[CI] Increase the threshold of the MTEB RERANK tests

[noooop]

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.

Purpose

fix Nightly build to run all tests

Just as I said in #19344.

I don't know why, but the differences between the models on local and CI machines are greater than those between fp16 and fp32.

try MTEB_RERANK_TOL = 1e-3 -> MTEB_RERANK_TOL = 2e-3

• test_bge_reranker_v2_gemma
  ci
  [2025-07-08T06:18:58Z] FAILED models/language/pooling/test_bge_reranker_v2_gemma.py::test_rerank_models_mteb[model_info0] - AssertionError
  [2025-07-08T05:22:14Z] VLLM: torch.float16 0.33624
  [2025-07-08T05:22:14Z] SentenceTransformers: torch.float32 0.33757
  [2025-07-08T05:22:14Z] Difference: 0.0013299999999999979

local
pytest -s -vvv tests/models/language/pooling/test_bge_reranker_v2_gemma.py
VLLM: torch.float16 0.33913
SentenceTransformers: torch.float32 0.33956
Difference: 0.00042999999999998595

• test_qwen3_reranker

ci
[2025-07-08T06:18:58Z] FAILED models/language/pooling/test_qwen3_reranker.py::test_rerank_models_mteb[model_info0] - AssertionError
[2025-07-08T06:12:54Z] VLLM: torch.float32 0.25841
[2025-07-08T06:12:54Z] SentenceTransformers: torch.float32 0.25736
[2025-07-08T06:12:54Z] Difference: -0.0010499999999999954

local
pytest -s -vvv tests/models/language/pooling/test_qwen3_reranker.py
VLLM: torch.bfloat16 0.26518
SentenceTransformers: torch.float32 0.26513
Difference: -5.0000000000050004e-05

Test Plan

Test Result

(Optional) Documentation Update

[gemini-code-assist]

Summary of Changes

Hello @noooop, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request aims to fix nightly build failures related to MTEB reranking tests by increasing the tolerance threshold. Additionally, it removes unnecessary dtype specifications from the model configurations, likely to simplify the test setup.

Highlights

• MTEB Rerank Test Tolerance: Increased the tolerance for the MTEB RERANK test from 1e-3 to 2e-3 in tests/models/language/pooling/mteb_utils.py to address CI failures.
• Removed dtype specification: Removed the dtype specification from several RerankModelInfo instances in tests/models/language/pooling/test_baai.py, tests/models/language/pooling/test_jina.py, and tests/models/language/pooling/test_qwen3_reranker.py.

Using Gemini Code Assist

The full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips.

Invoking Gemini

You can request assistance from Gemini at any point in your pull request via creating an issue comment (i.e. comment on the pull request page) using either /gemini <command> or @gemini-code-assist <command>. Below is a summary of the supported commands.

Feature	Command	Description
Code Review	/gemini review	Performs a code review for the current pull request in its current state.
Pull Request Summary	/gemini summary	Provides a summary of the current pull request in its current state.
Comment	@gemini-code-assist	Responds in comments when explicitly tagged, both in issue comments and review comments.
Help	/gemini help	Displays a list of available commands.

Customization

To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a .gemini/ folder in the base of the repository. Detailed instructions can be found here.

Limitations & Feedback

Gemini Code Assist is currently in preview and may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments to provide feedback.

You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension.

Footnotes

1. Review the Privacy Notices, Generative AI Prohibited Use Policy, Terms of Service, and learn how to configure Gemini Code Assist in GitHub here. Gemini can make mistakes, so double check it and use code with caution. ↩

[gemini-code-assist]

Code Review

This pull request increases the tolerance for MTEB rerank model comparisons to address a failing CI test. The changes also remove explicit dtype=\"float32\" specifications for several reranker models. A follow-up investigation into the root cause of the environmental discrepancies is recommended.

[noooop]

@DarkLight1337

Help enable the Language Models Test (Extended Pooling) so that we can ensure all tests remain passing.

[github-actions]

👋 Hi! Thank you for contributing to the vLLM project.

💬 Join our developer Slack at https://slack.vllm.ai to discuss your PR in #pr-reviews, coordinate on features in #feat- channels, or join special interest groups in #sig- channels.

Just a reminder: PRs would not trigger full CI run by default. Instead, it would only run fastcheck CI which starts running only a small and essential subset of CI tests to quickly catch errors. You can run other CI tests on top of those by going to your fastcheck build on Buildkite UI (linked in the PR checks section) and unblock them. If you do not have permission to unblock, ping simon-mo or khluu to add you in our Buildkite org.

Once the PR is approved and ready to go, your PR reviewer(s) can run CI to test the changes comprehensively before merging.

To run CI, PR reviewers can either: Add ready label to the PR or enable auto-merge.

🚀

[DarkLight1337]

Tests passed