ZMIME
Comparison · 3 models · Updated Oct 4, 2026

North Mini Code vs Trinity Large Thinking vs Laguna M.1

Too close to call on our weighted score (North Mini Code 71, Laguna M.1 68, Trinity Large Thinking 55). The right pick depends on what you value most.

  1. Cohere

    North Mini Code

    Released Jun 9, 2026

    71/100
    • ECI—
    • PriceFree / Free
    • Context256K
  2. Arcee AI

    Trinity Large Thinking

    Released Apr 1, 2026Beta

    55/100
    • ECI—
    • Price$0.25 / $0.80
    • Context524K
  3. Poolside

    Laguna M.1

    Released Apr 28, 2026

    68/100
    • ECI—
    • PriceFree / Free
    • Context262K
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 3 points (North Mini Code 71/100, Laguna M.1 68/100, Trinity Large Thinking 55/100), so choose by what matters most for your work: North Mini Code on price and Trinity Large Thinking for long inputs. 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 priceNorth Mini Code and Laguna M.1North Mini Code Free · Laguna M.1 Free · Trinity Large Thinking $0.388 per 1M tokens (3:1 blend)
  • Longest contextTrinity Large ThinkingTrinity Large Thinking 524,288 · Laguna M.1 262,144 · North Mini Code 256,000 tokens
  • Widest inputsSame inputsNorth Mini Code: Text · Trinity Large Thinking: Text · Laguna M.1: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightNorth Mini CodeTrinity Large ThinkingLaguna M.1
Price50%10069100
Inputs & features30%453535
Context window20%364937
Overall100%71/10055/10068/100

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.

North Mini Code vs Trinity Large Thinking vs Laguna M.1 specifications side by side
SpecificationNorth Mini CodeCohereTrinity Large ThinkingArcee AILaguna M.1Poolside
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
InputFree (best)$0.25Free (best)
OutputFree (best)$0.80Free (best)
Cached input—$0.06—
Blended (3:1)Free (best)$0.388Free (best)
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Cohere APIOfficial Arcee APIOfficial Poolside API
Limits
Context window256,000 tokens524,288 tokens (best)262,144 tokens
Max output64,000 tokens262,144 tokens (best)32,768 tokens
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYeshighYesYes
Tool callingYesYesYes
Structured outputYesNoNo
Availability
WeightsOpenOpenOpenMDW-1.1Open
API model IDnorth-mini-code-1-0trinity-large-thinkingpoolside/laguna-m.1
API providers26 (best)2
ReleasedJun 9, 2026Apr 1, 2026Apr 28, 2026
Knowledge cutoffSep 23, 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.

  • North Mini CodeFree
  • Trinity Large Thinking$4.10
  • Laguna M.1Free
04 — Questions

Which should you choose?

Which is better: North Mini Code, Trinity Large Thinking or Laguna M.1?

It is close. Our weighted score puts them within 3 points (North Mini Code 71/100, Laguna M.1 68/100, Trinity Large Thinking 55/100), so choose by what matters most for your work: North Mini Code on price and Trinity Large Thinking for long inputs. 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, North Mini Code, Trinity Large Thinking or Laguna M.1?

North Mini Code is cheaper at Free input / Free output per million tokens (official Cohere API price). Laguna M.1 costs Free input / Free output per million tokens (official Poolside API price); Trinity Large Thinking costs $0.25 input / $0.80 output per million tokens (official Arcee API price). North Mini Code is listed as free.

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. North Mini Code has not been scored yet, Trinity Large Thinking has not been scored yet and Laguna M.1 has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for North Mini Code, Trinity Large Thinking and Laguna M.1 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three 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 Laguna M.1 and 256,000 for North Mini Code. Maximum output per response: North Mini Code up to 64,000, Trinity Large Thinking up to 262,144, Laguna M.1 up to 32,768 tokens.

Which can read images, PDFs, audio or video?

North Mini Code accepts text; Trinity Large Thinking accepts text; Laguna M.1 accepts text. They handle the same number of input types.

Are any of these open source?

Yes, all three publish their weights (OpenMDW-1.1), so you can self-host them.

Which is newer?

North Mini Code is the newest, released Jun 9, 2026. Laguna M.1 came out Apr 28, 2026; Trinity Large Thinking came out Apr 1, 2026. Knowledge cutoff: North Mini Code Sep 23, 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.