GPT-4.1 mini vs Qwen3 14B vs Mistral Medium 3
GPT-4.1 mini comes out ahead, 60 to 54 and 53 on our weighted score, though Qwen3 14B is 13% cheaper per token.
- Our pick
OpenAI
GPT-4.1 mini
60/100- ECI135.0
- Price$0.40 / $1.60
- Context1.05M
Alibaba (Qwen)
Qwen3 14B
54/100- ECI138.2
- Price$0.35 / $1.40
- 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 Qwen3 14B (54) and Mistral Medium 3 (53). It leads on inputs & features and context window. Qwen3 14B wins on capability and price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3 14BCapabilities Index (ECI): Qwen3 14B 138.2 · GPT-4.1 mini 135.0 · Mistral Medium 3 134.1
- Lowest priceQwen3 14BQwen3 14B $0.613 · GPT-4.1 mini $0.70 · Mistral Medium 3 $0.80 per 1M tokens (3:1 blend)
- Longest contextGPT-4.1 miniGPT-4.1 mini 1,047,576 · Qwen3 14B 131,072 · Mistral Medium 3 131,072 tokens
- Widest inputsGPT-4.1 miniGPT-4.1 mini: Text, Images, PDFs · Qwen3 14B: Text · Mistral Medium 3: Text, Images
- Self-hostingQwen3 14BPublishes downloadable weights
| Measure | Weight | GPT-4.1 mini | Qwen3 14B | Mistral Medium 3 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 59 | 63 | 58 |
| Price | 25% | 57 | 60 | 54 |
| Inputs & features | 15% | 70 | 35 | 50 |
| Context window | 10% | 61 | 24 | 24 |
| Overall | 100% | 60/100 | 54/100 | 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 | 138.2 (best) | 134.1 |
| ECI rank | #115 of 148 | #107 of 148 (best) | #117 of 148 |
| GPQA DiamondGraduate-level science questions | 65.9% (best) | 63.8% | 59.5% |
| FrontierMath Tiers 1–3Research-level mathematics | 6.7% | — | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 44.7% | 66.4% (best) | 32.2% |
| SimpleQA VerifiedShort factual questions | 12.7% | — | — |
| Price per million tokens | |||
| Input | $0.40 | $0.35 (best) | $0.40 |
| Output | $1.60 | $1.40 (best) | $2.00 |
| Cached input | $0.10 | — | — |
| Blended (3:1) | $0.70 | $0.613 (best) | $0.80 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Official Alibaba API | 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 | qwen3-14b | mistral-medium-2505 |
| API providers | 24 (best) | 1 | 5 |
| Released | Apr 14, 2025 | Apr 29, 2025 | May 7, 2025 |
| Knowledge cutoff | Apr 2024 | Apr 2025 | 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
Qwen3 14B$6.30
Mistral Medium 3$8.00
Which should you choose?
Which is better: GPT-4.1 mini, Qwen3 14B or Mistral Medium 3?
GPT-4.1 mini is the better all-round choice, scoring 60/100 against Qwen3 14B (54) and Mistral Medium 3 (53). It leads on inputs & features and context window. Qwen3 14B wins on capability and price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GPT-4.1 mini, Qwen3 14B or Mistral Medium 3?
Qwen3 14B is cheaper at $0.35 input / $1.40 output per million tokens (official Alibaba API price). GPT-4.1 mini costs $0.40 input / $1.60 output per million tokens (official OpenAI API price); 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 $0.613 per million tokens for Qwen3 14B versus $0.70 for GPT-4.1 mini (1.1× as much) and $0.80 for Mistral Medium 3 (1.3× as much).
Which scores higher on benchmarks?
Qwen3 14B scores higher on the Capabilities Index (ECI): Qwen3 14B 138.2 (#107 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 (133.5–140.1 vs 131.2–136.6), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-4.1 mini 65.9%, Qwen3 14B 63.8%, Mistral Medium 3 59.5%; OTIS Mock AIME 2024–2025 — Qwen3 14B 66.4%, 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, Qwen3 14B and Mistral Medium 3 yet, so there is no like-for-like coding score. On overall capability, Qwen3 14B 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 14B and 131,072 for Mistral Medium 3. Maximum output per response: GPT-4.1 mini up to 32,768, Qwen3 14B 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; Qwen3 14B 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?
Qwen3 14B 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. Qwen3 14B came out Apr 29, 2025; GPT-4.1 mini came out Apr 14, 2025. Knowledge cutoff: GPT-4.1 mini Apr 2024, Qwen3 14B Apr 2025, 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.