Qwen3 32B vs GPT-4.1 mini vs DeepSeek-R1
GPT-4.1 mini comes out ahead, 60 to 51 and 51 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)
Qwen3 32B
51/100- ECI138.5
- Price$0.70 / $2.80
- Context131K
- Our pick
OpenAI
GPT-4.1 mini
60/100- ECI135.0
- Price$0.40 / $1.60
- Context1.05M
DeepSeek
DeepSeek-R1
51/100- ECI139.0
- Price$0.70 / $2.60
- Context128K
GPT-4.1 mini is our pick
GPT-4.1 mini is the better all-round choice, scoring 60/100 against DeepSeek-R1 (51) and Qwen3 32B (51). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityDeepSeek-R1Capabilities Index (ECI): DeepSeek-R1 139.0 · Qwen3 32B 138.5 · GPT-4.1 mini 135.0
- Lowest priceGPT-4.1 miniGPT-4.1 mini $0.70 · DeepSeek-R1 $1.18 · Qwen3 32B $1.23 per 1M tokens (3:1 blend)
- Longest contextGPT-4.1 miniGPT-4.1 mini 1,047,576 · Qwen3 32B 131,072 · DeepSeek-R1 128,000 tokens
- Widest inputsGPT-4.1 miniQwen3 32B: Text · GPT-4.1 mini: Text, Images, PDFs · DeepSeek-R1: Text
- Self-hostingQwen3 32B and DeepSeek-R1Publishes downloadable weights
| Measure | Weight | Qwen3 32B | GPT-4.1 mini | DeepSeek-R1 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 64 | 59 | 64 |
| Price | 25% | 46 | 57 | 47 |
| Inputs & features | 15% | 35 | 70 | 35 |
| Context window | 10% | 24 | 61 | 24 |
| Overall | 100% | 51/100 | 60/100 | 51/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 138.5 | 135.0 | 139.0 (best) |
| ECI rank | #106 of 148 | #115 of 148 | #104 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 65.7% | 65.9% | 71.7% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | — | 6.7% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 66.9% (best) | 44.7% | 53.3% |
| SimpleQA VerifiedShort factual questions | — | 12.7% | — |
| Price per million tokens | |||
| Input | $0.70 | $0.40 (best) | $0.70 |
| Output | $2.80 | $1.60 (best) | $2.60 |
| Cached input | — | $0.10 | — |
| Blended (3:1) | $1.23 | $0.70 (best) | $1.18 |
| 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 | qwen3-32b | gpt-4.1-mini | — |
| API providers | 14 | 24 (best) | 12 |
| Released | Apr 29, 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 32B$12.60
GPT-4.1 mini$7.20
DeepSeek-R1$12.20
Which should you choose?
Which is better: Qwen3 32B, GPT-4.1 mini or DeepSeek-R1?
GPT-4.1 mini is the better all-round choice, scoring 60/100 against DeepSeek-R1 (51) and Qwen3 32B (51). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3 32B, GPT-4.1 mini or DeepSeek-R1?
GPT-4.1 mini is cheaper at $0.40 input / $1.60 output per million tokens (official OpenAI API price). DeepSeek-R1 costs $0.70 input / $2.60 output per million tokens (median across 11 API providers); Qwen3 32B costs $0.70 input / $2.80 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.70 per million tokens for GPT-4.1 mini versus $1.18 for DeepSeek-R1 (1.7× as much) and $1.23 for Qwen3 32B (1.8× as much).
Which scores higher on benchmarks?
DeepSeek-R1 scores higher on the Capabilities Index (ECI): DeepSeek-R1 139.0 (#104 of 148), Qwen3 32B 138.5 (#106 of 148) and GPT-4.1 mini 135.0 (#115 of 148). The confidence ranges of the top two overlap (136.2–140.4 vs 135.1–140.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — DeepSeek-R1 71.7%, GPT-4.1 mini 65.9%, Qwen3 32B 65.7%; OTIS Mock AIME 2024–2025 — Qwen3 32B 66.9%, DeepSeek-R1 53.3%, GPT-4.1 mini 44.7%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 32B, GPT-4.1 mini and DeepSeek-R1 yet, so there is no like-for-like coding score. On overall capability, DeepSeek-R1 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 mini has the largest context window at 1,047,576 tokens, against 131,072 for Qwen3 32B and 128,000 for DeepSeek-R1. Maximum output per response: Qwen3 32B up to 16,384, GPT-4.1 mini up to 32,768, DeepSeek-R1 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Qwen3 32B accepts text; GPT-4.1 mini accepts text, images and PDFs; DeepSeek-R1 accepts text. GPT-4.1 mini handles the widest range of inputs.
Are any of these open source?
Qwen3 32B and DeepSeek-R1 publishes its weights and can be self-hosted; GPT-4.1 mini is proprietary.
Which is newer?
Qwen3 32B is the newest, released Apr 29, 2025. GPT-4.1 mini came out Apr 14, 2025; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: Qwen3 32B Apr 2025, GPT-4.1 mini 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.