LLM inference
Common Compute vs Together AI.
Together is a fully managed LLM inference API optimized for high-throughput chat. Common Compute offers a smaller catalog on provider-owned hardware; compare current price, capacity, and measured performance.
Last reviewed 2026-05-13
Honest take
Where we win, where they win.
For high-volume chat, benchmark Together and other purpose-built GPU services first.
Consider Common Compute when a currently offered model fits your provider-hardware and availability requirements and a locked per-task quote is useful.
Published comparisons are a starting point, not a savings or performance guarantee.
Pick Common Compute when…
- Your workflow fits a workload and model in the current public catalog.
- You want a quote before execution across the currently offered modalities.
- You can tolerate availability that depends on eligible provider devices.
Pick Together AI when…
- Chat is your primary workload.
- You need flagship open-weight models (Llama, Mixtral) at scale.
- You need fine-tuning.
- You're serving consumer-facing chat where token cost moves your gross margin.
Try us on a real workload.
See the unit rate and estimated total before every job, set a hard spend cap, and pay only for successful work. Cost depends on the workload, model, priority, and measured usage.