GPT-4.1 mini vs QwQ 32B vs Mistral Medium 3
GPT-4.1 mini comes out ahead, 60 to 53 and 53 on our weighted score, and it is the cheaper option too.
- Our pick
OpenAI
GPT-4.1 mini
60/100- ECI135.0
- Price$0.40 / $1.60
- Context1.05M
Alibaba (Qwen)
QwQ 32B
53/100- ECI137.6
- Price$0.66 / $1.00
- Context131K
Mistral AI
Mistral Medium 3
53/100- ECI134.1
- Price$0.40 / $2.00
- Context131K
GPT-4.1 mini is our pick
GPT-4.1 mini is the better all-round choice, scoring 60/100 against QwQ 32B (53) and Mistral Medium 3 (53). It leads on inputs & features and context window. QwQ 32B wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwQ 32BCapabilities Index (ECI): QwQ 32B 137.6 · GPT-4.1 mini 135.0 · Mistral Medium 3 134.1
- Lowest priceGPT-4.1 miniGPT-4.1 mini $0.70 · QwQ 32B $0.745 · Mistral Medium 3 $0.80 per 1M tokens (3:1 blend)
- Longest contextGPT-4.1 miniGPT-4.1 mini 1,047,576 · QwQ 32B 131,072 · Mistral Medium 3 131,072 tokens
- Widest inputsGPT-4.1 miniGPT-4.1 mini: Text, Images, PDFs · QwQ 32B: Text · Mistral Medium 3: Text, Images
- Self-hostingQwQ 32BPublishes downloadable weights
| Measure | Weight | GPT-4.1 mini | QwQ 32B | Mistral Medium 3 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 59 | 62 | 58 |
| Price | 25% | 57 | 56 | 54 |
| Inputs & features | 15% | 70 | 35 | 50 |
| Context window | 10% | 61 | 24 | 24 |
| Overall | 100% | 60/100 | 53/100 | 53/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 135.0 | 137.6 (best) | 134.1 |
| ECI rank | #115 of 148 | #109 of 148 (best) | #117 of 148 |
| GPQA DiamondGraduate-level science questions | 65.9% (best) | 65.3% | 59.5% |
| FrontierMath Tiers 1–3Research-level mathematics | 6.7% | — | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 44.7% | 59.2% (best) | 32.2% |
| SimpleQA VerifiedShort factual questions | 12.7% | — | — |
| Price per million tokens | |||
| Input | $0.40 (best) | $0.66 | $0.40 (best) |
| Output | $1.60 | $1.00 (best) | $2.00 |
| Cached input | $0.10 | — | — |
| Blended (3:1) | $0.70 (best) | $0.745 | $0.80 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Median of 1 providers | Official Mistral API |
| Limits | |||
| Context window | 1,047,576 tokens (best) | 131,072 tokens | 131,072 tokens |
| Max output | 32,768 tokens | 8,192 tokens | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | Yes | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | gpt-4.1-mini | — | mistral-medium-2505 |
| API providers | 24 (best) | 1 | 5 |
| Released | Apr 14, 2025 | Mar 5, 2025 | May 7, 2025 |
| Knowledge cutoff | Apr 2024 | Apr 2024 | May 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-4.1 mini$7.20
QwQ 32B$8.60
Mistral Medium 3$8.00
Which should you choose?
Which is better: GPT-4.1 mini, QwQ 32B or Mistral Medium 3?
GPT-4.1 mini is the better all-round choice, scoring 60/100 against QwQ 32B (53) and Mistral Medium 3 (53). It leads on inputs & features and context window. QwQ 32B wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GPT-4.1 mini, QwQ 32B or Mistral Medium 3?
GPT-4.1 mini is cheaper at $0.40 input / $1.60 output per million tokens (official OpenAI API price). QwQ 32B costs $0.66 input / $1.00 output per million tokens (median across 1 API provider); Mistral Medium 3 costs $0.40 input / $2.00 output per million tokens (official Mistral 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 $0.745 for QwQ 32B (1.1× as much) and $0.80 for Mistral Medium 3 (1.1× as much).
Which scores higher on benchmarks?
QwQ 32B scores higher on the Capabilities Index (ECI): QwQ 32B 137.6 (#109 of 148), GPT-4.1 mini 135.0 (#115 of 148) and Mistral Medium 3 134.1 (#117 of 148). The confidence ranges of the top two overlap (133.1–141.7 vs 131.2–136.6), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-4.1 mini 65.9%, QwQ 32B 65.3%, Mistral Medium 3 59.5%; OTIS Mock AIME 2024–2025 — QwQ 32B 59.2%, GPT-4.1 mini 44.7%, Mistral Medium 3 32.2%.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-4.1 mini, QwQ 32B and Mistral Medium 3 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. 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 QwQ 32B and 131,072 for Mistral Medium 3. Maximum output per response: GPT-4.1 mini up to 32,768, QwQ 32B up to 8,192, Mistral Medium 3 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
GPT-4.1 mini accepts text, images and PDFs; QwQ 32B accepts text; Mistral Medium 3 accepts text and images. GPT-4.1 mini 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 mini and Mistral Medium 3 is proprietary.
Which is newer?
Mistral Medium 3 is the newest, released May 7, 2025. GPT-4.1 mini came out Apr 14, 2025; QwQ 32B came out Mar 5, 2025. Knowledge cutoff: GPT-4.1 mini Apr 2024, QwQ 32B Apr 2024, Mistral Medium 3 May 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.