What GPU do I need to run CohereLabs/c4ai-command-r7b-12-2024?
8.0B parameters, published in BF16. View on Hugging FaceGated
c4ai-command-r7b-12-2024 is published by CohereLabs on Hugging Face, with 13,140 downloads and 429 likes to date. It's a Cohere2ForCausalLM model built for text-generation, published natively in BF16, and gated: you'll need to accept the model's terms on Hugging Face before downloading weights.
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 c4ai-command-r7b-12-2024 at its published (BF16) precision: 1× RTX 3090 on simplepod, at $0.160/hr per GPU ($0.160/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)
- North-Mini-Code-1.0 (30.5B, BF16)
- aya-expanse-8b (8.0B, F16)
- Qwen3-0.6B (752M, BF16)
