MiniMax-M2.5-highspeed vs Trinity Large Thinking vs DeepSeek OCR 2
Trinity Large Thinking comes out ahead, 55 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
Arcee AITrinity Large Thinking
55/100- ECI—
- Price$0.25 / $0.80
- Context524K
DeepSeekDeepSeek OCR 2
32/100- ECI—
- Price$0.89 / $1.47
- Context8K
Trinity Large Thinking is our pick
Trinity Large Thinking is the better all-round choice, scoring 55/100 against MiniMax-M2.5-highspeed (41) and DeepSeek OCR 2 (32). It leads on price 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 priceTrinity Large ThinkingTrinity Large Thinking $0.388 · DeepSeek OCR 2 $1.03 · MiniMax-M2.5-highspeed $1.05 per 1M tokens (3:1 blend)
- Longest contextTrinity Large ThinkingTrinity Large Thinking 524,288 · MiniMax-M2.5-highspeed 204,800 · DeepSeek OCR 2 8,192 tokens
- Widest inputsDeepSeek OCR 2MiniMax-M2.5-highspeed: Text · Trinity Large Thinking: Text · 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 | Trinity Large Thinking | DeepSeek OCR 2 |
|---|---|---|---|---|
| Price | 50% | 49 | 69 | 49 |
| Inputs & features | 30% | 35 | 35 | 25 |
| Context window | 20% | 32 | 49 | 0 |
| Overall | 100% | 41/100 | 55/100 | 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 | Trinity Large ThinkingArcee AI | DeepSeek OCR 2DeepSeek |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.60 | $0.25 (best) | $0.89 |
| Output | $2.40 | $0.80 (best) | $1.47 |
| Cached input | $0.06 | $0.06 | — |
| Blended (3:1) | $1.05 | $0.388 (best) | $1.03 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official MiniMax (minimax.io) API | Official Arcee API | Median of 1 providers |
| Limits | |||
| Context window | 204,800 tokens | 524,288 tokens (best) | 8,192 tokens |
| Max output | 131,072 tokens | 262,144 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | 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 | No | No |
| Availability | |||
| Weights | Open | OpenOpenMDW-1.1 | Open |
| API model ID | MiniMax-M2.5-highspeed | trinity-large-thinking | — |
| API providers | 7 (best) | 6 | 2 |
| Released | Feb 13, 2026 | Apr 1, 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
- Trinity Large Thinking$4.10
- DeepSeek OCR 2$11.83
Which should you choose?
Which is better: MiniMax-M2.5-highspeed, Trinity Large Thinking or DeepSeek OCR 2?
Trinity Large Thinking is the better all-round choice, scoring 55/100 against MiniMax-M2.5-highspeed (41) and DeepSeek OCR 2 (32). It leads on price 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, Trinity Large Thinking or DeepSeek OCR 2?
Trinity Large Thinking is cheaper at $0.25 input / $0.80 output per million tokens (official Arcee API price). 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 $0.388 per million tokens for Trinity Large Thinking versus $1.03 for DeepSeek OCR 2 (2.7× as much) and $1.05 for MiniMax-M2.5-highspeed (2.7× 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, Trinity Large Thinking has not been scored yet 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, Trinity Large Thinking 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?
Trinity Large Thinking has the largest context window at 524,288 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, Trinity Large Thinking up to 262,144, DeepSeek OCR 2 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
MiniMax-M2.5-highspeed accepts text; Trinity Large Thinking accepts text; DeepSeek OCR 2 accepts text and images. DeepSeek OCR 2 handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (OpenMDW-1.1), so you can self-host them.
Which is newer?
Trinity Large Thinking is the newest, released Apr 1, 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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