float8 for FP8 and bfloat16 for BF16. An offer with missing quantization metadata does not qualify. If no eligible offer matches, the request fails with routing diagnostics; Phaseo does not fall back to an unverified quantization. The equivalent routing.quantizations shape is also accepted.
Step 1: define your success criteria
Before choosing a quant:- Set quality thresholds (task accuracy, pass rates, structured output validity).
- Set latency and cost targets.
- Define unacceptable failure modes.
Step 2: pick a high-quality baseline
Start with a stronger baseline (oftenBF16 or FP16) and measure:
- Output quality
- Median and tail latency
- Token/cost profile
Step 3: step down gradually
Evaluate progressively lower precision:FP8orINT8FP4orINT4only if needed for cost/throughput
Step 4: evaluate real workloads
Use production-like prompts:- Long prompts
- Multi-step reasoning
- Tool calling
- Edge cases from support tickets
Step 5: decide per endpoint/use case
One quantization does not need to fit everything. Examples:- Customer support and critical decisioning: higher precision.
- Large-volume classification/summarization: lower precision can be acceptable.
Suggested starting points
Deployment policy
- Keep a fallback model/quantization configured.
- Monitor quality drift after rollout.
- Re-test when provider runtime or model revision changes.