[Bugfix] Deterministic MoE combine (reduce_scatterv) under VLLM_BATCH_INVARIANT by shijuzhao · Pull Request #45683 · vllm-project/vllm

shijuzhao · 2026-06-15T09:59:19Z

Purpose

Under batch-invariant / deterministic mode (VLLM_BATCH_INVARIANT=1), the
cross-rank summation order in the MoE combine step is not stable, which breaks
bit-for-bit reproducibility when running with Data Parallel (DP) + Expert
Parallel (EP). This PR makes the combine reduction deterministic with two
coordinated changes:

cuda_communicator.py (deterministic combine branch): under
VLLM_BATCH_INVARIANT with DP world size > 2, run the MoE combine as a
fixed-root reduce + scatter instead of the routing-dependent
reduce_scatter / reduce_scatterv.
pynccl.py (deterministic primitives): add reduce (single fixed-root
ncclReduce over the whole buffer) and scatter (deliver each rank's own
chunk from the root), so every element is reduced with the same NCCL
reduction tree regardless of where a token is routed.

This only changes behavior when VLLM_BATCH_INVARIANT is enabled and DP world
size > 2; the default (non-deterministic, performance-first) path is
untouched.

Fixes #30321

Motivation

vLLM's batch-invariant mode is meant to guarantee that the logits/logprobs of a
request are bit-for-bit identical regardless of batch composition and of
which DP worker the request lands on. For MoE/EP models this guarantee currently
does not hold in the combine step. This issue was first observed in [Feature]:
Batch Invariant Feature in DP+EP.

We observed the divergence by sending the same request to different DP ranks.
This issue can be reproduced using an MoE model with DP world size > 2.

Brief Env:

vLLM version: 0.23.0
Model: Qwen/Qwen3-30B-A3B-Instruct-2507
GPU: NVIDIA H200 141GB x 4
OS: Linux
CUDA: 13.0
PyTorch: 2.11.0

First launch the vLLM server with DP world size 4:

VLLM_BATCH_INVARIANT=1 vllm serve --model Qwen/Qwen3-30B-A3B-Instruct-2507 --data-parallel-size 4

Then send the same request to different DP ranks with the script repro_for_issue.py:

python3 repro_for_issue.py

repro_for_issue.py sends the same prompt to both workers and compares the results.

Observed output:

[INFO] Comparing Worker 0 vs Worker 1 ...
  [FAIL] Different tokens sampled.
         BS=1 tokens: [' the', ' long', ',', ' warm', ' days', ' that', ' stretch', ' out']
         BS=N tokens: [' the', ' long', ',', ' warm', ' days', ' with', ' the', ' sun']

Root cause

The MoE combine is implemented on top of CudaCommunicator.reduce_scatterv,
which picks one of two PyNCCL primitives depending on the per-rank sizes:

# vllm/distributed/device_communicators/cuda_communicator.py (before)
if sizes is not None and sizes.count(sizes[0]) != len(sizes):
    pynccl_comm.reduce_scatterv(output, input_tensor, sizes=sizes)  # variable sizes
else:
    pynccl_comm.reduce_scatter(output, input_tensor)                # uniform sizes

Both branches are routing/order-dependent and therefore non-deterministic across
DP ranks:

reduce_scatter (uniform-sizes branch) maps to ncclReduceScatter,
whose internal ring/tree reduction order depends on rank position. This is
the branch that actually breaks decode (see below).
reduce_scatterv (variable-sizes branch) issues one ncclReduce
per chunk, each with a different root (chunk i is reduced to
root == i):
```
for root, split_size in enumerate(sizes):
    chunk = input_tensor[split_offset : split_offset + split_size, ...]
    self.nccl.ncclReduce(..., root, ...)
```
Different roots use different NCCL reduction trees, so the summation order
depends on which chunk/root a token belongs to.

Why decode was the failing case: in the decode phase every DP rank contributes
exactly one token, so sizes is uniform (e.g. [1, 1, 1, 1]). With uniform
sizes, sizes.count(sizes[0]) != len(sizes) is False, so the dispatcher took
the reduce_scatter branch and never entered reduce_scatterv at all. A
deterministic implementation living inside reduce_scatterv therefore had no
effect on decode — the combine still went through the non-deterministic
ncclReduceScatter.

Floating-point addition is not associative: (a + b) + c ≠ a + (c + b) at the
ULP level. Because the reduction order is rank/routing dependent in both
branches, the rounded combine result changes with the DP rank a request lands
on. This is the source of the DP-rank-dependent, ULP-level nondeterminism.

Note this only matters for DP world size > 2: with exactly two ranks the
cross-rank reduction is a single a + b, which is commutative and bit-exact
regardless of the tree, so no fix is needed there.

Changes

cuda_communicator.py: deterministic combine branch in
reduce_scatterv. A new gate selects the deterministic combine only when
it is both requested and meaningful — batch-invariant mode with DP world size
> 2:

use_deterministic_combine = envs.VLLM_BATCH_INVARIANT and world_size > 2
if use_deterministic_combine:
    # Reduce to a fixed root (0) for determinism.
    reduced = torch.empty_like(input_tensor)
    sizes = sizes if sizes else [chunk_size] * world_size
    pynccl_comm.reduce(reduced, input_tensor, root=0)
    pynccl_comm.scatter(output, reduced, sizes, root=0)
elif sizes is not None and sizes.count(sizes[0]) != len(sizes):
    pynccl_comm.reduce_scatterv(output, input_tensor, sizes=sizes)
else:
    pynccl_comm.reduce_scatter(output, input_tensor)

This is what fixes the decode phase: uniform sizes (e.g. [1, 1, 1, 1])
used to fall through to the routing-dependent reduce_scatter. Now, under
batch-invariant mode, uniform sizes also take the deterministic path. The
two original branches (reduce_scatterv for variable sizes, reduce_scatter
otherwise) are preserved unchanged for the default path.

pynccl.py: add a PyNcclCommunicator.reduce(...) method.
It reduces the entire input_tensor to a single root with one
ncclReduce call (binding already exists in pynccl_wrapper.py), so every
element is summed with the same reduction tree irrespective of its
position in the buffer.
pynccl.py: add a PyNcclCommunicator.scatter(...) method.
It splits the buffer on root into per-rank chunks (sizes) and delivers
chunk i to rank i, implemented as a single grouped ncclSend/ncclRecv
(root keeps its own chunk via a local copy). This is pure data movement.

Together, changes 2–3 give a deterministic reduce-scatter: a single reduce
tree (independent of token routing) followed by pure data movement, driven from
the new branch in change 1.

vllm/distributed/device_communicators/cuda_communicator.py | deterministic reduce()+scatter() branch gated by VLLM_BATCH_INVARIANT and DP > 2
vllm/distributed/device_communicators/pynccl.py            | + reduce(), + scatter()

Why this approach

Alternatives considered:

all_gather + local sum in a fixed order: also deterministic, but requires
gathering world_size full copies of the buffer and summing them locally —
more memory traffic and a local reduction on top.
single reduce (fixed root) + broadcast: one reduce + one broadcast.
Correct and deterministic, but broadcast delivers the whole buffer to
every rank while each rank only needs its own chunk_size rows — roughly
world_sizex redundant ingest per rank. Even with NCCL multicast (NVLS/SHARP)
optimizing the broadcast, each receiver still has to pull the full buffer over
its inbound link, so the redundant data can't be avoided.
single reduce (fixed root) + scatter (this PR): the reduced result
already lives on root, so we scatter only the sizes[rank] rows each rank
needs. On a fully-connected intra-node fabric (NVLink/NVSwitch) the root fans
out the distinct chunks over independent links in parallel, moving far less
data per rank than broadcast. Determinism is identical (scatter does no
arithmetic). The only assumption is that a single ncclReduce call uses one
consistent reduction tree for the whole buffer (fixed root / communicator).

Limitations / future work

Active only for DP world size > 2; DP ≤ 2 is already bit-exact.
CUDA / NCCL path only (CudaCommunicator); other backends (e.g. XPU) are not
changed. Note the dispatch fix lives in CudaCommunicator.reduce_scatterv, so
non-CUDA communicators still take their original combine path.
Relies on NCCL using a single reduction tree per ncclReduce call for a fixed
root and communicator.

Test plan

Batch Invariance Test test.py:

Start the server.
Send 32 requests with batch size 1 one-by-one.
Send 32 requests with batch size 32 all at once.
Compare the results.

python3 test.py

Test results

Pass.

============================================================
Batch Invariance Test
============================================================
  Server URL : http://0.0.0.0:8000/v1
  Model      : Qwen/Qwen3-30B-A3B-Instruct-2507
  Num prompts: 32
  Max tokens : 8
  Seed       : 42
  Temperature: 0.6
  Top-p      : 1.0
  Logprobs   : 5
============================================================
[INFO] Server reachable. Available models: ['Qwen/Qwen3-30B-A3B-Instruct-2507']
[INFO] Starting BS=1 requests for 32 prompts ...
  BS=1 progress: 8/32
  BS=1 progress: 16/32
  BS=1 progress: 24/32
  BS=1 progress: 32/32
[INFO] Starting BS=N (batch of 32) request ...
  BS=N done.
[INFO] Comparing BS=1 vs BS=N ...
  [PASS] Prompt 0: tokens and logprobs match exactly.
  [PASS] Prompt 1: tokens and logprobs match exactly.
  [PASS] Prompt 2: tokens and logprobs match exactly.
  [PASS] Prompt 3: tokens and logprobs match exactly.
  [PASS] Prompt 4: tokens and logprobs match exactly.
  [PASS] Prompt 5: tokens and logprobs match exactly.
  [PASS] Prompt 6: tokens and logprobs match exactly.
  [PASS] Prompt 7: tokens and logprobs match exactly.
  [PASS] Prompt 8: tokens and logprobs match exactly.
  [PASS] Prompt 9: tokens and logprobs match exactly.
  [PASS] Prompt 10: tokens and logprobs match exactly.
  [PASS] Prompt 11: tokens and logprobs match exactly.
  [PASS] Prompt 12: tokens and logprobs match exactly.
  [PASS] Prompt 13: tokens and logprobs match exactly.
  [PASS] Prompt 14: tokens and logprobs match exactly.
  [PASS] Prompt 15: tokens and logprobs match exactly.
  [PASS] Prompt 16: tokens and logprobs match exactly.
  [PASS] Prompt 17: tokens and logprobs match exactly.
  [PASS] Prompt 18: tokens and logprobs match exactly.
  [PASS] Prompt 19: tokens and logprobs match exactly.
  [PASS] Prompt 20: tokens and logprobs match exactly.
  [PASS] Prompt 21: tokens and logprobs match exactly.
  [PASS] Prompt 22: tokens and logprobs match exactly.
  [PASS] Prompt 23: tokens and logprobs match exactly.
  [PASS] Prompt 24: tokens and logprobs match exactly.
  [PASS] Prompt 25: tokens and logprobs match exactly.
  [PASS] Prompt 26: tokens and logprobs match exactly.
  [PASS] Prompt 27: tokens and logprobs match exactly.
  [PASS] Prompt 28: tokens and logprobs match exactly.
  [PASS] Prompt 29: tokens and logprobs match exactly.
  [PASS] Prompt 30: tokens and logprobs match exactly.
  [PASS] Prompt 31: tokens and logprobs match exactly.
============================================================
[RESULT] ALL 32 prompts PASSED — BS=1 and BS=N produce bitwise-identical results.

Without this, 19 of the 32 runs will diverge from the batch-size 1 version. Otherwise, it will pass.

============================================================
Batch Invariance Test
============================================================
  Server URL : http://0.0.0.0:8000/v1
  Model      : Qwen/Qwen3-30B-A3B-Instruct-2507
  Num prompts: 32
  Max tokens : 8
  Seed       : 42
  Temperature: 0.6
  Top-p      : 1.0
  Logprobs   : 5
============================================================
[INFO] Server reachable. Available models: ['Qwen/Qwen3-30B-A3B-Instruct-2507']
[INFO] Starting BS=1 requests for 32 prompts ...
  BS=1 progress: 8/32
  BS=1 progress: 16/32
  BS=1 progress: 24/32
  BS=1 progress: 32/32
[INFO] Starting BS=N (batch of 32) request ...
  BS=N done.
[INFO] Comparing BS=1 vs BS=N ...
  [PASS] Prompt 0: tokens and logprobs match exactly.
  [PASS] Prompt 1: tokens and logprobs match exactly.
  [FAIL] Prompt 2 Step 0: Bitwise mismatch (abs diff=5.671501e-02).
         BS=1 tokens: [' ', '3', '0', '0', ' pieces', ' of', ' candy', '.']
         BS=N tokens: [' ', '3', '0', '0', ' pieces', ' of', ' candy', '.']
  [FAIL] Prompt 3 Step 0: Bitwise mismatch (abs diff=1.016247e-02).
         BS=1 tokens: [' the', ' long', ',', ' warm', ' days', ' that', ' stretch', ' out']
         BS=N tokens: [' the', ' long', ',', ' warm', ' days', ' that', ' stretch', ' out']
  [PASS] Prompt 4: tokens and logprobs match exactly.
  [PASS] Prompt 5: tokens and logprobs match exactly.
  [FAIL] Prompt 6 Step 0: Bitwise mismatch (abs diff=2.738833e-02).
         BS=1 tokens: [' the', ' long', '-lo', 'st', ' planet', ' of', ' Earth', ',']
         BS=N tokens: [' the', ' long', '-lo', 'st', ' planet', ' of', ' Earth', ',']
  [FAIL] Prompt 7 Step 0: Bitwise mismatch (abs diff=4.982090e-02).
         BS=1 tokens: [' ', '3', '0', '0', ' pieces', ' of', ' candy', '.']
         BS=N tokens: [' ', '3', '0', '0', ' pieces', ' of', ' candy', '.']
  [PASS] Prompt 8: tokens and logprobs match exactly.
  [FAIL] Prompt 9 Step 0: Bitwise mismatch (abs diff=7.431746e-03).
         BS=1 tokens: [' natural', ' and', ' human', ' activities', '.', ' What', ' are', ' some']
         BS=N tokens: [' natural', ' and', ' human', ' activities', '.', ' What', ' are', ' some']
  [FAIL] Prompt 10 Step 0: Bitwise mismatch (abs diff=1.092851e-02).
         BS=1 tokens: [' span', 'ned', ' from', ' the', ' ', '1', '4', 'th']
         BS=N tokens: [' span', 'ned', ' from', ' the', ' ', '1', '4', 'th']
  [FAIL] Prompt 11 Step 0: Bitwise mismatch (abs diff=1.361342e-04).
         BS=1 tokens: [' a', ' fundamental', ' theory', ' in', ' physics', ' that', ' provides', ' a']
         BS=N tokens: [' a', ' fundamental', ' theory', ' in', ' physics', ' that', ' provides', ' a']
  [PASS] Prompt 12: tokens and logprobs match exactly.
  [PASS] Prompt 13: tokens and logprobs match exactly.
  [FAIL] Prompt 14 Step 0: Bitwise mismatch (abs diff=1.092851e-02).
         BS=1 tokens: [' span', 'ned', ' from', ' the', ' ', '1', '4', 'th']
         BS=N tokens: [' span', 'ned', ' from', ' the', ' ', '1', '4', 'th']
  [FAIL] Prompt 15 Step 0: Bitwise mismatch (abs diff=5.140714e-05).
         BS=1 tokens: [' a', ' fundamental', ' theory', ' in', ' physics', ' that', ' provides', ' a']
         BS=N tokens: [' a', ' fundamental', ' theory', ' in', ' physics', ' that', ' provides', ' a']
  [PASS] Prompt 16: tokens and logprobs match exactly.
  [FAIL] Prompt 17 Step 0: Bitwise mismatch (abs diff=8.551445e-03).
         BS=1 tokens: [' a', ' curious', ' little', ' robot', ' named', ' R', 'oly', '.']
         BS=N tokens: [' a', ' curious', ' little', ' robot', ' named', ' R', 'oly', '.']
  [FAIL] Prompt 18 Step 0: Bitwise mismatch (abs diff=2.738833e-02).
         BS=1 tokens: [' the', ' long', '-lo', 'st', ' planet', ' of', ' Earth', ',']
         BS=N tokens: [' the', ' long', '-lo', 'st', ' planet', ' of', ' Earth', ',']
  [FAIL] Prompt 19 Step 0: Bitwise mismatch (abs diff=1.113994e-01).
         BS=1 tokens: [' for', ' each', ' element', ',', ' it', ' compares', ' the', ' current']
         BS=N tokens: [' for', ' each', ' element', ',', ' it', ' compares', ' the', ' current']
  [PASS] Prompt 20: tokens and logprobs match exactly.
  [PASS] Prompt 21: tokens and logprobs match exactly.
  [FAIL] Prompt 22 Step 0: Bitwise mismatch (abs diff=6.803842e-04).
         BS=1 tokens: [' Paris', '.\n\n', 'Question', ':', ' What', ' is', ' the', ' capital']
         BS=N tokens: [' Paris', '.\n\n', 'Question', ':', ' What', ' is', ' the', ' capital']
  [FAIL] Prompt 23 Step 0: Bitwise mismatch (abs diff=5.350661e-02).
         BS=1 tokens: [' natural', ' and', ' human', ' activities', '.', ' What', ' are', ' some']
         BS=N tokens: [' natural', ' and', ' human', ' activities', '.', ' What', ' are', ' some']
  [PASS] Prompt 24: tokens and logprobs match exactly.
  [PASS] Prompt 25: tokens and logprobs match exactly.
  [FAIL] Prompt 26 Step 0: Bitwise mismatch (abs diff=5.025234e-03).
         BS=1 tokens: [' green', ' plants', ',', ' algae', ',', ' and', ' some', ' bacteria']
         BS=N tokens: [' green', ' plants', ',', ' algae', ',', ' and', ' some', ' bacteria']
  [FAIL] Prompt 27 Step 0: Bitwise mismatch (abs diff=5.155802e-06).
         BS=1 tokens: [' green', ' plants', ',', ' algae', ',', ' and', ' some', ' bacteria']
         BS=N tokens: [' green', ' plants', ',', ' algae', ',', ' and', ' some', ' bacteria']
  [PASS] Prompt 28: tokens and logprobs match exactly.
  [FAIL] Prompt 29 Step 0: Bitwise mismatch (abs diff=8.551445e-03).
         BS=1 tokens: [' a', ' curious', ' little', ' robot', ' named', ' R', 'oly', '.']
         BS=N tokens: [' a', ' curious', ' little', ' robot', ' named', ' R', 'oly', '.']
  [FAIL] Prompt 30 Step 0: Bitwise mismatch (abs diff=1.092851e-02).
         BS=1 tokens: [' span', 'ned', ' from', ' the', ' ', '1', '4', 'th']
         BS=N tokens: [' span', 'ned', ' from', ' the', ' ', '1', '4', 'th']
  [FAIL] Prompt 31 Step 0: Bitwise mismatch (abs diff=4.395278e-02).
         BS=1 tokens: [' my', ' current', ' one', ' is', ' over', ' ', '5', ' years']
         BS=N tokens: [' my', ' current', ' one', ' is', ' over', ' ', '5', ' years']
============================================================
[RESULT] 19/32 prompts FAILED — batch invariance is NOT satisfied.

Notes

AI assistance was used to help analyze the root cause and draft this change.
The submitter has reviewed every changed line and is responsible for the change
end-to-end.

Essential Elements of an Effective PR Description Checklist

The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
The test plan, such as providing test command.
The test results, such as pasting the results comparison before and after, or e2e results
(Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.

github-actions · 2026-06-15T09:59:29Z

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🚀

yewentao256

Thanks for the work!

yewentao256 · 2026-06-26T14:50:08Z

+        if sizes is not None and (
+            sizes.count(sizes[0]) != len(sizes) or envs.VLLM_BATCH_INVARIANT
+        ):
+            # Note: force to use `reduce_scatterv` under BATCH_INVARIANT mode.


Why do we need this? Changing the default behavior for other cases

When 4 DP workers happen to have exactly the same number of tokens to reduce_scatter, sizes.count(sizes[0]) == len(sizes). Without this, the code would follow the else branch below, bypassing the batch-invariant path. You can delete this and test with test.py. Without this, 22 of the 32 runs will diverge from the batch-size 1 version. Otherwise, it will pass.

============================================================ Batch Invariance Test ============================================================ Server URL : http://0.0.0.0:8000/v1 Model : Qwen/Qwen3-30B-A3B-Instruct-2507 Num prompts: 32 Max tokens : 8 Seed : 42 Temperature: 0.6 Top-p : 1.0 Logprobs : 5 ============================================================ [INFO] Server reachable. Available models: ['Qwen/Qwen3-30B-A3B-Instruct-2507'] [INFO] Starting BS=1 requests for 32 prompts ... BS=1 progress: 8/32 BS=1 progress: 16/32 BS=1 progress: 24/32 BS=1 progress: 32/32 [INFO] Starting BS=N (batch of 32) request ... BS=N done. [INFO] Comparing BS=1 vs BS=N ... [PASS] Prompt 0: tokens and logprobs match exactly. [PASS] Prompt 1: tokens and logprobs match exactly. [FAIL] Prompt 2 Step 0: Bitwise mismatch (abs diff=7.413387e-02). BS=1 tokens: [' some', ' apples', '.', ' ', ' This', ' is', ' an', ' interesting'] BS=N tokens: [' some', ' apples', '.', ' ', ' This', ' is', ' an', ' interesting'] [FAIL] Prompt 3 Step 0: Bitwise mismatch (abs diff=1.930434e-02). BS=1 tokens: [' the', ' long', ' days', ' and', ' warm', ' weather', '.', ' I'] BS=N tokens: [' the', ' long', ' days', ' and', ' warm', ' weather', '.', ' I'] [PASS] Prompt 4: tokens and logprobs match exactly. [PASS] Prompt 5: tokens and logprobs match exactly. [FAIL] Prompt 6 Step 0: Bitwise mismatch (abs diff=1.002533e-01). BS=1 tokens: [' the', ' long', '-lo', 'st', ' planet', ' of', ' Earth', ','] BS=N tokens: [' the', ' long', '-lo', 'st', ' planet', ' of', ' Earth', ','] [FAIL] Prompt 7 Step 0: Bitwise mismatch (abs diff=1.590445e-01). BS=1 tokens: [' some', ' apples', '.', ' ', ' This', ' is', ' an', ' interesting'] BS=N tokens: [' some', ' apples', '.', ' ', ' This', ' is', ' an', ' interesting'] [PASS] Prompt 8: tokens and logprobs match exactly. [PASS] Prompt 9: tokens and logprobs match exactly. [FAIL] Prompt 10 Step 0: Bitwise mismatch (abs diff=3.256738e-03). BS=1 tokens: [' span', 'ned', ' from', ' the', ' ', '1', '4', 'th'] BS=N tokens: [' span', 'ned', ' from', ' the', ' ', '1', '4', 'th'] [FAIL] Prompt 11 Step 0: Bitwise mismatch (abs diff=7.660594e-03). BS=1 tokens: [' a', ' fundamental', ' theory', ' in', ' physics', ' that', ' provides', ' a'] BS=N tokens: [' a', ' fundamental', ' theory', ' in', ' physics', ' that', ' provides', ' a'] [PASS] Prompt 12: tokens and logprobs match exactly. [FAIL] Prompt 13 Step 0: Bitwise mismatch (abs diff=4.455280e-03). BS=1 tokens: [' green', ' plants', ',', ' algae', ',', ' and', ' some', ' bacteria'] BS=N tokens: [' green', ' plants', ',', ' algae', ',', ' and', ' some', ' bacteria'] [FAIL] Prompt 14 Step 0: Bitwise mismatch (abs diff=5.840617e-02). BS=1 tokens: [' are', ' responsible', ' for', ' processing', ' and', ' transmitting', ' information', '.'] BS=N tokens: [' are', ' responsible', ' for', ' processing', ' and', ' transmitting', ' information', '.'] [FAIL] Prompt 15 Step 0: Bitwise mismatch (abs diff=3.838408e-02). BS=1 tokens: [' span', 'ned', ' from', ' the', ' ', '1', '4', 'th'] BS=N tokens: [' span', 'ned', ' from', ' the', ' ', '1', '4', 'th'] [FAIL] Prompt 16 Step 0: Bitwise mismatch (abs diff=7.048920e-04). BS=1 tokens: [' a', ' fundamental', ' theory', ' in', ' physics', ' that', ' provides', ' a'] BS=N tokens: [' a', ' fundamental', ' theory', ' in', ' physics', ' that', ' provides', ' a'] [FAIL] Prompt 17 Step 0: Bitwise mismatch (abs diff=4.000474e-03). BS=1 tokens: [' a', ' curious', ' little', ' robot', ' named', ' Z', 'ippy', '.'] BS=N tokens: [' a', ' curious', ' little', ' robot', ' named', ' Z', 'ippy', '.'] [FAIL] Prompt 18 Step 0: Bitwise mismatch (abs diff=4.461013e-03). BS=1 tokens: [' green', ' plants', ',', ' algae', ',', ' and', ' some', ' bacteria'] BS=N tokens: [' green', ' plants', ',', ' algae', ',', ' and', ' some', ' bacteria'] [FAIL] Prompt 19 Step 0: Bitwise mismatch (abs diff=7.484198e-02). BS=1 tokens: [' some', ' apples', '.', ' ', ' This', ' is', ' an', ' interesting'] BS=N tokens: [' some', ' apples', '.', ' ', ' This', ' is', ' an', ' interesting'] [FAIL] Prompt 20 Step 0: Bitwise mismatch (abs diff=6.425381e-04). BS=1 tokens: [' the', ' long', '-lo', 'st', ' planet', ' of', ' Earth', ','] BS=N tokens: [' the', ' long', '-lo', 'st', ' planet', ' of', ' Earth', ','] [FAIL] Prompt 21 Step 0: Bitwise mismatch (abs diff=1.037071e-01). BS=1 tokens: [' for', ' each', ' element', ',', ' it', ' checks', ' if', ' there'] BS=N tokens: [' for', ' each', ' element', ',', ' it', ' checks', ' if', ' there'] [FAIL] Prompt 22 Step 0: Bitwise mismatch (abs diff=7.279223e-05). BS=1 tokens: [' Paris', '.', ' ', ' This', ' is', ' an', ' interesting', ' topic'] BS=N tokens: [' Paris', '.', ' ', ' This', ' is', ' an', ' interesting', ' topic'] [FAIL] Prompt 23 Step 0: Bitwise mismatch (abs diff=4.689336e-03). BS=1 tokens: [' are', ' responsible', ' for', ' processing', ' and', ' transmitting', ' information', '.'] BS=N tokens: [' are', ' responsible', ' for', ' processing', ' and', ' transmitting', ' information', '.'] [PASS] Prompt 24: tokens and logprobs match exactly. [FAIL] Prompt 25 Step 0: Bitwise mismatch (abs diff=1.175986e-04). BS=1 tokens: [' Paris', '.', ' ', ' This', ' is', ' an', ' interesting', ' topic'] BS=N tokens: [' Paris', '.', ' ', ' This', ' is', ' an', ' interesting', ' topic'] [FAIL] Prompt 26 Step 0: Bitwise mismatch (abs diff=7.413387e-02). BS=1 tokens: [' some', ' apples', '.', ' ', ' This', ' is', ' an', ' interesting'] BS=N tokens: [' some', ' apples', '.', ' ', ' This', ' is', ' an', ' interesting'] [FAIL] Prompt 27 Step 0: Bitwise mismatch (abs diff=2.929689e-02). BS=1 tokens: [' my', ' current', ' one', ' is', ' starting', ' to', ' lag', ','] BS=N tokens: [' my', ' current', ' one', ' is', ' starting', ' to', ' lag', ','] [PASS] Prompt 28: tokens and logprobs match exactly. [PASS] Prompt 29: tokens and logprobs match exactly. [FAIL] Prompt 30 Step 0: Bitwise mismatch (abs diff=9.555101e-03). BS=1 tokens: [' create', ' a', ' class', ' for', ' the', ' nodes', ' of', ' the'] BS=N tokens: [' create', ' a', ' class', ' for', ' the', ' nodes', ' of', ' the'] [FAIL] Prompt 31 Step 0: Bitwise mismatch (abs diff=1.930434e-02). BS=1 tokens: [' the', ' long', ' days', ' and', ' warm', ' weather', '.', ' I'] BS=N tokens: [' the', ' long', ' days', ' and', ' warm', ' weather', '.', ' I'] ============================================================ [RESULT] 22/32 prompts FAILED — batch invariance is NOT satisfied.

Btw, I found that only All2all combine use reduce_scatterv() by searching reduce_scatterv in the repository.

I meant we might not want to change the default behivior for other cases (without dp, eg.) unless fully tested and showing performance improvement.

I see. My new commit should address this. Please take a look. 🙏🏻

mergify · 2026-06-30T21:22:52Z

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @shijuzhao.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork

yewentao256 · 2026-07-02T14:49:49Z

@@ -382,7 +383,14 @@ def reduce_scatterv(
            output = torch.empty(
                output_shape, dtype=input_tensor.dtype, device=input_tensor.device
            )
-            if sizes is not None and sizes.count(sizes[0]) != len(sizes):
+            dp_world_size = get_dp_group().world_size


get_dp_group() will assert when DP is None

Yes, you are right. I found that self.world_size is DP world size when sequence parallel is disabled, and self.world_size is EP world size when sequence parallel is enabled. I have changed dp_world_size to world_size in latest push.

Here is the only place where reduce_scatterv() is called.
https://github.com/vllm-project/vllm/blob/22d78df13474395e26778049c5253c759fb2dc7d/vllm/distributed/device_communicators/all2all.py#L125-L138

When is_sequence_parallel is False, dist_group = get_dp_group(), so get_dp_group().world_size == self.world_size.

When is_sequence_parallel is True, dist_group = get_ep_group(). In this case (DP=2, TP=2, EP=4), we also need this fix.

VLLM_BATCH_INVARIANT=1 vllm serve --model Qwen/Qwen3-30B-A3B-Instruct-2507 --data-parallel-size 2 --tensor-parallel-size 2 --enable-expert-parallel

This configuration will enable sequence parallel automatically (See ParallelConfig.use_sequence_parallel_moe() in vllm/config/parallel.py). Without this fix, 21 of the 32 runs will diverge from the batch-size 1 version. Otherwise, it will pass. The root cause is the same as above.

============================================================ Batch Invariance Test ============================================================ Server URL : http://0.0.0.0:8000/v1 Model : Qwen/Qwen3-30B-A3B-Instruct-2507 Num prompts: 32 Max tokens : 8 Seed : 42 Temperature: 0.6 Top-p : 1.0 Logprobs : 5 ============================================================ [INFO] Server reachable. Available models: ['Qwen/Qwen3-30B-A3B-Instruct-2507'] [INFO] Starting BS=1 requests for 32 prompts ... BS=1 progress: 8/32 BS=1 progress: 16/32 BS=1 progress: 24/32 BS=1 progress: 32/32 [INFO] Starting BS=N (batch of 32) request ... BS=N done. [INFO] Comparing BS=1 vs BS=N ... [FAIL] Prompt 0 Step 0: Bitwise mismatch (abs diff=8.507037e-02). BS=1 tokens: [' create', ' a', ' class', ' for', ' the', ' nodes', ' of', ' the'] BS=N tokens: [' create', ' a', ' class', ' for', ' the', ' nodes', ' of', ' the'] [FAIL] Prompt 1 Step 0: Bitwise mismatch (abs diff=1.310429e-06). BS=1 tokens: [' Paris', '.', ' ', ' This', ' is', ' an', ' interesting', ' topic'] BS=N tokens: [' Paris', '.', ' ', ' This', ' is', ' an', ' interesting', ' topic'] [FAIL] Prompt 2 Step 0: Bitwise mismatch (abs diff=5.714893e-03). BS=1 tokens: [' some', ' apples', '.', ' ', ' This', ' is', ' an', ' interesting'] BS=N tokens: [' some', ' apples', '.', ' ', ' This', ' is', ' an', ' interesting'] [FAIL] Prompt 3 Step 0: Bitwise mismatch (abs diff=2.191085e-02). BS=1 tokens: [' the', ' long', ' days', ' and', ' warm', ' weather', '.', ' I'] BS=N tokens: [' the', ' long', ' days', ' and', ' warm', ' weather', '.', ' I'] [FAIL] Prompt 4 Step 1: Bitwise mismatch (abs diff=5.436087e-02). BS=1 tokens: [' the', ' long', '-', 'ago', ' days', ' of', ' his', ' youth'] BS=N tokens: [' the', ' long', '-', 'ago', ' days', ' of', ' his', ' youth'] [FAIL] Prompt 5 Step 1: Bitwise mismatch (abs diff=5.276065e-03). BS=1 tokens: [' create', ' a', ' class', ' for', ' the', ' nodes', ' of', ' the'] BS=N tokens: [' create', ' a', ' class', ' for', ' the', ' nodes', ' of', ' the'] [FAIL] Prompt 6 Step 1: Bitwise mismatch (abs diff=7.893324e-02). BS=1 tokens: [' the', ' long', '-lo', 'st', ' planet', ' of', ' Earth', ','] BS=N tokens: [' the', ' long', '-lo', 'st', ' planet', ' of', ' Earth', ','] [FAIL] Prompt 7 Step 0: Bitwise mismatch (abs diff=1.418853e-02). BS=1 tokens: [' some', ' apples', '.', ' ', ' This', ' is', ' an', ' interesting'] BS=N tokens: [' some', ' apples', '.', ' ', ' This', ' is', ' an', ' interesting'] [FAIL] Prompt 8 Step 1: Bitwise mismatch (abs diff=5.436087e-02). BS=1 tokens: [' the', ' long', '-', 'ago', ' days', ' of', ' his', ' youth'] BS=N tokens: [' the', ' long', '-', 'ago', ' days', ' of', ' his', ' youth'] [FAIL] Prompt 9 Step 0: Bitwise mismatch (abs diff=5.949271e-02). BS=1 tokens: [' human', ' activities', ' such', ' as', ' burning', ' fossil', ' fuels', ','] BS=N tokens: [' human', ' activities', ' such', ' as', ' burning', ' fossil', ' fuels', ','] [FAIL] Prompt 10 Step 0: Bitwise mismatch (abs diff=2.123064e-02). BS=1 tokens: [' span', 'ned', ' from', ' the', ' ', '1', '4', 'th'] BS=N tokens: [' span', 'ned', ' from', ' the', ' ', '1', '4', 'th'] [FAIL] Prompt 11 Step 1: Bitwise mismatch (abs diff=6.176896e-03). BS=1 tokens: [' a', ' fundamental', ' theory', ' in', ' physics', ' that', ' provides', ' a'] BS=N tokens: [' a', ' fundamental', ' theory', ' in', ' physics', ' that', ' provides', ' a'] [FAIL] Prompt 12 Step 1: Bitwise mismatch (abs diff=6.421864e-03). BS=1 tokens: [' are', ' responsible', ' for', ' processing', ' and', ' transmitting', ' information', '.'] BS=N tokens: [' are', ' responsible', ' for', ' processing', ' and', ' transmitting', ' information', '.'] [FAIL] Prompt 13 Step 0: Bitwise mismatch (abs diff=4.430853e-03). BS=1 tokens: [' green', ' plants', ',', ' algae', ',', ' and', ' some', ' bacteria'] BS=N tokens: [' green', ' plants', ',', ' algae', ',', ' and', ' some', ' bacteria'] [FAIL] Prompt 14 Step 0: Bitwise mismatch (abs diff=1.927078e-02). BS=1 tokens: [' are', ' responsible', ' for', ' processing', ' and', ' transmitting', ' information', '.'] BS=N tokens: [' are', ' responsible', ' for', ' processing', ' and', ' transmitting', ' information', '.'] [FAIL] Prompt 15 Step 0: Bitwise mismatch (abs diff=5.237126e-02). BS=1 tokens: [' span', 'ned', ' from', ' the', ' ', '1', '4', 'th'] BS=N tokens: [' span', 'ned', ' from', ' the', ' ', '1', '4', 'th'] [PASS] Prompt 16: tokens and logprobs match exactly. [PASS] Prompt 17: tokens and logprobs match exactly. [PASS] Prompt 18: tokens and logprobs match exactly. [FAIL] Prompt 19 Step 0: Bitwise mismatch (abs diff=6.083012e-03). BS=1 tokens: [' some', ' apples', '.', ' ', ' This', ' is', ' an', ' interesting'] BS=N tokens: [' some', ' apples', '.', ' ', ' This', ' is', ' an', ' interesting'] [PASS] Prompt 20: tokens and logprobs match exactly. [PASS] Prompt 21: tokens and logprobs match exactly. [PASS] Prompt 22: tokens and logprobs match exactly. [PASS] Prompt 23: tokens and logprobs match exactly. [PASS] Prompt 24: tokens and logprobs match exactly. [PASS] Prompt 25: tokens and logprobs match exactly. [PASS] Prompt 26: tokens and logprobs match exactly. [FAIL] Prompt 27 Step 0: Bitwise mismatch (abs diff=5.373359e-05). BS=1 tokens: [' my', ' current', ' one', ' is', ' starting', ' to', ' lag', ','] BS=N tokens: [' my', ' current', ' one', ' is', ' starting', ' to', ' lag', ','] [FAIL] Prompt 28 Step 0: Bitwise mismatch (abs diff=8.940119e-03). BS=1 tokens: [' a', ' fundamental', ' theory', ' in', ' physics', ' that', ' provides', ' a'] BS=N tokens: [' a', ' fundamental', ' theory', ' in', ' physics', ' that', ' provides', ' a'] [FAIL] Prompt 29 Step 0: Bitwise mismatch (abs diff=2.417713e-06). BS=1 tokens: [' green', ' plants', ',', ' algae', ',', ' and', ' some', ' bacteria'] BS=N tokens: [' green', ' plants', ',', ' algae', ',', ' and', ' some', ' bacteria'] [PASS] Prompt 30: tokens and logprobs match exactly. [FAIL] Prompt 31 Step 0: Bitwise mismatch (abs diff=2.191085e-02). BS=1 tokens: [' the', ' long', ' days', ' and', ' warm', ' weather', '.', ' I'] BS=N tokens: [' the', ' long', ' days', ' and', ' warm', ' weather', '.', ' I'] ============================================================ [RESULT] 21/32 prompts FAILED — batch invariance is NOT satisfied.

yewentao256 · 2026-07-09T18:48:55Z

+
+                chunk = input_tensor[split_offset : split_offset + split_size, ...]
+                if dst == root:
+                    output_tensor.copy_(chunk)


Should this use stream as well?

Thanks for catching this! I've updated the code accordingly.

yewentao256

LGTM, thanks for the work!

shijuzhao · 2026-07-13T11:14:17Z

Thanks for the thorough and careful review! I especially appreciate you pointing out those edge cases I initially missed—definitely made the code more robust. Learned a lot! 👍🏻

shijuzhao · 2026-08-04T02:04:59Z

@khluu Appreciate the review! Noticed the CI failure. Based on the stack trace, the error is occurring in compile/fullgraph/test_basic_correctness.py entrypoints/serve/instrumentator/test_metrics.py models/language/generation/test_hybrid.py and compile/h100/test_startup.py, which aren't affected by this patch (we don't hit that code path if VLLM_BATCH_INVARIANT=0). Might be a pre-existing flake. Happy to help debug if needed, but likely safe to ignore for this PR.

aoshen02 · 2026-08-20T23:14:10Z

Let's try to merge it as soon as possible.

aoshen02 · 2026-08-20T23:17:29Z

@shijuzhao Could you rebase the code and then run the CI again, I think it might help to make the ci pass.

Signed-off-by: shijuzhao <758710341@qq.com> Signed-off-by: shijuzhao <shijuzhao@tencent.com>

aoshen02 · 2026-08-21T09:38:14Z

/ci run

github-actions · 2026-08-21T09:38:33Z

✅ Triggered Buildkite CI #84991 for commit 83d73f328f3b.

…_INVARIANT (vllm-project#45683) Signed-off-by: shijuzhao <shijuzhao@tencent.com> Co-authored-by: shijuzhao <shijuzhao@tencent.com> Signed-off-by: Wyett <wyettzeng@gmail.com>

…_INVARIANT (vllm-project#45683) Signed-off-by: shijuzhao <shijuzhao@tencent.com> Co-authored-by: shijuzhao <shijuzhao@tencent.com> Signed-off-by: khushali9 <khushali.desai9@gmail.com>

…_INVARIANT (vllm-project#45683) Signed-off-by: shijuzhao <shijuzhao@tencent.com> Co-authored-by: shijuzhao <shijuzhao@tencent.com>

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[Feature]: Batch Invariant Feature in DP+EP #30321

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[RFC]: Logprobs/Logits Semantics and Determinism Across the vLLM Ecosystem #42259

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[Bug]: VLLM_BATCH_INVARIANT=1 not deterministic under tensor parallelism (TP>1); fuse_allreduce_rms fused all-reduce is the cause #51290

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Deterministic MoE combine (reduce_scatterv) under VLLM_BATCH_INVARIANT

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Signed-off-by: shijuzhao <758710341@qq.com> Signed-off-by: shijuzhao <shijuzhao@tencent.com>

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Isotr0py merged commit cda3868 into vllm-project:main Aug 21, 2026
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yonromai mentioned this pull request Aug 27, 2026

Support Hero GrugMoE inference marin-community/vllm#51

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[Bugfix][MoE] Deterministic expert selection in the grouped_topk Python fallback #55514

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LioEinaudi mentioned this pull request Sep 11, 2026

[Bug]: Batch invariance is broken when sequence parallelism / async TP is enabled (VLLM_BATCH_INVARIANT=1 + pass_config.enable_sp) #56370

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GuoCheng24 mentioned this pull request Sep 11, 2026

[CI Test] Mark batch invariance test flaky #46530

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