[Bugfix][Benchmark] Make streaming TTFT/E2E latency accounting consistent across endpoints

[surajm20061998]

Purpose

vllm/benchmarks/serve.py derives TPOT from the end of the request:

latency_minus_ttft = outputs[i].latency - outputs[i].ttft
tpot = latency_minus_ttft / (output_len - 1)

For that to mean "average inter-token latency", latency - ttft has to equal
sum(itl). Today it does not, and it fails differently per endpoint, so E2EL
and TPOT are not comparable between an openai run and an openai-chat run.

Two independent causes:

1. TTFT is read off a second clock call (/v1/completions).

timestamp = time.perf_counter()          # chunk arrival; seeds the ITL chain
if not first_chunk_received:
    first_chunk_received = True
    ttft = time.perf_counter() - st      # a different, later reading
    output.ttft = ttft
...
most_recent_timestamp = timestamp        # the earlier reading

TTFT is measured from one reading while the ITL chain continues from another,
so latency - ttft comes up short by the gap between the two calls.
async_request_openai_chat_completions and async_request_openai_audio already
do the right thing (output.ttft = timestamp - st), so this aligns completions
with its siblings rather than introducing a new convention.

2. The trailing usage chunk extends E2E latency (chat and audio).

vllm bench serve always sends stream_options.include_usage, so every stream
ends with a choice-less usage chunk after the last token. In chat and audio,
most_recent_timestamp = timestamp sits outside the if choices: branch, so
that trailer advances the end of the request; output.latency therefore runs
past the final token. async_request_openai_completions updates it inside
the branch and stops at the last token. serve.py assigns
e2els.append(outputs[i].latency) directly, so this lands in reported E2EL and
TPOT.

I fixed it in the direction that stops at the last token, because the
alternative — having completions also count the usage chunk — would break the
identity on both endpoints instead of fixing it: the usage gap appears in
latency but never in any itl. The loop already refuses to let the [DONE]
sentinel move the clock; the usage chunk is the same category of non-token
trailer.

benchmarks/backend_request_func.py carries the same two defects and is still
imported by benchmark_prefix_caching.py and
benchmark_serving_structured_output.py, so it gets the identical hunks (plus
the same one-line TTFT fix in async_request_tgi). Happy to split that file
into its own PR if you'd rather keep this one to vllm/benchmarks/.

Magnitude — deliberately not overstated

This is a correctness and cross-endpoint-comparability fix, not a
performance claim. chat_completion/serving.py yields the usage chunk
immediately after the final content chunk in the same generator with no engine
await between, so in normal operation the error is tens of microseconds — I
measured ~24 µs on a 200 ms request, about 0.01%. The gap is not bounded by
anything, though: it is whatever separates two SSE writes, which on a saturated
client event loop is not guaranteed to stay small.

The lasting value is the test: endpoint_request_func.py currently has no test
coverage of its timing accounting at all, so nothing was stopping this from
drifting further.

Not a duplicate

Per AGENTS.md I checked:

gh pr list --repo vllm-project/vllm --state open --search "endpoint_request_func"
gh pr list --repo vllm-project/vllm --state open --search "backend_request_func"
gh pr list --repo vllm-project/vllm --state open --search "usage chunk latency"
gh pr list --repo vllm-project/vllm --state open --search "benchmark ttft latency"

The only open PRs in this area are #42661 and #46652, which both address
a different bug: servers batching multiple tokens into one SSE chunk, making
ITL per-chunk rather than per-token. Neither touches which clock reading TTFT
uses, nor where the request is considered to end. They are complementary — with
either merged, sum(itl) still spans the same decode window, so the identity
asserted here continues to hold.

#46652 also adds tests/benchmarks/test_endpoint_request_func.py; this PR adds
test_endpoint_request_func_timing.py, so there is no filename collision, and
the two suites could be folded together later if that is preferred.

Test Plan

New: tests/benchmarks/test_endpoint_request_func_timing.py, parametrized over
all three streaming request functions (completions, chat, audio). CPU-only — no
GPU, model, or socket; the request functions are driven against a fake session.

The exactness tests substitute a scripted clock that advances by a fixed
tick on every read. What a code path observes then depends only on how many
times it reads the clock, so a stray or misattributed read shows up as a whole
tick of drift instead of sub-microsecond jitter. That makes the assertions
exact and free of timing flakiness.

1. test_decode_span_identity_is_exact — (latency - ttft) - sum(itl) == 0.
2. test_trailing_usage_chunk_does_not_extend_latency — E2E latency stops at
   the final token.
3. test_decode_span_identity_holds_with_real_clock — same identity against the
   real clock with real inter-chunk gaps.
4. test_usage_only_stream_is_not_reported_as_success — a stream with no token
   chunk fails rather than reporting a zero-duration success. The residual differences out the same
   recorded timestamps, so jitter cancels and only float rounding remains; the
   1 µs bound is ample rather than tight.

uv venv --python 3.12 && source .venv/bin/activate
VLLM_TARGET_DEVICE=empty uv pip install -e . --no-build-isolation
.venv/bin/python -m pytest tests/benchmarks/test_endpoint_request_func_timing.py -v
.venv/bin/python -m pytest tests/benchmarks/test_audio_dataset.py -v   # sibling suite, same module
pre-commit run --files vllm/benchmarks/lib/endpoint_request_func.py \
    benchmarks/backend_request_func.py \
    tests/benchmarks/test_endpoint_request_func_timing.py

Test Result

On unpatched main (f4eccda), the new tests fail with the defects visible as
whole ticks of the scripted clock — negative for the extra TTFT read, positive
for the counted usage chunk:

FAILED test_decode_span_identity_is_exact[completions]
  AssertionError: completions: (latency - ttft) - sum(itl) = -1.0
FAILED test_decode_span_identity_is_exact[chat]
  AssertionError: chat: (latency - ttft) - sum(itl) = 1.0
FAILED test_decode_span_identity_is_exact[audio]
  AssertionError: audio: (latency - ttft) - sum(itl) = 1.0
8 failed, 1 passed

With the fix applied:

tests/benchmarks/test_endpoint_request_func_timing.py 12 passed
tests/benchmarks/test_audio_dataset.py                 8 passed   (no regression)
(20 passed total)

Reverting only the two source files and re-running reproduces the 8 failures,
confirming the tests actually exercise the fix.

Independently, driving the unpatched request functions against a local SSE
server over a real socket, residual (latency - ttft) - sum(itl):

scenario	completions	chat
usage chunk emitted immediately (realistic)	−0.35 µs	+24.09 µs
usage chunk delayed 30 ms (mechanism probe)	−0.32 µs	+31 473 µs

The probe isolates the mechanism: a 30 ms delay before the usage chunk moves
chat's residual by ~30 ms and leaves completions flat. After the fix, all four
cells are 0.00 µs.

pre-commit / ruff check / ruff format --check: clean on all three files.

Model evaluation

Not applicable. This changes only how the benchmark client measures latency
on the wire. No engine, scheduler, sampling, or serving path is touched, so
model outputs and accuracy are unaffected.

AI assistance

This change was developed with AI assistance. I have reviewed every changed
line, run the tests above myself, and can defend the change end-to-end.

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---

📝 Summary

Summary by CodeRabbit

• Bug Fixes

  • Improved streaming latency measurements for completions, chat completions, and audio requests.
  • Time-to-first-token and inter-token latency calculations now use consistent timestamps.
  • Trailing usage data no longer extends the reported request duration.
  • Streams containing only usage data are now correctly reported as unsuccessful instead of showing zero latency.

• Tests

  • Added coverage validating latency calculations across streaming request types and timing scenarios.

Walkthrough

The streaming benchmark handlers now reuse captured timestamps for TTFT, stop latency measurement at the final token, and reject usage-only streams. New tests validate these timing invariants for completions, chat completions, and audio requests.

Changes

Streaming timing accounting

Layer / File(s)	Summary
Captured timestamp timing benchmarks/backend_request_func.py, vllm/benchmarks/lib/endpoint_request_func.py	TGI and OpenAI completion handlers compute TTFT from the captured chunk timestamp.
Token latency boundaries benchmarks/backend_request_func.py, vllm/benchmarks/lib/endpoint_request_func.py	Chat and audio handlers update the request-end timestamp only for token chunks and mark usage-only streams as failures.
Timing invariant validation tests/benchmarks/test_endpoint_request_func_timing.py	Tests use scripted and real clocks to verify decode-span identity, final-token latency, and usage-only stream failure handling.

Estimated code review effort: 3 (Moderate) | ~20 minutes

Merge Risk: ⚪ Minimal · up to bfe61

Streaming benchmark timing now ends at the final token and usage-only streams are reported as failures; no current merge-blocking risk is identified.

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 21.43% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 28 functions across 3 files.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Title check	✅ Passed	The title clearly summarizes the main change: consistent streaming TTFT and end-to-end latency accounting across benchmark endpoints.
Description check	✅ Passed	The description directly explains the timing defects, fixes, affected endpoints, tests, and validation results.

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Inline comments:
In `@benchmarks/backend_request_func.py`:
- Around line 454-456: Update async_request_openai_chat_completions and
async_request_openai_audio in benchmarks/backend_request_func.py at lines
454-456 and 565-568 to track first_chunk_received, reject streams containing
only a usage chunk, and return the same no-token failure result as
async_request_openai_completions instead of success with zero latency. Add
usage-only SSE coverage for both handlers in
tests/benchmarks/test_endpoint_request_func_timing.py at lines 256-258.

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[DarkLight1337]

Have you verified that these tests actually fail without your changes? (i.e. they are effective regression tests)

[surajm20061998]

Yes, I checked. If I undo the fix in vllm/benchmarks/lib/endpoint_request_func.py, 8 of the tests fail.

[DarkLight1337]

Thanks for fixing!

[DarkLight1337]

/ci run

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✅ Triggered Buildkite CI #88598 for commit e6c8f546a802.