Skip to content

[Feature]: EXL3 support #19896

@Teeeto

Description

@Teeeto

🚀 The feature, motivation and pitch

EXL3 has strong potential to become the go-to format for small BPW quantization, offering excellent perplexity-to-size performance. The authors note that changes in the format make integration with VLLM more feasible.
See: https://github.com/turboderp-org/exllamav3?tab=readme-ov-file#exl3-quantization

Adding EXL3 support to VLLM would be a major win, as the native EXLlama engine struggles with large-scale serving, where VLLM excels.

Alternatives

Using EXLLama for inference - bad performance, bad concurrency
Using different quantization formats - more vram, or worse model performance

Additional context

No response

Before submitting a new issue...

  • Make sure you already searched for relevant issues, and asked the chatbot living at the bottom right corner of the documentation page, which can answer lots of frequently asked questions.

Metadata

Metadata

Assignees

No one assigned

    Labels

    Type

    No type

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions