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vllm-omni/docs/design/module/diffusion/continuous_batching.md
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---
title: Diffusion Continuous Batching
kind: module
status: draft
owners:
- "@Isotr0py"
- "@princepride"
primary_code_paths:
- vllm_omni/diffusion/sched/**
related_code_paths:
- vllm_omni/diffusion/executor/**
depends_on:
- diffusion_runtime.md
validation_paths:
- tests/diffusion/batching/**
upstream_refs: []
last_reviewed: 2026-07-16
---
# Diffusion continuous batching
Continuous batching defines when diffusion requests are compatible, how they
share an execution step, and how each request advances independently.
## Candidate invariants
### BATCH-INV-001: Compatibility is explicit
**Rule:** Requests MAY share a batch only when all properties required by the
selected pipeline, scheduler step, shape, precision, and execution features are
compatible.
### BATCH-INV-002: Per-request state remains isolated
**Rule:** Batch assembly MUST preserve each request's random generator, progress,
conditioning, outputs, cancellation, and errors.
### BATCH-INV-003: Admission is bounded
**Rule:** Admission MUST respect configured capacity and MUST NOT rely on an
unbounded waiting or active-request collection.
### BATCH-INV-004: Batch order is not completion order
**Rule:** Output association MUST use stable request identity rather than batch
position across execution steps.
## Safe-change guide
Test heterogeneous requests, partial completion, cancellation, deterministic
seeds, capacity limits, and batch sizes of one and many.