Trinity Large Thinking vs Kimi K2.7 Code Highspeed
Trinity Large Thinking comes out ahead, 55 to 44 on our weighted score, and it is the cheaper option too.
- Our pick
Arcee AITrinity Large Thinking
55/100- ECI—
- Price$0.25 / $0.80
- Context524K
Moonshot AIKimi K2.7 Code Highspeed
44/100- ECI—
- Price$1.90 / $8.00
- Context262K
Add a model
Make it a three-way comparison.
Trinity Large Thinking is our pick
Trinity Large Thinking is the better all-round choice, scoring 55/100 against Kimi K2.7 Code Highspeed (44). It leads on price and context window. Kimi K2.7 Code Highspeed wins on inputs & features. 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 · Kimi K2.7 Code Highspeed $3.42 per 1M tokens (3:1 blend)
- Longest contextTrinity Large ThinkingTrinity Large Thinking 524,288 · Kimi K2.7 Code Highspeed 262,144 tokens
- Widest inputsKimi K2.7 Code HighspeedTrinity Large Thinking: Text · Kimi K2.7 Code Highspeed: Text, Images, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Trinity Large Thinking | Kimi K2.7 Code Highspeed |
|---|---|---|---|
| Price | 50% | 69 | 25 |
| Inputs & features | 30% | 35 | 80 |
| Context window | 20% | 49 | 37 |
| Overall | 100% | 55/100 | 44/100 |
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 | Kimi K2.7 Code HighspeedMoonshot AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.25 (best) | $1.90 |
| Output | $0.80 (best) | $8.00 |
| Cached input | $0.06 | — |
| Blended (3:1) | $0.388 (best) | $3.42 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Arcee API | Median of 11 providers |
| Limits | ||
| Context window | 524,288 tokens (best) | 262,144 tokens |
| Max output | 262,144 tokens | 262,144 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | Yes |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | OpenOpenMDW-1.1 | Open |
| API model ID | trinity-large-thinking | — |
| API providers | 6 | 11 (best) |
| Released | Apr 1, 2026 | Jun 12, 2026 |
| Knowledge cutoff | — | Jan 2025 |
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
- Kimi K2.7 Code Highspeed$35.00
Which should you choose?
Which is better: Trinity Large Thinking or Kimi K2.7 Code Highspeed?
Trinity Large Thinking is the better all-round choice, scoring 55/100 against Kimi K2.7 Code Highspeed (44). It leads on price and context window. Kimi K2.7 Code Highspeed wins on inputs & features. 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 Kimi K2.7 Code Highspeed?
Trinity Large Thinking is cheaper at $0.25 input / $0.80 output per million tokens (official Arcee API price). Kimi K2.7 Code Highspeed costs $1.90 input / $8.00 output per million tokens (median across 11 API providers). At a typical mix of three input tokens to one output token, that is $0.388 per million tokens for Trinity Large Thinking versus $3.42 for Kimi K2.7 Code Highspeed (8.8× 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 Kimi K2.7 Code Highspeed has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Trinity Large Thinking and Kimi K2.7 Code Highspeed 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?
Trinity Large Thinking has the largest context window at 524,288 tokens, against 262,144 for Kimi K2.7 Code Highspeed. Maximum output per response: Trinity Large Thinking up to 262,144, Kimi K2.7 Code Highspeed up to 262,144 tokens.
Which can read images, PDFs, audio or video?
Trinity Large Thinking accepts text; Kimi K2.7 Code Highspeed accepts text, images and video. Kimi K2.7 Code Highspeed 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?
Kimi K2.7 Code Highspeed is the newest, released Jun 12, 2026. Trinity Large Thinking came out Apr 1, 2026. Knowledge cutoff: Kimi K2.7 Code Highspeed Jan 2025.
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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