to 16,384, GPT-4.1 up to 32,768, DeepSeek-R1 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Qwen3 235B-A22B accepts text; GPT-4.1 accepts text, images and PDFs; DeepSeek-R1 accepts text. GPT-4.1 handles the widest range of inputs.
Are any of these open source?
Qwen3 235B-A22B and DeepSeek-R1 publishes its weights and can be self-hosted; GPT-4.1 is proprietary.
Which is newer?
Qwen3 235B-A22B is the newest, released Apr 28, 2025. GPT-4.1 came out Apr 14, 2025; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: Qwen3 235B-A22B Apr 2025, GPT-4.1 Apr 2024, DeepSeek-R1 Jul 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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