MiniMax-M2.5-highspeed vs Gemma 4 31B IT vs DeepSeek OCR 2
Gemma 4 31B IT comes out ahead, 70 to 41 and 32 on our weighted score, and it is the cheaper option too.
MiniMaxMiniMax-M2.5-highspeed
41/100- ECI—
- Price$0.60 / $2.40
- Context205K
- Our pick
GoogleGemma 4 31B IT
70/100- ECI142.8
- Price$0.14 / $0.40
- Context262K
DeepSeekDeepSeek OCR 2
32/100- ECI—
- Price$0.89 / $1.47
- Context8K
Gemma 4 31B IT is our pick
Gemma 4 31B IT is the better all-round choice, scoring 70/100 against MiniMax-M2.5-highspeed (41) and DeepSeek OCR 2 (32). It leads on price, inputs & features and 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 priceGemma 4 31B ITGemma 4 31B IT $0.205 · DeepSeek OCR 2 $1.03 · MiniMax-M2.5-highspeed $1.05 per 1M tokens (3:1 blend)
- Longest contextGemma 4 31B ITGemma 4 31B IT 262,144 · MiniMax-M2.5-highspeed 204,800 · DeepSeek OCR 2 8,192 tokens
- Widest inputsGemma 4 31B IT and DeepSeek OCR 2MiniMax-M2.5-highspeed: Text · Gemma 4 31B IT: Text, Images · DeepSeek OCR 2: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | MiniMax-M2.5-highspeed | Gemma 4 31B IT | DeepSeek OCR 2 |
|---|---|---|---|---|
| Price | 50% | 49 | 83 | 49 |
| Inputs & features | 30% | 35 | 70 | 25 |
| Context window | 20% | 32 | 37 | 0 |
| Overall | 100% | 41/100 | 70/100 | 32/100 |
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 | MiniMax-M2.5-highspeedMiniMax | Gemma 4 31B ITGoogle | DeepSeek OCR 2DeepSeek |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 142.8 | — |
| ECI rank | — | #86 of 148 | — |
| GPQA DiamondGraduate-level science questions | — | 75.8% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 73.3% | — |
| SimpleQA VerifiedShort factual questions | — | 10.4% | — |
| Price per million tokens | |||
| Input | $0.60 | $0.14 (best) | $0.89 |
| Output | $2.40 | $0.40 (best) | $1.47 |
| Cached input | $0.06 | — | — |
| Blended (3:1) | $1.05 | $0.205 (best) | $1.03 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official MiniMax (minimax.io) API | Median of 30 providers | Median of 1 providers |
| Limits | |||
| Context window | 204,800 tokens | 262,144 tokens (best) | 8,192 tokens |
| Max output | 131,072 tokens (best) | 32,768 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | No |
| Tool calling | Yes | Yes | No |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | MiniMax-M2.5-highspeed | gemma-4-31b-it | — |
| API providers | 7 | 38 (best) | 2 |
| Released | Feb 13, 2026 | Apr 2, 2026 | Jan 27, 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-M2.5-highspeed$10.80
- Gemma 4 31B IT$2.20
- DeepSeek OCR 2$11.83
Which should you choose?
Which is better: MiniMax-M2.5-highspeed, Gemma 4 31B IT or DeepSeek OCR 2?
Gemma 4 31B IT is the better all-round choice, scoring 70/100 against MiniMax-M2.5-highspeed (41) and DeepSeek OCR 2 (32). It leads on price, inputs & features and 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-M2.5-highspeed, Gemma 4 31B IT or DeepSeek OCR 2?
Gemma 4 31B IT is cheaper at $0.14 input / $0.40 output per million tokens (median across 30 API providers). DeepSeek OCR 2 costs $0.89 input / $1.47 output per million tokens (median across 1 API provider); MiniMax-M2.5-highspeed costs $0.60 input / $2.40 output per million tokens (official MiniMax (minimax.io) API price). At a typical mix of three input tokens to one output token, that is $0.205 per million tokens for Gemma 4 31B IT versus $1.03 for DeepSeek OCR 2 (5× as much) and $1.05 for MiniMax-M2.5-highspeed (5.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. MiniMax-M2.5-highspeed has not been scored yet, Gemma 4 31B IT has an ECI of 142.8 and DeepSeek OCR 2 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for MiniMax-M2.5-highspeed, Gemma 4 31B IT and DeepSeek OCR 2 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that DeepSeek OCR 2 does not support tool calling, which most coding agents need.
Which has the bigger context window?
Gemma 4 31B IT has the largest context window at 262,144 tokens, against 204,800 for MiniMax-M2.5-highspeed and 8,192 for DeepSeek OCR 2. Maximum output per response: MiniMax-M2.5-highspeed up to 131,072, Gemma 4 31B IT up to 32,768, DeepSeek OCR 2 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
MiniMax-M2.5-highspeed accepts text; Gemma 4 31B IT accepts text and images; DeepSeek OCR 2 accepts text and images. Gemma 4 31B IT handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights, so you can self-host them.
Which is newer?
Gemma 4 31B IT is the newest, released Apr 2, 2026. MiniMax-M2.5-highspeed came out Feb 13, 2026; DeepSeek OCR 2 came out Jan 27, 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.
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