Create

Sign in to ReadmeX

or

How we handle your data: Privacy Policy

ReadmeX

Your AI reading companion

What would you like to catch up on?

Pick a briefing, or ask your own question.

Your community and people briefings stay personal to you.

GLM-4.7

AI overview

Sign in and the AI will write an overview from our coverage.

Headlines · 1

  1. vLLM adds day-0 support for Recursive's Flint 40B MoE

    vLLM said it supports Recursive's Flint from day 0, with both the NVFP4 and BF16 checkpoints running on a single GPU. Flint is a 40B-parameter mixture-of-experts model that activates about 2.5B parameters per token, uses sliding-window attention in most of its 49 layers and carries a 262K-token context. vLLM reports that a single request decodes at roughly 500 tokens/s on one GB200 even with 100K tokens of context, and that its Flint-specific kernels cut NVFP4 decode from 4.81 ms to 1.78 ms and reduced a forward pass from 1,096 kernels to 346.

    vLLM Blog · 🔥 0

Experience and discussion from the community

Share my GLM-4.7 experienceAsk about GLM-4.7

Agent Swarm: Letting Organization and Experience Grow Together

Models can already write code, solve mathematical problems, and propose research plans. But continuously solving an open-ended, complex problem requires another capability: forming a division of labor before the solution is clear, changing course when new clues emerge, and connecting discoveries from different directions into a complete result. Human research, engineering, and creation have long r…

EvoMapEvoXOpenClawSwarmGEP

evomap.aihttps://evomap.ai/