Cohere's North Mini Code: A 30B Open-Weight Coding Model That Runs on One H100

Cohere has mostly been known for retrieval, embeddings, and enterprise RAG. On June 9, 2026, it stepped onto coding-model turf for the first time. North Mini Code is the company's first agentic coding model, released with open weights under Apache 2.0 and sized so it fits on a single H100. For teams that want a capable coding model they can actually self-host, that combination is the headline.

This post sticks to what Cohere has published and what independent coverage has confirmed. Where a number is a vendor claim rather than an independently reproduced benchmark, it is flagged as such.

Published: June 17, 2026

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What North Mini Code Is

North Mini Code is a mixture-of-experts (MoE) model with 30B total parameters and 3B active per token. The MoE design is the whole point: you get the knowledge capacity of a 30B model while only paying the inference cost of routing through roughly 3B parameters on each forward pass. That is what keeps the deployment footprint small.

The specs Cohere lists:

• 30B total / 3B active parameters (MoE)
• 256K token context window
• 64K token maximum generation length
• Apache 2.0 license (open weights, commercial use permitted)
• Minimum hardware: 1x H100 at FP8 or 1x H100 at FP4

It is positioned as the first model in what Cohere calls its next generation, and it is aimed squarely at agentic software engineering - code generation, sub-agent orchestration, architecture mapping, code review, and terminal work.

Where You Can Run It

Cohere made availability broad on day one, which matters more than benchmarks for a model people are meant to actually deploy:

• Hugging Face - weights in bf16, fp8, and w4a16 (4-bit) formats
• Cohere API - hosted inference
• Model Vault - Cohere's managed dedicated inference
• OpenCode - usable for free inside the open-source coding harness
• OpenRouter - routed access alongside other models

The OpenCode integration is a smart distribution move. OpenCode is currently the most-starred open-source coding agent, so dropping North Mini Code into that harness puts it in front of a large existing developer audience without asking anyone to change tools.

The Benchmark Picture (Read This Carefully)

This is where favorable framing needs to give way to precision.

The single concrete, third-party-anchored number Cohere reports is 33.4 on the Artificial Analysis Coding Index, which the company characterizes as "a competitive position among similarly sized models." That is an honest framing - it is not claiming frontier parity, it is claiming it competes in its weight class.

Cohere says it evaluated the model on SWE-Bench Verified, SWE-Bench Pro, Terminal-Bench v2 (plus Terminal-Bench Hard, SciCode, and LiveCodeBench v6), running three seeds and averaging. However, individual scores for those benchmarks were not disclosed in the launch materials or in independent coverage available at publication. Treat any specific SWE-Bench percentage you see attributed to North Mini Code with skepticism until Cohere publishes the per-benchmark numbers.

The efficiency claims are clearer, though still vendor-reported. Against Devstral Small 2, Cohere reports:

• Up to 2.8x higher output throughput
• A ~30% advantage in inter-token latency
• Devstral Small 2 keeps a slight lead on time-to-first-token

These are throughput-and-latency claims, not quality claims, and they have not been independently reproduced. They are plausible given the 3B active-parameter design, but worth confirming on your own hardware before you build a latency budget around them.

Why This Matters

The interesting story here is not "Cohere beat anyone." It is the shape of the offering.

Self-hosting just got more practical for coding. A 30B MoE that runs on one H100 with open weights and a permissive license lands in the same conversation as Devstral, Qwen-class coders, and other locally runnable models. For teams under data-residency or compliance pressure - the exact crowd that cannot send source code to a third-party API - a single-GPU footprint and Apache 2.0 terms remove two of the biggest blockers at once.

256K context is generous for the size class. Agentic coding chews through context fast once you add file trees, diffs, and tool output. A quarter-million-token window on a model this small is a real working advantage for repo-scale tasks.

Cohere is signaling a direction. Calling this the "inaugural member" of a next generation suggests more developer-facing models are coming from a company that previously stayed out of the coding race. That is worth watching even if this first model is a mid-tier entry rather than a leader.

The Honest Caveats

• No disclosed SWE-Bench scores. The headline coding benchmarks were run but not published with numbers. Until they are, the quality picture rests on a single composite index (33.4) and Cohere's own framing.
• Efficiency numbers are vendor-reported. The 2.8x throughput and 30% latency figures come from Cohere, not independent labs.
• "Competitive among similarly sized models" is not "best." This is a small, efficient, openly licensed model - not a Fable 5 or GPT-5.5 competitor on raw capability. Set expectations accordingly.

Should You Try It?

If you are already self-hosting coding models, North Mini Code is worth a slot in your evaluation harness this week - the Apache 2.0 license, single-H100 footprint, and OpenCode integration make it cheap to test. If you are happy with a hosted frontier model and have no compliance reason to bring inference in-house, there is no urgency here. And if you see a specific SWE-Bench percentage quoted for it, ask where the number came from before you trust it.

The most useful thing about this release is not the model itself but what it represents: capable, openly licensed coding models that fit on hardware a single team can afford are becoming normal. That trend is good for developers regardless of which vendor's logo is on this particular checkpoint.

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Sources

• North Mini Code: Agentic Coding Model for Developers - Cohere
• Introducing North Mini Code - Cohere Labs on Hugging Face
• Cohere open-sources a coding agent that runs on a single H100 - VentureBeat
• Meet North Mini Code - MarkTechPost