North Mini Code

Tool callingStructured outputReasoning

Website

Cohere coding model for practical software engineering and agentic edits

Context: 256K
Released: 4mo ago
Parameters: —

Sources:models.dev

Benchmarks

DeepSWE is the primary coding benchmark where an exact model evaluation exists. Other sourced evaluations appear below; missing scores are not zero.

Not evaluated in DeepSWE 1.1 as of 2026-09-22. Results are only shown for exact model versions in the official dataset. Official leaderboard.

No benchmark results have been matched to this model yet.

Specifications

Developer: Cohere
Model family: —
Type: Language model
Predecessor: —
Successor: —
Released: June 9, 2026
Model ID: cohere/north-mini-code-1-0
Openness: Open weights
License: —
Parameters: —
Input modalities: text
Output modalities: text
Modality: text->text
Max output tokens: 64K
Knowledge cutoff: 2025-09-23
Hugging Face: —
Source freshness: Metadata synced Oct 8, 2026, 10:17 PM UTC

Additional source evidence

Source model: cohere/north-mini-code-1-0
Source family: north
Last updated: 2026-06-09
Knowledge cutoff: 2025-09-23
Model context: 256K
Model output limit: 64K
Open weights: Yes
File attachments: No
Reasoning: Yes
Tool calling: Yes
Structured output: Yes
Temperature control: Yes

Published benchmarks

Benchmark	Score	Evaluation details	Evidence
SWE-Bench Verified	67.6 · resolved	SWE-agent · 2026-06-09	Source
SWE-Bench Pro	40.2 · resolve rate	SWE-agent · 2026-06-09	Source
Artificial Analysis Intelligence Index	27.6 · index score	2026-06-09	Source
Artificial Analysis Coding Index	33.4 · index score	2026-06-09	Source
GDPval-AA	14 · win rate	2026-06-09	Source
τ²-Bench Telecom	37 · success rate	2026-06-09	Source

Complete source record (JSON)

{
  "id": "cohere/north-mini-code-1-0",
  "name": "North Mini Code",
  "description": "Cohere coding model for practical software engineering and agentic edits",
  "family": "north",
  "last_updated": "2026-06-09",
  "knowledge": "2025-09-23",
  "attachment": false,
  "reasoning": true,
  "tool_call": true,
  "structured_output": true,
  "temperature": true,
  "modalities": {
    "input": [
      "text"
    ],
    "output": [
      "text"
    ]
  },
  "limit": {
    "context": 256000,
    "output": 64000
  },
  "benchmarks": [
    {
      "name": "SWE-Bench Verified",
      "score": 67.6,
      "source": "https://huggingface.co/CohereLabs/North-Mini-Code-1.0",
      "metric": "resolved",
      "harness": "SWE-agent",
      "date": "2026-06-09"
    },
    {
      "name": "SWE-Bench Pro",
      "score": 40.2,
      "source": "https://huggingface.co/CohereLabs/North-Mini-Code-1.0",
      "metric": "resolve rate",
      "harness": "SWE-agent",
      "date": "2026-06-09"
    },
    {
      "name": "Artificial Analysis Intelligence Index",
      "score": 27.6,
      "source": "https://artificialanalysis.ai/articles/north-mini-code-cohere-s-small-coding-focused-moe-model",
      "metric": "index score",
      "date": "2026-06-09"
    },
    {
      "name": "Artificial Analysis Coding Index",
      "score": 33.4,
      "source": "https://artificialanalysis.ai/articles/north-mini-code-cohere-s-small-coding-focused-moe-model",
      "metric": "index score",
      "date": "2026-06-09"
    },
    {
      "name": "GDPval-AA",
      "score": 14,
      "source": "https://artificialanalysis.ai/articles/north-mini-code-cohere-s-small-coding-focused-moe-model",
      "metric": "win rate",
      "date": "2026-06-09"
    },
    {
      "name": "τ²-Bench Telecom",
      "score": 37,
      "source": "https://artificialanalysis.ai/articles/north-mini-code-cohere-s-small-coding-focused-moe-model",
      "metric": "success rate",
      "date": "2026-06-09"
    }
  ],
  "release_date": "2026-06-09",
  "open_weights": true
}

Infrastructure

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