Trinity Large Thinking vs MiMo-V2.5
MiMo-V2.5 comes out ahead, 79 to 55 on our weighted score, and it is the cheaper option too.
Arcee AITrinity Large Thinking
55/100- ECI—
- Price$0.25 / $0.80
- Context524K
- Our pick
XiaomiMiMo-V2.5
79/100- ECI—
- Price$0.14 / $0.28
- Context1.05M
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Make it a three-way comparison.
MiMo-V2.5 is our pick
MiMo-V2.5 is the better all-round choice, scoring 79/100 against Trinity Large Thinking (55). 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 priceMiMo-V2.5MiMo-V2.5 $0.175 · Trinity Large Thinking $0.388 per 1M tokens (3:1 blend)
- Longest contextMiMo-V2.5MiMo-V2.5 1,048,576 · Trinity Large Thinking 524,288 tokens
- Widest inputsMiMo-V2.5Trinity Large Thinking: Text · MiMo-V2.5: Text, Images, Audio, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Trinity Large Thinking | MiMo-V2.5 |
|---|---|---|---|
| Price | 50% | 69 | 86 |
| Inputs & features | 30% | 35 | 80 |
| Context window | 20% | 49 | 61 |
| Overall | 100% | 55/100 | 79/100 |
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 | Trinity Large ThinkingArcee AI | MiMo-V2.5Xiaomi |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.25 | $0.14 (best) |
| Output | $0.80 | $0.28 (best) |
| Cached input | $0.06 | $0.0028 (best) |
| Blended (3:1) | $0.388 | $0.175 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Arcee API | Official Xiaomi API |
| Limits | ||
| Context window | 524,288 tokens | 1,048,576 tokens (best) |
| Max output | 262,144 tokens (best) | 131,072 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | Yes |
| Video | No | Yes |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | OpenOpenMDW-1.1 | Open |
| API model ID | trinity-large-thinking | mimo-v2.5 |
| API providers | 6 | 21 (best) |
| Released | Apr 1, 2026 | Apr 22, 2026 |
| Knowledge cutoff | — | Dec 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Trinity Large Thinking$4.10
- MiMo-V2.5$1.96
Which should you choose?
Which is better: Trinity Large Thinking or MiMo-V2.5?
MiMo-V2.5 is the better all-round choice, scoring 79/100 against Trinity Large Thinking (55). 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, Trinity Large Thinking or MiMo-V2.5?
MiMo-V2.5 is cheaper at $0.14 input / $0.28 output per million tokens (official Xiaomi API price). Trinity Large Thinking costs $0.25 input / $0.80 output per million tokens (official Arcee API price). At a typical mix of three input tokens to one output token, that is $0.175 per million tokens for MiMo-V2.5 versus $0.388 for Trinity Large Thinking (2.2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Trinity Large Thinking has not been scored yet and MiMo-V2.5 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Trinity Large Thinking and MiMo-V2.5 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?
MiMo-V2.5 has the largest context window at 1,048,576 tokens, against 524,288 for Trinity Large Thinking. Maximum output per response: Trinity Large Thinking up to 262,144, MiMo-V2.5 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Trinity Large Thinking accepts text; MiMo-V2.5 accepts text, images, audio and video. MiMo-V2.5 handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights (OpenMDW-1.1), so you can self-host them.
Which is newer?
MiMo-V2.5 is the newest, released Apr 22, 2026. Trinity Large Thinking came out Apr 1, 2026. Knowledge cutoff: MiMo-V2.5 Dec 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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