Cohere·#233 of 352 on the current board·cheaper than #232 Llama 4 Scout
North Mini Code is a language model from Cohere. It ranks #233 of 352 on ModelCap's current board, with an Index score of 31.0, modeled from public metadata, not measured. Its score range of 5.1–56.8 spans positions #98–#347. It is listed free of charge from one provider. It reads up to 256K tokens of context, and its weights are openly downloadable.
Figures as of 6 Nov 2026, 20:32 UTC · download the public dataset · methodology
Structured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. Rows marked as used were laddered against independently measured peers inside the launch-card channel of this model's modeled placement, with the replay-measured optimism haircut applied; the others played no part.
No general-family board lists this model yet. Its point estimate is the precision-weighted mean of every channel that spoke for it; each channel’s share is the weight it carried. Independent measurements replace this placement as boards list the model.
BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.
These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.
The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.
Experimental estimate. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.
Not yet published: the base model it derives from, admitted benchmark results, results across several capability areas, results from more than one source, a confident match to its benchmark entries, pinned evaluation dataset versions.
A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.
Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.
This model is visible because it is available in the live catalogue, but it has no trustworthy community result yet. ModelCap does not infer a quality score from price, features, or market activity.
OpenRouter weekly popularity across the full model catalogue.
Independent providers versus the model's open or closed cohort, weighted by uptime.
Hugging Face 30-day downloads for open models; neutral for closed models.
Time since first public availability, on a six-month half-life.
cohere/north-mini-codeOpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata
Open weights. Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI.
Models within 3 places of #233 on the ModelCap Index.
The same publisher's other current models with a public Index position.
North Mini Code holds ModelCap Index position #233 of 352 ranked language models as of 6 November 2026, with an Index score of 31.0 (interval 5.1–56.8); evidence: modeled · prior. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.
North Mini Code is listed at Free per 1M input tokens and Free per 1M output tokens as of 6 November 2026. Prices come from the OpenRouter catalogue and re-observe on every refresh; at least one provider lists a free tier. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply Free total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.
North Mini Code has a published context window of 256K tokens (256,000). The snapshot lists a 64,000 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.
Open weights (apache-2.0). Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI. The repository is CohereLabs/North-Mini-Code-1.0 on Hugging Face.
One provider serves North Mini Code through OpenRouter as of 6 November 2026: Cohere. Each provider's price, context limit, quantization and measured uptime are in the providers table above.
North Mini Code has published results on 1 public board tracked by ModelCap as of 6 November 2026: AA Intelligence Index 3.4 (#97 of 98). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.
North Mini Code first appeared in the catalogue on 17 Jun 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.