Skip to content

Conversation

@slin1237
Copy link
Collaborator

What this PR does

Why we need it

Fixes #

How to test

Checklist

  • Tests added/updated (if applicable)
  • Docs updated (if applicable)
  • make test passes locally

@github-actions github-actions bot added documentation Documentation changes models Model configuration changes config Configuration changes dependencies Dependency updates labels Jan 13, 2026
@gemini-code-assist
Copy link
Contributor

Summary of Changes

Hello @slin1237, 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 introduces a new documentation artifact to systematically track the testing status of a wide array of AI models, providing a centralized and detailed overview of their compatibility and performance. Concurrently, it updates the project's Go module dependencies, likely to support new features, improve stability, or maintain compatibility with evolving external services and libraries.

Highlights

  • New Model Test Tracking Document: A new Markdown document, config/models/test-tracking.md, has been added. This comprehensive document details the testing status of 203 AI models across various vendors and architectures. It includes a summary of pass/fail/skipped/not tested counts, a master list with model specifics (size, type, GPUs, runtime, owner, notes), supported and unsupported architectures, and common failure categories.
  • Go Dependency Updates: The go.sum file has been significantly updated, reflecting a broad refresh of Go module dependencies. This includes numerous updates and additions related to Google Cloud libraries, AWS SDK components, Azure SDK, Docker, Kubernetes-related modules, and other third-party packages, ensuring the project uses up-to-date versions of its external dependencies.

🧠 New Feature in Public Preview: You can now enable Memory to help Gemini Code Assist learn from your team's feedback. This makes future code reviews more consistent and personalized to your project's style. Click here to enable Memory in your admin console.

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 by creating a comment using either /gemini <command> or @gemini-code-assist <command>. Below is a summary of the supported commands on the current page.

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 pull request 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 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. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up here.

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.

Copy link
Contributor

@gemini-code-assist gemini-code-assist bot left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Code Review

This pull request introduces a comprehensive tracking document for model testing, which is a valuable addition for monitoring test coverage and status. The document is well-structured and detailed.

I've left a couple of comments on the new markdown file regarding minor data inconsistencies that should be addressed to ensure accuracy.

Additionally, this PR includes significant changes to the go.sum file, which seems unrelated to the documentation focus. It's best practice to separate dependency updates from documentation changes into their own pull requests. This helps maintain a clean and understandable commit history. Please consider moving the go.sum changes to a separate PR.

# Model Test Tracking

**Last Updated**: 2025-12-05
**Total Models**: 203 | **Total Runtimes**: 187
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

medium

There's an inconsistency in the total number of runtimes reported. The header states Total Runtimes: 187, but the Runtime Coverage section on line 244 indicates that 163 models have a runtime. Based on the master list, 163 seems to be the correct number (203 total models - 40 models without a runtime). Please update the total in the header for consistency.

Comment on lines +339 to +349
## Failure Categories

| Category | Count | Examples |
|----------------------------|-------|--------------------------------------------------------|
| Architecture not supported | 12 | Bloom, Falcon, GPT-J, GPT-NeoX, StableLM, CodeGen, MPT |
| Download timeout | 8 | Large models, gated models, system issues |
| CUDA OOM | 3 | DeepSeek-V3, Llama-4-Maverick (non-FP8) |
| Module missing | 3 | phi-2, phi-3-mini (vllm module) |
| HuggingFace access | 2 | Gated models requiring license |
| Inference issues | 2 | FP8 NaN, warmup failures |
| Other | 10 | Various configuration/compatibility issues |
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

medium

There appear to be some inconsistencies in the failure analysis:

  • Contradiction for MPT: The Failure Categories table lists MPT as an example of an unsupported architecture. However, the Supported Text Generation Architectures table on line 294 includes MptForCausalLM, and the mpt-7b model in the master list failed due to a "Download timeout", not an architecture issue.
  • Incorrect Count: This table states there are 12 models with an unsupported architecture. However, I could only identify 7 models in the master list that failed for this reason.

Could you please verify these details and update the tables for accuracy?

@shahronak
Copy link

shahronak commented Jan 14, 2026

@slin1237 : Could you break down the the SUPPORTED MODEL markdown for model families (or vendor) for each of the modalities (text, multimodal, embed, rerank, reward). Thanks!

Also add corresponding recommended hardware shapes. Remove large models that aren't supported (like Deepseek v3)

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

config Configuration changes dependencies Dependency updates documentation Documentation changes models Model configuration changes

Projects

None yet

Development

Successfully merging this pull request may close these issues.

3 participants