MiniMax-M2.7 vs GPT-4.1 mini
Too close to call on our weighted score (MiniMax-M2.7 61, GPT-4.1 mini 60). The right pick depends on what you value most.
MiniMaxMiniMax-M2.7
61/100- ECI145.9
- Price$0.30 / $1.20
- Context205K
OpenAIGPT-4.1 mini
60/100- ECI135.0
- Price$0.40 / $1.60
- Context1.05M
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within a point (MiniMax-M2.7 61/100, GPT-4.1 mini 60/100), so choose by what matters most for your work: MiniMax-M2.7 for raw capability and GPT-4.1 mini for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMiniMax-M2.7Capabilities Index (ECI): MiniMax-M2.7 145.9 · GPT-4.1 mini 135.0
- Lowest priceMiniMax-M2.7MiniMax-M2.7 $0.525 · GPT-4.1 mini $0.70 per 1M tokens (3:1 blend)
- Longest contextGPT-4.1 miniGPT-4.1 mini 1,047,576 · MiniMax-M2.7 204,800 tokens
- Widest inputsGPT-4.1 miniMiniMax-M2.7: Text · GPT-4.1 mini: Text, Images, PDFs
- Self-hostingMiniMax-M2.7Publishes downloadable weights
| Measure | Weight | MiniMax-M2.7 | GPT-4.1 mini |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 73 | 59 |
| Price | 25% | 63 | 57 |
| Inputs & features | 15% | 35 | 70 |
| Context window | 10% | 32 | 61 |
| Overall | 100% | 61/100 | 60/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | MiniMax-M2.7MiniMax | GPT-4.1 miniOpenAI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 145.9 (best) | 135.0 |
| ECI rank | #73 of 148 (best) | #115 of 148 |
| GPQA DiamondGraduate-level science questions | — | 65.9% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 6.7% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 44.7% |
| SimpleQA VerifiedShort factual questions | — | 12.7% |
| Price per million tokens | ||
| Input | $0.30 (best) | $0.40 |
| Output | $1.20 (best) | $1.60 |
| Cached input | $0.06 (best) | $0.10 |
| Blended (3:1) | $0.525 (best) | $0.70 |
| Long-context rate | Same rate | Same rate |
| Price source | Official MiniMax (minimax.io) API | Official OpenAI API |
| Limits | ||
| Context window | 204,800 tokens | 1,047,576 tokens (best) |
| Max output | 131,072 tokens (best) | 32,768 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | Yes |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | No |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | Open | Proprietary |
| API model ID | MiniMax-M2.7 | gpt-4.1-mini |
| API providers | 29 (best) | 24 |
| Released | Mar 18, 2026 | Apr 14, 2025 |
| Knowledge cutoff | — | Apr 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- MiniMax-M2.7$5.40
- GPT-4.1 mini$7.20
Which should you choose?
Which is better: MiniMax-M2.7 or GPT-4.1 mini?
It is close. Our weighted score puts them within a point (MiniMax-M2.7 61/100, GPT-4.1 mini 60/100), so choose by what matters most for your work: MiniMax-M2.7 for raw capability and GPT-4.1 mini for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, MiniMax-M2.7 or GPT-4.1 mini?
MiniMax-M2.7 is cheaper at $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) API price). GPT-4.1 mini costs $0.40 input / $1.60 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.525 per million tokens for MiniMax-M2.7 versus $0.70 for GPT-4.1 mini (1.3× as much).
Which scores higher on benchmarks?
MiniMax-M2.7 scores higher on the Capabilities Index (ECI): MiniMax-M2.7 145.9 (#73 of 148) and GPT-4.1 mini 135.0 (#115 of 148). Their confidence ranges do not overlap (138.2–148.0 vs 131.2–136.6), so the gap is a real one.
Which is better for coding?
There are no published SWE-bench Verified results for MiniMax-M2.7 and GPT-4.1 mini yet, so there is no like-for-like coding score. On overall capability, MiniMax-M2.7 leads, which tends to carry over to coding, but test on your own codebase. Both 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 204,800 for MiniMax-M2.7. Maximum output per response: MiniMax-M2.7 up to 131,072, GPT-4.1 mini up to 32,768 tokens.
Which can read images, PDFs, audio or video?
MiniMax-M2.7 accepts text; GPT-4.1 mini accepts text, images and PDFs. GPT-4.1 mini handles the widest range of inputs.
Are any of these open source?
MiniMax-M2.7 publishes its weights and can be self-hosted; GPT-4.1 mini is proprietary.
Which is newer?
MiniMax-M2.7 is the newest, released Mar 18, 2026. GPT-4.1 mini came out Apr 14, 2025. Knowledge cutoff: GPT-4.1 mini Apr 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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