Feature Request: EAGLE-4 support
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Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 25/100
- Issue type
- Feature
- Clarity
- Mostly clear
- Activity status
- Active
- Tech stack
- cpp
- Domain
- machine-learning
Research direction
Start by reading the speculative decoding and model architecture support in llama.cpp, then trace where GGUF model metadata and tensors are loaded. The issue identifies EAGLE-4 additions and a drafter-only option, but names no files or tests. Done means supporting those additions and validating the proposed drafter behavior; clarify the source-available license before implementation.
Written by the indexing model from the issue text.
Description
Prerequisites
- I am running the latest code. Mention the version if possible as well.
- I carefully followed the README.md.
- I searched using keywords relevant to my issue to make sure that I am creating a new issue that is not already open (or closed).
- I reviewed the Discussions, and have a new and useful enhancement to share.
Feature Description
EAGLE-4 came out 20.10, there's a dense-draft Qwen3.8-27B-EAGLE4. Came 4 things in arch: fc_norm for 3 layers, norm_output, SWA 4096, low-rank candidate lm_head. There's an option to do only drafter.
Motivation
On A100: 1.93× at Q8_0, 1.57–1.60× к Q4_K_M. low-rank head: same acceptance, but ~20% faster.
At this model native MTP is a bit faster
License is Eagle 4 Source-Available. Please tell me is this ok?
Possible Implementation
GGUF remains eagle3, options through key and tensors.
My PR is expected
- Dominant language
- C++
- Stars
- 133k
- Forks
- 25.1k
- Avg merge
- 2d 8h
- Merged PRs (30d)
- 495
Getting set up
- No Dockerfile or Docker Compose file
- Has a pull request template
- Read the contributing guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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