Cohere: North Mini Code
cohere/north-mini-code:free
Access North Mini Code from Cohere using Puter.js AI API.
Get Started// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "cohere/north-mini-code:free"
}).then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms", {
model: "cohere/north-mini-code:free"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
# pip install openai
from openai import OpenAI
client = OpenAI(
base_url="https://api.puter.com/puterai/openai/v1/",
api_key="YOUR_PUTER_AUTH_TOKEN",
)
response = client.chat.completions.create(
model="cohere/north-mini-code:free",
messages=[
{"role": "user", "content": "Explain quantum computing in simple terms"}
],
)
print(response.choices[0].message.content)
curl https://api.puter.com/puterai/openai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_PUTER_AUTH_TOKEN" \
-d '{
"model": "cohere/north-mini-code:free",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Cohere North Mini Code is an open-weight agentic coding model from Cohere Labs, built on a sparse Mixture-of-Experts architecture with 30B total parameters and 3B active per token.
It is optimized for code generation, agentic software engineering workflows — including sub-agent orchestration, multi-file analysis, and code review — and real terminal tasks. On the Artificial Analysis Coding Index it scores 33.4, outperforming open-source models up to 4x its size. It delivers 2.8x higher throughput and 30% lower inter-token latency than Devstral Small 2.
With a 256K context window and 64K max output, it suits developers building AI coding agents or automated engineering pipelines. Released under Apache 2.0.
Context Window 256K
tokens
Max Output 64K
tokens
Input Cost $0
per million tokens
Output Cost $0
per million tokens
Release Date Jun 17, 2026
Model Playground
Try North Mini Code instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
More AI Models From Cohere
Command A
Command A is Cohere's flagship enterprise language model with 111 billion parameters and a 256K token context window, released in March 2025. Built for complex agentic workflows, it leads on tool-use benchmarks including BFCL-v3 and Tau-bench, and performs on par with GPT-4o on MMLU and SQL tasks. It is particularly strong at multi-step tool calling — including knowing when not to invoke a tool, a critical quality for production agents. Supporting 23 languages with 150% higher throughput than Command R+, it's a strong choice for developers building RAG pipelines, autonomous agents, or multilingual enterprise applications.
ChatCommand R7B (12-2024)
Command R7B is Cohere's smallest and fastest model in the R series, with 7 billion parameters and a 128K token context window. Despite its compact size, it ranked first among similarly-sized open-weights models on the HuggingFace Open LLM Leaderboard, leading across IFEval, BBH, GPQA, MuSR, and MMLU. It supports native tool use, multi-step agentic workflows, and RAG across 23 languages, with particular strength in code tasks including SQL and code translation. For API developers, it's the best option when latency and cost are priorities and a full-scale model isn't required.
ChatCommand R (08-2024)
Command R 08-2024 is a 32-billion-parameter generative language model from Cohere, optimized for complex reasoning, retrieval-augmented generation, multilingual tasks, and tool use across a 128K token context window. Compared to its predecessor, this version delivers approximately 50% higher throughput and 20% lower latency while showing competitive performance on math, code, and reasoning tasks. It supports 23 languages. For API developers, it is a practical mid-tier option that balances capability and cost — well-suited for question answering, summarization, and RAG-based applications.
Frequently Asked Questions
You can access North Mini Code by Cohere through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add North Mini Code to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price per 1M tokens | |
|---|---|
| Input | $0 |
| Output | $0 |
North Mini Code was created by Cohere and released on Jun 17, 2026.
North Mini Code supports a context window of 256K tokens. For reference, that is roughly equivalent to 512 pages of text.
North Mini Code can generate up to 64K tokens in a single response.
Yes — the North Mini Code API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
Get started with Puter.js
Add North Mini Code to your app without worrying about API keys or setup.
Read the Docs View Tutorials