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Comparison · 2 models · Updated Nov 2, 2026

Perceptron Mk1 vs Trinity Large Thinking

Trinity Large Thinking comes out ahead, 53 to 45 on our weighted score, and it is the cheaper option too.

  1. Perceptron

    Perceptron Mk1

    Released May 12, 2026

    45/100
    • ECI—
    • Price$0.15 / $1.50
    • Context33K
    Full specs Remove Perceptron Mk1
  2. Our pick

    Arcee AI

    Trinity Large Thinking

    Released Apr 1, 2026Beta

    53/100
    • 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

Trinity Large Thinking is our pick

Trinity Large Thinking is the better all-round choice, scoring 53/100 against Perceptron Mk1 (45). It leads on price and context window. Perceptron Mk1 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 · Perceptron Mk1 $0.487 per 1M tokens (3:1 blend)
  • Longest contextTrinity Large ThinkingTrinity Large Thinking 524,288 · Perceptron Mk1 32,768 tokens
  • Widest inputsPerceptron Mk1Perceptron Mk1: Text, Images, Video · Trinity Large Thinking: Text
  • Self-hostingTrinity Large ThinkingPublishes downloadable weights (OpenMDW-1.1)
How the score is built
MeasureWeightPerceptron Mk1Trinity Large Thinking
Price50%6266
Inputs & features30%4535
Context window20%049
Overall100%45/10053/100

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.

Perceptron Mk1 vs Trinity Large Thinking specifications side by side
SpecificationPerceptron Mk1PerceptronTrinity Large ThinkingArcee AI
Capability
Capabilities Index (ECI)——
ECI rank——
Price per million tokens
Input$0.15 (best)$0.25
Output$1.50$0.80 (best)
Cached input—$0.06
Blended (3:1)$0.487$0.388 (best)
Long-context rateSame rateSame rate
Price sourceMedian of 3 providersOfficial Arcee API
Limits
Context window32,768 tokens524,288 tokens (best)
Max output8,192 tokens262,144 tokens (best)
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoYesNo
ReasoningYesYes
Tool callingNoYes
Structured outputNoNo
Availability
WeightsProprietaryOpenOpenMDW-1.1
API model ID—trinity-large-thinking
API providers33
ReleasedMay 12, 2026Apr 1, 2026
Knowledge cutoff——
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.

  • Perceptron Mk1$4.50
  • Trinity Large Thinking$4.10
04 — Questions

Which should you choose?

Which is better: Perceptron Mk1 or Trinity Large Thinking?

Trinity Large Thinking is the better all-round choice, scoring 53/100 against Perceptron Mk1 (45). It leads on price and context window. Perceptron Mk1 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, Perceptron Mk1 or Trinity Large Thinking?

Trinity Large Thinking is cheaper at $0.25 input / $0.80 output per million tokens (official Arcee API price). Perceptron Mk1 costs $0.15 input / $1.50 output per million tokens (median across 3 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 $0.487 for Perceptron Mk1 (1.3× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Perceptron Mk1 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 Perceptron Mk1 and Trinity Large Thinking yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Perceptron Mk1 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 32,768 for Perceptron Mk1. Maximum output per response: Perceptron Mk1 up to 8,192, Trinity Large Thinking up to 262,144 tokens.

Which can read images, PDFs, audio or video?

Perceptron Mk1 accepts text, images and video; Trinity Large Thinking accepts text. Perceptron Mk1 handles the widest range of inputs.

Are any of these open source?

Trinity Large Thinking publishes its weights (OpenMDW-1.1) and can be self-hosted; Perceptron Mk1 is proprietary.

Which is newer?

Perceptron Mk1 is the newest, released May 12, 2026. Trinity Large Thinking came out Apr 1, 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 Nov 2, 2026.

05 — Keep comparing

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