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vllm-project/vllm — GitHub trending stats & insights | Trendshift
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vllm-project/vllm
#
AI infrastructure
A high-throughput and memory-efficient inference and serving engine for LLMs
Python
81k
17.1k
2,644 contributors
Apache License 2.0
website
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Easy, fast, and cheap LLM serving for everyone 📦 vllm ⭐ 80,872 🐍 Python #LLM #PyTorch #Python 🔗
@Marco_Ramilli · x.com
Most people trying to build with AI hit the same wall: «API costs.» Experiment a little. Test a few agents. Run some workflows. Suddenly your credits are gone. That’s why repos like this spread fast.…
@RoyAmal · x.com
Are there any vLLM code maintainers active on X? I have two small PRs that have not received any feedback yet. I’d really appreciate any review, comments, or guidance on what might be blocking them.
@Ricky_reasearch · x.com
Flash-MaxSim 🚀 FlashAttention killed the materialized attention matrix in 2022. The same Lq×Ld matrix still lives in every ColBERT/ColPali pipeline — 21 GB for ColPali @ 10K docs, built only to be…
@PonyRoi · x.com
午后开源工具链速递 ☕️ 🔗 vLLM v0.21.0(5/15):KV Offload + Hybrid Memory Allocator 上线,推测解码支持 thinking budget,Blackwell GPU 上 DeepSeek-R1 走 TOKENSPEED_MLA 后端 ⚡ Unsloth v0.1.405-beta(5/18):MTP 推测解码让 GGUF 推理 2x…
@honitec · x.com
让Claude Opus 4.7 Max点评了一下 DeepSeek V4 Flash 的生成质量,评测的产物在 用我的 vLLM fork 跑的 覆盖度齐全:nomtp / mtp2 / mtp1 各 315 个 .md(17 case × 3 mode × 3 round × 2 lang)。开读代表性样本—— 读完代表性样本,给你认真说下我的主观评价。 产物覆盖度 ✓ 315…
@jasl9187 · x.com
🐍 vllm ⭐ 80,203 stars **"vLLM : Le serveur LLM ultra-rapide, économe et accessible à tous !"** 🚀 #GitHub
@clxymox · x.com
Hi @vllm_project, could someone review vllm-project/vllm#41967? It impacts Gemma4 streaming tool calls with MTP/speculative decoding. Fixes are already proposed in #42006 and #42300. Maintainer…
@yasu_oh_ · x.com
🐾 vLLM: Fast and Easy LLM Serving for Everyone Unlock super-fast language model responses with minimal effort! Dive into state-of-the-art serving and see your models perform like never before. Learn…
@repocatai_git · x.com
Benchmark LLMs beyond just accuracy scores. Focus on operational metrics too. Consider `tokens/second`: - Measures output generation speed. - Crucial for interactive user experiences. - Impacts…
@vikashkaushik01 · x.com
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