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Comparison · 2 models · Updated Oct 4, 2026

Mistral Small 4 vs Trinity Large Thinking

Mistral Small 4 comes out ahead, 64 to 55 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Mistral AI

    Mistral Small 4

    Released Mar 16, 2026

    64/100
    • ECI—
    • Price$0.15 / $0.60
    • Context256K
    Full specs Remove Mistral Small 4

  2. Arcee AI

    Trinity Large Thinking

    Released Apr 1, 2026Beta

    55/100
    • ECI—
    • Price$0.25 / $0.80
    • Context524K
    Full specs Remove Trinity Large Thinking

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Mistral Small 4 is our pick

Mistral Small 4 is the better all-round choice, scoring 64/100 against Trinity Large Thinking (55). It leads on price and inputs & features. Trinity Large Thinking wins 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 priceMistral Small 4Mistral Small 4 $0.263 · Trinity Large Thinking $0.388 per 1M tokens (3:1 blend)
  • Longest contextTrinity Large ThinkingTrinity Large Thinking 524,288 · Mistral Small 4 256,000 tokens
  • Widest inputsMistral Small 4Mistral Small 4: Text, Images · Trinity Large Thinking: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightMistral Small 4Trinity Large Thinking
Price50%7769
Inputs & features30%6035
Context window20%3649
Overall100%64/10055/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Mistral Small 4 vs Trinity Large Thinking specifications side by side
SpecificationMistral Small 4Mistral AITrinity Large ThinkingArcee AI
Capability
Capabilities Index (ECI)——
ECI rank——
Price per million tokens
Input$0.15 (best)$0.25
Output$0.60 (best)$0.80
Cached input$0.015 (best)$0.06
Blended (3:1)$0.263 (best)$0.388
Long-context rateSame rateSame rate
Price sourceOfficial Mistral APIOfficial Arcee API
Limits
Context window256,000 tokens524,288 tokens (best)
Max output256,000 tokens262,144 tokens (best)
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningYeshighYes
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpenOpenMDW-1.1
API model IDmistral-small-2603trinity-large-thinking
API providers16 (best)6
ReleasedMar 16, 2026Apr 1, 2026
Knowledge cutoffJun 2025—
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • Mistral Small 4$2.70
  • Trinity Large Thinking$4.10
04 — Questions

Which should you choose?

Which is better: Mistral Small 4 or Trinity Large Thinking?

Mistral Small 4 is the better all-round choice, scoring 64/100 against Trinity Large Thinking (55). It leads on price and inputs & features. Trinity Large Thinking wins 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, Mistral Small 4 or Trinity Large Thinking?

Mistral Small 4 is cheaper at $0.15 input / $0.60 output per million tokens (official Mistral 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 $0.263 per million tokens for Mistral Small 4 versus $0.388 for Trinity Large Thinking (1.5× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Mistral Small 4 has not been scored yet and Trinity Large Thinking has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Small 4 and Trinity Large Thinking 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 256,000 for Mistral Small 4. Maximum output per response: Mistral Small 4 up to 256,000, Trinity Large Thinking up to 262,144 tokens.

Which can read images, PDFs, audio or video?

Mistral Small 4 accepts text and images; Trinity Large Thinking accepts text. Mistral Small 4 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?

Trinity Large Thinking is the newest, released Apr 1, 2026. Mistral Small 4 came out Mar 16, 2026. Knowledge cutoff: Mistral Small 4 Jun 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.

05 — Keep comparing

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