Repository navigation
[DSv4.1] Add Flash model generation preset - #58
Merged
hnyls2002 merged 1 commit intoOct 13, 2026
Merged
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
[codex/claude generated]
Summary
Add the exact
deepseek-ai/DeepSeek-V4.1-Flashmodel ID to the built-in preset registry. SGLang's MMMU-Pro E2E in sgl-project/sglang#44131 currently fails before evaluation because this ID is unsupported.The preset uses temperature 1.0, top-p 0.95, thinking enabled, and reasoning effort high, matching the explicit settings used in the V4.1 MMMU-Pro evaluation driver. It leaves max_tokens unset so benchmark/server defaults apply; callers can set an explicit output budget. This does not claim a completed accuracy baseline or change existing model presets.
Add a documented MMMU-Pro invocation and regression coverage for loading the preset, resolving generation settings, and overriding the output budget and reasoning settings.
Validation
SGLang CI must install a version containing this preset before its existing preset-based V4.1 E2E can use it; this PR alone does not update SGLang's pinned dependency.