North Mini Code
CohereLabsapache-2.0text

North Mini Code

Updated Jul 13, 2026
Parameters
30.5B
Context
500,000
License
apache-2.0
Updated
Jul 13, 2026

Intelligence benchmarks

Artificial Analysis indexes - compared with the best open and proprietary models

Intelligence

20.6

AA Index

Coding

36.5

AA Index

Intelligence Index - North Mini Code vs. the field

Best open-weight models (you can run locally) and leading proprietary models for context.

Claude Fable 5 (with fallback)
59.9
closed
GPT-5.6 Sol (max)
58.9
closed
Claude Opus 4.8 (max)
55.7
closed
GPT-5.6 Terra (max)
55
closed
GPT-5.5 (xhigh)
54.8
closed
GLM-5.2
51.1
open
MiniMax-M3
44.4
open
North Mini Code
20.6
open

Coding Index comparison

GPT-5.6 Sol (xhigh)
78.3
closed
GPT-5.6 Terra (max)
76.7
closed
Claude Fable 5 (with fallback)
76.5
closed
GPT-5.5 (xhigh)
74.9
closed
Claude Opus 4.8 (max)
74.3
closed
GLM-5.2
68.8
open
Kimi K2.6
61.8
open
North Mini Code
36.5
open

Benchmark data from Artificial Analysis · updated 2026-07-13.

Standard benchmarks

Performance across standard evaluations

BenchmarkScore
GPQA75.7

Will it run on your hardware?

Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest

Runs on your 24 GB - best at Q4_K_M
1 of 4 quantizations fit North Mini Code with real runtime overhead.
fits tight too big

Need an exact figure for your context length? Use the VRAM calculator.

Run it locally

Copy-paste - running in under a minute

vLLMOpenAI-compatible API
vllm serve CohereLabs/North-Mini-Code-1.0-fp8

New to this? Start with Ollama · serve to many users with vLLM.

Deep dive

Notes, sources, and the full write-up

North Mini Code is a 30.5B-parameter apache-2.0 model from Cohere. It scores 20.6 on the Artificial Analysis Intelligence Index (coding 36.5). At Q4_K_M it needs roughly 18 GB of VRAM, placing it in the 12–24 GB GPU hardware tier.

Benchmarks

Artificial Analysis Intelligence Index - North Mini Code vs. leading closed models:

ModelIntelligenceCodingGPQA
North Mini Code20.636.575.7
Claude Fable 5 (with fallback)59.976.592.6
GPT-5.6 Sol (max)58.977.494.1
Claude Opus 4.8 (max)55.774.392
GPT-5.6 Terra (max)5576.792.5
GPT-5.5 (xhigh)54.874.993.5

Source: Artificial Analysis (2026-07-11).

Popularity

North Mini Code has 42,833 downloads in the last month on HuggingFace and 30 likes.

Frequently asked

Quick answers to common questions

How much VRAM does North Mini Code need?

North Mini Code with 30.5B parameters needs approximately 18 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.

Is North Mini Code better than other CohereLabs models?

North Mini Code has 30.5B parameters with 500,000 context - a strong choice for general use.

What license is North Mini Code under?

North Mini Code is released under the apache-2.0 license, making it suitable for most commercial and personal projects.

What hardware runs North Mini Code well?

With 30.5B parameters, North Mini Code requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.

What is the best quantization for North Mini Code?

Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~22 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.

How long can North Mini Code's context window handle?

North Mini Code supports a 500,000-token context window - enough for very long documents, codebases, or multi-turn conversations. Real-world usable context may vary by implementation.

What models compete with North Mini Code?

North Mini Code competes with other 15B–46B. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.

Nearby options

Similar models and compatible hardware by spec

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