# Deploy c4ai-command-a-03-2025 on dedicated GPUs

c4ai-command-a-03-2025 by Cohere, deployable on sference as a dedicated deployment: reserved GPU capacity, private endpoint, European GPUs, billed per GPU-hour on monthly commitments. Request it at https://sference.com/models/CohereLabs/c4ai-command-a-03-2025.

## Specs

- Hugging Face: https://huggingface.co/CohereLabs/c4ai-command-a-03-2025
- Category: Chat & reasoning
- Parameters: 111B
- Architecture: Dense
- Context: — tokens
- Published precision: BF16
- Checkpoint size: 222 GB
- Minimum footprint: 4 GPUs (80 GB) or 2 GPUs (141 GB) to load the weights; more for long contexts and concurrency
- License: CC BY-NC 4.0 (Non-commercial only)

## FAQ

### Can I run c4ai-command-a-03-2025 on a dedicated deployment in Europe?

Yes. sference deploys c4ai-command-a-03-2025 on GPU capacity reserved for you, behind a private endpoint, with every request processed on European GPUs and logged in your audit trail. Tell us your expected volume and latency targets with the form on this page and we come back with a sizing and a quote.

### How many GPUs does c4ai-command-a-03-2025 need?

The published checkpoint is about 222 GB (BF16), so loading it takes at least 4 GPUs with 80 GB of memory each, or 2 GPUs with 141 GB each. Long contexts and high concurrency need more for the KV cache; quantization needs less. You don't pick hardware on sference: you choose a performance tier and we size the deployment.

### Is c4ai-command-a-03-2025 licensed for commercial use?

c4ai-command-a-03-2025 is published under the CC BY-NC 4.0 license. Non-commercial use only. Production use needs a separate commercial license from the model maker.

### How is a dedicated deployment priced?

Per GPU-hour on a monthly commitment, sized to your throughput and latency targets.

Facts from Hugging Face, synced 2026-10-27. All deployable models: https://sference.com/dedicated.md