Choose an inference setup based on the workload you actually need to run. The selector focuses on architecture and requirements rather than producing a universal provider ranking.
Select the characteristics that matter most. The tool will generate a practical inference profile.
This tool does not rank providers or estimate live pricing.
Generate a profile to see which inference characteristics to prioritize.
Different applications should optimize for different inference signals.
| Workload | Prioritize | Watch closely | Typical mistake |
|---|---|---|---|
| Interactive chat | TTFT, streaming, p95 latency | Context length, provider load | Optimizing only tokens/sec |
| Agentic workflow | Total task latency, reliability, tool support | Retries, tool round trips, failover | Measuring only one model call |
| Batch generation | Throughput, utilization, cost | Queue depth, batching efficiency | Over-prioritizing interactive latency |
| Embeddings | Request throughput, latency, cost | Batch size, vector consistency | Ignoring retrieval quality after model changes |
| Multimodal | End-to-end latency, modality support | Upload/preprocessing time, memory | Comparing with text-only metrics |
| Edge / local | Memory, power, bounded latency | Quantization, hardware compatibility | Using cloud assumptions on-device |