MiniMax-M2 Her vs MiniMax-M2.5
MiniMax-M2.5 comes out ahead, 48 to 45 on our weighted score.
MiniMax
MiniMax-M2 Her
45/100- ECI—
- Price$0.30 / $1.20
- Context66K
- Our pick
MiniMax
MiniMax-M2.5
48/100- ECI146.7
- Price$0.30 / $1.20
- Context205K
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Make it a three-way comparison.
MiniMax-M2.5 is our pick
MiniMax-M2.5 is the better all-round choice, scoring 48/100 against MiniMax-M2 Her (45). It leads on context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceSame priceMiniMax-M2 Her $0.525 · MiniMax-M2.5 $0.525 per 1M tokens (3:1 blend)
- Longest contextMiniMax-M2.5MiniMax-M2.5 204,800 · MiniMax-M2 Her 65,536 tokens
- Widest inputsSame inputsMiniMax-M2 Her: Text · MiniMax-M2.5: Text
- Self-hostingMiniMax-M2.5Publishes downloadable weights
| Measure | Weight | MiniMax-M2 Her | MiniMax-M2.5 |
|---|---|---|---|
| Price | 50% | 63 | 63 |
| Inputs & features | 30% | 35 | 35 |
| Context window | 20% | 12 | 32 |
| Overall | 100% | 45/100 | 48/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | ||
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | 146.7 |
| ECI rank | — | #66 of 148 |
| Price per million tokens | ||
| Input | $0.30 | $0.30 |
| Output | $1.20 | $1.20 |
| Cached input | — | $0.03 |
| Blended (3:1) | $0.525 | $0.525 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 4 providers | Official MiniMax (minimax.io) API |
| Limits | ||
| Context window | 65,536 tokens | 204,800 tokens (best) |
| Max output | 2,048 tokens | 131,072 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Proprietary | Open |
| API model ID | — | MiniMax-M2.5 |
| API providers | 4 | 21 (best) |
| Released | Jan 23, 2026 | Feb 12, 2026 |
| Knowledge cutoff | — | — |
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 Her$5.40
MiniMax-M2.5$5.40
Which should you choose?
Which is better: MiniMax-M2 Her or MiniMax-M2.5?
MiniMax-M2.5 is the better all-round choice, scoring 48/100 against MiniMax-M2 Her (45). It leads on context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, MiniMax-M2 Her or MiniMax-M2.5?
MiniMax-M2 Her and MiniMax-M2.5 cost the same: $0.30 input / $1.20 output per million tokens.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. MiniMax-M2 Her has not been scored yet and MiniMax-M2.5 has an ECI of 146.7.
Which is better for coding?
There are no published SWE-bench Verified results for MiniMax-M2 Her and MiniMax-M2.5 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
MiniMax-M2.5 has the largest context window at 204,800 tokens, against 65,536 for MiniMax-M2 Her. Maximum output per response: MiniMax-M2 Her up to 2,048, MiniMax-M2.5 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
MiniMax-M2 Her accepts text; MiniMax-M2.5 accepts text. They handle the same number of input types.
Are any of these open source?
MiniMax-M2.5 publishes its weights and can be self-hosted; MiniMax-M2 Her is proprietary.
Which is newer?
MiniMax-M2.5 is the newest, released Feb 12, 2026. MiniMax-M2 Her came out Jan 23, 2026.
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.