What GPU do I need to run CohereLabs/North-Mini-Code-1.0?
30.5B parameters, published in BF16. View on Hugging Face
North-Mini-Code-1.0 is published by CohereLabs on Hugging Face, with 20,274 downloads and 564 likes to date. It's a Cohere2MoeForCausalLM model built for text-generation, published natively in BF16.
VRAM required & cheapest live GPU fit
Required VRAM = weight size at each precision, plus a fixed overhead for KV-cache, activations, and fragmentation. Full formula and assumptions: methodology.
A GPU is only matched to a row if its hardware supports that precision, and the primary recommendation is always a single-GPU fit when one exists.
INT4 caveat: requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.
Cheapest way to run North-Mini-Code-1.0 at its published (BF16) precision: 1× A100 on runpod, at $1.19/hr per GPU ($1.19/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More CohereLabs models
- cohere-transcribe-03-2026 (2.1B, BF16)
- cohere-transcribe-arabic-07-2026 (2.1B, BF16)
- c4ai-command-r-v01 (35.0B, F16)
- aya-expanse-8b (8.0B, F16)
- c4ai-command-r7b-12-2024 (8.0B, BF16)
- Qwen3-0.6B (752M, BF16)