vLLM concurrency

Plan vLLM concurrency before raising max_num_seqs

Higher sequence concurrency only works when the KV Cache can support the chosen model length; a single-user fit is not a serving-capacity result.

Use full-length concurrency as the planning baseline

Plan for the concurrent active requests that may reach the configured maximum model length. Shorter real-world requests can create headroom, but they should not be the only capacity assumption.

Treat cache pressure as a scheduling signal

When the cache budget is close to the requested total, queueing, recomputation, or request limits can become part of normal operation. Keep a planning margin rather than treating the theoretical maximum as the default setting.

Change one lever at a time

Reduce the model-length target, reduce concurrent active requests, select a smaller weight footprint, or increase aggregate VRAM. Each path has a different effect on product behavior and cost.

Continue planning

Test this memory constraint with a live capacity plan.

Editorial record

Maintained by Make Your Own Tools to turn “Fit an LLM workload” into a defined weights, context or activations, runtime reserve, and the next hardware boundary. The references below provide the technical context for this planning path. Its calculation rules and planning assumptions are documented in the methodology, and affected calculations pass regression checks before the review date advances.

Last reviewed
Evidence set
3 primary references
Calculation coverage
2 affected rules checked
Planning scope
vLLM active-sequence planning against a defined model-length and GPU-memory budget.
Next check
Carry the concurrency limit into the exact request distribution, scheduler configuration, service objective, and load test.