[Docs] Add Phi-3.5-mini-instruct to batch invariance tested models

[yuvalluria]

Description

Adds microsoft/Phi-3.5-mini-instruct to the list of tested models for batch invariance.

Test Results

Model: microsoft/Phi-3.5-mini-instruct (3.8B)

Results:

Trial 1: MATCH
Trial 2: MATCH
Trial 3: MATCH
Trial 4: MATCH
Trial 5: MATCH

[determinism] total=5, passed=5, failed=0, max_batch_size=8

✓ TEST PASSED - Batch invariance verified!

Test Configuration:

• Hardware: 4x NVIDIA A10G GPUs (23GB each)
• Tensor Parallelism: 4
• Backend: FLASH_ATTN
• vLLM Version: v0.21.0
• Environment: VLLM_BATCH_INVARIANT=1, VLLM_USE_FLASHINFER_SAMPLER=0
• Temperature: 0.0 (greedy decoding)

Test Methodology:
Used the official test script from tests/v1/determinism/test_batch_invariance.py with needle-in-batch testing methodology.

Motivation

Phi-3.5-mini-instruct is a popular small model (3.8B) from Microsoft, ideal for edge deployments and applications requiring deterministic inference with batch invariance.

Closes part of #27433

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[mergify]

Documentation preview: https://vllm--46396.org.readthedocs.build/en/46396/

[yewentao256]

I am not 100% sure about this model, please test with all cases in the script, attach with full command and full output log here.

[yuvalluria]

Test Command

export VLLM_BATCH_INVARIANT=1
export VLLM_USE_FLASHINFER_SAMPLER=0
export VLLM_TEST_MODEL="microsoft/Phi-3.5-mini-instruct"
export VLLM_NEEDLE_TRIALS=5
export VLLM_NEEDLE_BATCH_SIZE=8
export VLLM_MAX_MODEL_LEN=2048
export VLLM_TP_SIZE=4

python3 tests/v1/determinism/test_batch_invariance.py

Full Output Log

================================================================================
BATCH INVARIANCE TEST: microsoft/Phi-3.5-mini-instruct
================================================================================
Model: microsoft/Phi-3.5-mini-instruct
Trials: 5
Max Batch Size: 8
Temperature: 0.0
================================================================================

Initializing LLM with tensor_parallel_size=4...
INFO 06-22 16:18:36 [utils.py:240] non-default args: {'trust_remote_code': True, 'max_model_len': 2048, 'tensor_parallel_size': 4, 'max_num_seqs': 8, 'disable_log_stats': True, 'enforce_eager': True, 'model': 'microsoft/Phi-3.5-mini-instruct'}
...
(EngineCore pid=1329) INFO 06-22 16:19:14 [kv_cache_utils.py:1710] GPU KV cache size: 197,195 tokens
(EngineCore pid=1329) INFO 06-22 16:19:14 [kv_cache_utils.py:1711] Maximum concurrency for 2,048 tokens per request: 96.29x
...
✓ LLM initialized

Generating baseline (batch_size=1)...
Baseline: 10-year-old boy named Timmy who loved to play with his toy cars. He had a collec...

Trial 1: MATCH
Trial 2: MATCH
Trial 3: MATCH
Trial 4: MATCH
Trial 5: MATCH

[determinism] total=5, passed=5, failed=0, max_batch_size=8

✓ TEST PASSED - Batch invariance verified!

[yewentao256]

Thanks, similar to what you did for another PR, python3 test_batch_invariance.py is not the correct command, you should test using pytest test_batch_invariance.py and gather the summary like 13 passed, 30 warnings in 471.33s (0:07:51).

[hai19851221-lgtm]

好的，感谢 Wentao Ye ***@***.***>于2026年6月23日 周二20:57写道：

…

***@***.**** commented on this pull request. Thanks, similar to what you did for another PR, python3 test_batch_invariance.py is not the correct command, you should test using pytest test_batch_invariance.py and gather the summary like 13 passed, 30 warnings in 471.33s (0:07:51). — Reply to this email directly, view it on GitHub <#46396?email_source=notifications&email_token=B7AO2GWFAVOJKLNHHSHC3TD5BKEFJA5CNFSNUABKM5UWIORPF5TWS5BNNB2WEL2QOVWGYUTFOF2WK43UKJSXM2LFO4XTINJVGM4TMOBVGUY2M4TFMFZW63VKON2WE43DOJUWEZLEUVSXMZLOOSWGM33PORSXEX3DNRUWG2Y#pullrequestreview-4553968551>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/B7AO2GWEOI5XSAK37C2MGOT5BKEFJAVCNFSNUABFKJSXA33TNF2G64TZHM2TSOJVGQ3TKMJYHNEXG43VMU5TINZRHE2TMMJXHE22C5QC> . You are receiving this because you are subscribed to this thread.Message ID: ***@***.***>

[yuvalluria]

Tested on H100 NVL GPU (NVIDIA H100 NVL, 95GB VRAM):

VLLM_TEST_MODEL=microsoft/Phi-3.5-mini-instruct pytest test_batch_invariance.py -v

============================= test session starts ==============================
platform linux -- Python 3.12.13, pytest-9.1.1, pluggy-1.6.0
collected 16 items

test_batch_invariance.py::test_v1_generation_is_deterministic_across_batch_sizes_with_needle[FLASH_ATTN] PASSED [  6%]
test_batch_invariance.py::test_v1_generation_is_deterministic_across_batch_sizes_with_needle[TRITON_ATTN] PASSED [ 12%]
test_batch_invariance.py::test_v1_generation_is_deterministic_across_batch_sizes_with_needle[FLEX_ATTENTION] PASSED [ 18%]
test_batch_invariance.py::test_logprobs_bitwise_batch_invariance_bs1_vs_bsN[16-16-FLASH_ATTN] PASSED [ 25%]
test_batch_invariance.py::test_logprobs_bitwise_batch_invariance_bs1_vs_bsN[16-16-TRITON_ATTN] PASSED [ 31%]
test_batch_invariance.py::test_logprobs_bitwise_batch_invariance_bs1_vs_bsN[16-16-FLEX_ATTENTION] PASSED [ 37%]
test_batch_invariance.py::test_logprobs_bitwise_batch_invariance_bs1_vs_bsN[8-16-FLASH_ATTN] PASSED [ 43%]
test_batch_invariance.py::test_logprobs_bitwise_batch_invariance_bs1_vs_bsN[8-16-TRITON_ATTN] PASSED [ 50%]
test_batch_invariance.py::test_logprobs_bitwise_batch_invariance_bs1_vs_bsN[8-16-FLEX_ATTENTION] PASSED [ 56%]
test_batch_invariance.py::test_simple_generation[FLASH_ATTN] PASSED      [ 62%]
test_batch_invariance.py::test_simple_generation[TRITON_ATTN] PASSED     [ 68%]
test_batch_invariance.py::test_simple_generation[FLEX_ATTENTION] PASSED  [ 75%]
test_batch_invariance.py::test_logprobs_without_batch_invariance_should_fail[FLASH_ATTN] PASSED [ 81%]
test_batch_invariance.py::test_logprobs_without_batch_invariance_should_fail[TRITON_ATTN] PASSED [ 87%]
test_batch_invariance.py::test_logprobs_without_batch_invariance_should_fail[FLEX_ATTENTION] PASSED [ 93%]
test_batch_invariance.py::test_decode_logprobs_match_prefill_logprobs[FLASH_ATTN] PASSED [100%]

16 passed, 16 warnings in 695.64s (0:11:35)

[yewentao256]

LGTM, thanks for the work!