North-Mini-Code-1.0
North Mini Code is an open weights research release of a 30B-A3B parameter model optimized for code generation, agentic software engineering, and terminal tasks.
Params
30.5 B
Context
500,000
Downloads 30d
7 K
Likes
583
Download history
tracking started — chart appears after 7 days of snapshots (6 recorded)7 K downloads in the last 30 days
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | bf16 | 61.0 GB | 72.1 GB | ❌ Won’t fit |
| model.safetensors (bf16, full) | bf16 + 488K ctx | 61.0 GB | 346.7 GB | ❌ Won’t fit |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Run it
copy-paste, exact tags checked against the Hub$ curl -s https://aimodelscomparison.com/api/v1/models/north-mini-code-1-0
{
"hf_id": "CohereLabs/North-Mini-Code-1.0",
"params_b": 30.48,
"context_length": 500000,
"license": { "id": "apache-2.0", "commercial": "yes" },
"downloads_30d": 7070,
"vram_estimates": [
{ "quant": "bf16", "gb": 72.1 }
],
"updated_at": "2026-10-19T06:02:45Z"
}
Use via API
via OpenRouter · USD per 1M tokens · synced 2026-10-24Free
input / 1M
Free
output / 1M
—
cached input / 1M
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1M in + 1M out
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- Context window
- 256,000 tokens
- Max output
- 64,000 tokens
- Providers
- —
- Cheapest provider
- —
- Best throughput
- —
- AA Intelligence / Coding / Agentic
- 9.9 / 36.5 / 1.1
✓ Tool calling
✓ Reasoning
✗ Structured outputs
✗ Image input
✗ File input
✗ Audio input
✗ Prompt caching
Specifications
- Architecture
- Cohere2MoeForCausalLM
- Parameters
- 30.5 B
- Tensor type
- BF16
- Context length
- 500,000
- Vocabulary
- 262,144
- Layers / heads
- 49 / 32
- Licence
- apache-2.0
- First seen on the Hub
- 2026-06-05
- Training datasets
- undisclosed
- Added to our catalog
- 2026-10-20
Compare with any text-generation model