vllm / csrc
AGENTS.md97k starsChanged yesterdayApache-2.0View on GitHub
- A .cu is one unit of build parallelism, and it is compiled once per GPU architecture (-gencode on CUDA, --offload-arch on ROCm), so a file instantiating every variant of an op can be the build's whole critical path. Before adding instantiations, find the slowest unit of a cold build from .ninja_log (end minus start per object, MAX_JOBS fixed). - Split on the instantiation axis (head size, output width, dtype, block size), never on line count: kernels in an include-only…
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- Fahd Mirza“How-to Install vLLM and Serve AI Models Locally – Step by Step Easy Guide”YouTube · Apr 20, 2025 · 21k views
- Red Hat“Optimize LLM inference with vLLM”YouTube · Jul 22, 2025 · 21k views
- lorvo“What is vLLM and how does it work?”YouTube · Oct 27, 2026 · 5.1k views
- Red Hat“[vLLM Office Hours #35] How to Build and Contribute to vLLM - October 23, 2025”YouTube · Oct 24, 2025 · 2.5k views
- Red Hat“[vLLM Office Hours #37] InferenceMAX & vLLM - November 13, 2025”YouTube · Nov 14, 2025 · 886 views
The biggest 5 of 98 mentions linking to the repository that our crawl found. Each line is their own headline.
See all 98
Talked about on GitHub, YouTube, Hacker News, Bluesky, the web and Stack Overflow (98 times).
On GitHub · 28
- Jul 28, 2025Feature Request: GLM 4.5 MoE support — ggml-org/llama.cpp165 reactions · 5 comments
- Apr 17, 2025[rollout] feat: introduce vLLM AsyncLLM to support multi-turn rollout — verl-project/verl52 reactions · 42 comments
- Apr 1, 2024Ecosystem compatibility with numpy 2.0 — numpy/numpy42 reactions · 167 comments
- Sep 29, 2025Feature Request: DeepSeek V3.2-Exp support — ggml-org/llama.cpp35 reactions · 54 comments
- Jun 20, 2023Add support to vLLM inference engine - to possibly gain x10 speedup in inference — oobabooga/textgen33 reactions · 19 comments
23 more on GitHub
- Dec 26, 20252025 年我提了 500 个 Pull Requests — yihong0618/gitblog32 reactions · 9 comments
- Jul 26, 2024[Feature] Generation Inputs: input_embeds — sgl-project/sglang30 reactions · 13 comments
- Sep 2, 2025Feature Request: Apertus models support — ggml-org/llama.cpp29 reactions · 14 comments
- Feb 7, 2024Development Roadmap (Deprecated) — sgl-project/sglang25 reactions · 17 comments
- Jul 14, 2023vLLM Support — guidance-ai/guidance25 reactions · 5 comments
- Jan 12, 2026[roadmap] verl 26Q1 roadmap — verl-project/verl24 reactions · 13 comments
- Feb 9, 2026model: support GLM MoE DSA arch (NOTE: indexer is not yet supported) — ggml-org/llama.cpp23 reactions · 28 comments
- May 6, 2026Feature Request: MTP (Multi-Token Prediction) Speculative Decoding for Gemma 4 — jundot/omlx20 reactions · 3 comments
- Apr 19, 2024llama3-instruct models not stopping at stop token — ollama/ollama20 reactions · 47 comments
- Feb 17, 2026Feature Request: Add Voxtral Realtime — ggml-org/llama.cpp18 reactions · 2 comments
- Apr 14, 2025kernel: support slightly faster merge_state_v2 cuda kernel — sgl-project/sglang17 reactions · 3 comments
- Nov 22, 2024[Roadmap] veRL Development Roadmap — verl-project/verl17 reactions · 7 comments
- Mar 8, 2026vllm: 0.16.0 -> 0.24.0 — NixOS/nixpkgs16 reactions · 91 comments
- Apr 7, 2025Support MHA with chunked prefix cache for DeepSeek chunked prefill — sgl-project/sglang16 reactions · 7 comments
- Mar 23, 2025[Model] Adding Qwen3 and Qwen3MoE — sgl-project/sglang16 reactions · 14 comments
- Sep 16, 2025fix: Resolve response format corruption due to incorrect encoding — openai/harmony15 reactions · 17 comments
- Sep 2, 2026[recipe] feat: preview DeepSeek-V4 exact 0-diff true-on-policy RL on Megatron and vLLM — verl-project/verl14 reactions · 2 comments
- Apr 25, 2026Support SM120 — deepseek-ai/DeepGEMM12 reactions · 18 comments
- Mar 30, 2025Add DeepSeek V3/R1 shared experts fusion — sgl-project/sglang11 reactions · 14 comments
- Jun 15, 2026Add DFlash support — ikawrakow/ik_llama.cpp9 reactions · 3 comments
- Apr 26, 2026[Quantization] add humming quantization kernel — sgl-project/sglang9 reactions · 17 comments
- Mar 29, 2026feat(kv-cache): Add TurboQuant KV cache quantization (WIP) — sgl-project/sglang8 reactions · 5 comments
- Dec 18, 2025[Draft] [Preview] Support gfx1201 — ROCm/aiter8 reactions · 5 comments
On YouTube · 21
- Apr 20, 2025How-to Install vLLM and Serve AI Models Locally – Step by Step Easy Guide — Fahd Mirza21k views · 13 comments
- Jul 22, 2025Optimize LLM inference with vLLM — Red Hat21k views · 6 comments
- Oct 27, 2026What is vLLM and how does it work? — lorvosays it tested it5.1k views
- Oct 24, 2025[vLLM Office Hours #35] How to Build and Contribute to vLLM - October 23, 2025 — Red Hat2.5k views · 4 comments
- Nov 14, 2025[vLLM Office Hours #37] InferenceMAX & vLLM - November 13, 2025 — Red Hat886 views
16 more on YouTube
- Oct 19, 2026vLLM 0.32: Serve Local AI Across Your Homelab — Scottek476 views · 2 comments
- Aug 5, 2026Stop Using Ollama! (Unless you see these vLLM Benchmarks) 🚀 — Optilatesays it tested it422 views
- Oct 19, 2026vLLM 0.32 Turns Your GPU Into a LAN AI Server — Scottek360 views
- Sep 17, 2026VLLM: Ultra-Fast LLM Serving with PagedAttention for Production AI (LLama/Mistral/Qwen) — Solopreneurs hub355 views
- Dec 3, 2025STOP Paying Cloud Tax: The Ultimate FREE vLLM + LMCache Stack for LLM Deployment — Agentic Economics172 views
- Aug 26, 2026vLLM v0.28.0: Major Performance Updates for LLM Inference — Love More116 views · 1 comment
- Oct 22, 2026How ONE Server Answers 1000s of AI Chats (vLLM Explained) — The Rethinking Machine95 views
- Oct 20, 2026vLLM: phục vụ LLM qua API, nhưng độ ổn định ra sao? | PaperEngineer #shorts — Kỹ sư giấy63 views · 1 comment
- Oct 22, 2026A vLLM advisory: one bad request, a server alive but not serving — Data Engineering With AI55 views
- Oct 30, 2026vLLM vs Jev: What Do the Speed Results Actually Prove? — Tensor Garage48 views
- Nov 3, 2026vLLM 0.33 Is Out: What Changed, and What Breaks? #shorts — Ever Known?46 views
- Nov 1, 2026LLM inference: KV cache, FlashAttention, vLLM, speculative decoding | Evolution Grid — TFM Lab46 views · 1 comment
- Oct 29, 2026Cancel Cloud API Subscriptions: Run 100% Free Self-Hosted vLLM Engine — DailyDev AIsays it tested it22 views
- Oct 2, 2026Why Fast LLMs Feel Slow: Inside the vLLM Scheduler — Tim Lin21 views
- Oct 16, 2026vLLM CVE-2026-105757: Patch Structured-Output Engine DoS — dailytechhackglobal8 views
- Oct 12, 2026vLLM CVE-2026-105757: Patch AI Serving DoS Risk Now — dailytechhackglobal3 views
On Hacker News · 15
- Aug 29, 2026vLLM v0.28.0108 points · 43 comments
- Apr 4, 2026vLLM introduces memory optimizations for long-context inference5 points
- Apr 7, 2026vLLM IR: A Functional Intermediate Representation for vLLM4 points
- Sep 9, 2026vLLM 0.29.0: Model Runner V2 is now the default3 points
- Sep 10, 2023Vllm: High-throughput and memory-efficient inference and serving engine for LLMs3 points
10 more on Hacker News
- Aug 6, 2023Vllm3 points
- Feb 25, 2026vLLM (high-throughput LLM serving engine)2 points
- Dec 17, 2023Easy, fast, and cheap LLM serving for everyone2 points
- Dec 11, 2023Official PR Reveals the Inference Code for Mixtral 8x7B2 points
- Jun 25, 2023VLLM2 points
- Sep 16, 2026vLLM: Jev-like mode for the DiffusionGemma model1 point
- Jan 22, 2026vLLM multi-turn conversations design1 point
- Jan 24, 2024VLLM Sacrifices Accuracy for Speed1 point
- Dec 15, 2023vllm1 point
- Dec 15, 2023Mixtral Expert Parallelism1 point
On Bluesky · 15
- Apr 13, 2025Vllm est un projet de serveur d'inférence pour vos LLM qui se veut performant et efficace en terme de gestion mémoire ⬇️… — @ponceto91.bsky.social17 likes and reposts
- Feb 2, 2025vLLM has been updated to 0.71 with the enhancement to DeepSeek models. github.com/vllm-project... — @sungkim.bsky.social15 likes and reposts · 1 reply
- Jun 24, 2026No uses Ollama si quieres usar IA local con buen rendimiento. No exprime tu GPU al máximo. Mejor usa vLLM: ✓ Mejor eficiencia ✓ Más… — @midu.dev10 likes and reposts · 2 replies
- Jan 31, 2025Paper: R.I.P.: Better Models by Survival of the Fittest Prompts ( arxiv.org/abs/2501.18578 ) They used: - Fairseq2 from FAIR for LLM… — @sungkim.bsky.social4 likes and reposts
- Oct 28, 2026⚡ Serve LLMs faster and cheaper with vLLM's PagedAttention, continuous batching and a drop-in OpenAI-compatible API. 🔗… — @prosperflowio.bsky.social3 likes and reposts
10 more on Bluesky
- May 27, 2025🔥 Hot Repo! 🔥 (100+ new stars) 📦 vllm-project / vllm ⭐ 48,168 (+100) 🗒 Python A high-throughput and memory-efficient inference and… — @github-trending.bsky.social3 likes and reposts
- Apr 12, 2025🚀 Skyrocketing! 🚀 (200+ new stars) 📦 vllm-project / vllm ⭐ 44,413 (+267) 🗒 Python A high-throughput and memory-efficient inference and… — @github-trending.bsky.social2 likes and reposts
- Jan 21, 2025🔥 Hot Repo! 🔥 (100+ new stars) 📦 vllm-project / vllm ⭐ 34,172 (+145) 🗒 Python A high-throughput and memory-efficient inference and… — @github-trending.bsky.social2 likes and reposts
- Mar 23, 2026https://github.com/vllm-project/vllm — @tom-doerr.bsky.social1 likes and repost
- Aug 14, 2025A high-throughput and memory-efficient inference and serving engine for LLMs — @midnattssol.bsky.social1 likes and repost
- Apr 30, 2025🔥 Hot Repo! 🔥 (100+ new stars) 📦 vllm-project / vllm ⭐ 46,215 (+128) 🗒 Python A high-throughput and memory-efficient inference and… — @github-trending.bsky.social1 likes and repost
- Mar 7, 2025🔥 Hot Repo! 🔥 (100+ new stars) 📦 vllm-project / vllm ⭐ 40,586 (+148) 🗒 Python A high-throughput and memory-efficient inference and… — @github-trending.bsky.social1 likes and repost
- Oct 18, 2024📦 vllm-project / vllm ⭐ 28,641 (+85) 🗒 Python A high-throughput and memory-efficient inference and serving engine for LLMs — @github-trending.bsky.social1 likes and repost
- Oct 2, 2024interessante esse vllm, parece ser mais performático em cpus do que o ollama github.com/vllm-project... — @gaucho.dev1 likes and repost
- Dec 12, 2023🚀 Skyrocketing! 🚀 (200+ new stars) 📦 vllm-project / vllm ⭐ 11,193 (+321) 🗒 Python A high-throughput and memory-efficient inference and… — @github-trending.bsky.social1 likes and repost · 1 reply
On the web · 10
- May 20, 2026vLLM in Production: Ranked Configuration Decisions, Failure Modes, and the Architecture That Makes Them Work — dev.to
- Jan 23, 2026Local LLMs V - Installing and running vLLM | Rough Notes — javiercancela.com
- Jan 4, 2026Zero to Hero with vLLM: A Practical Guide for High‑Throughput LLM Inference | martinuke0's Blog — martinuke0.github.io
- Nov 6, 2025🧑🚀 Choosing the Right Engine to Launch Your LLM (LM Studio, Ollama, and vLLM) | by astronaut27 — medium.com
- Aug 26, 2025vLLM on x86: Because Not Everyone Can Afford a GPU Cluster — dev.to
5 more on the web
- Apr 1, 2025Run your own AI at scale: Tuning vLLM for Superb LLM Deployment (Vol. 1) — petarzrinscak.substack.com
- Feb 28, 2025Benchmarking llm serving performance a comprehensive guide — medium.comsays it tested it
- Feb 26, 2025Practical Large Language Model Serving with vLLM on VertexAI — infocruncher.substack.com
- Mar 9, 2024Run your own local Copilot. This is more of a blog on what I am… | by Thameem Abbas — tabbas97.medium.com
- Aug 14, 2023Efficiently Serving Open Source LLMs | by Ryan Shrott | TDS Archive — medium.com
On Stack Overflow · 9
- Apr 16, 2024How to install pip install torch==2.1.2+cu118 in linux?5 votes · 2 answers
- Jul 2, 2024How to set eos_token_id in llama3 in HuggingFaceLLM?2 votes
- May 15, 2024How to Load an Already Instantiated Hugging Face Model into vLLM for Inference?1 vote
- May 12, 2026How to Evaluate my RAG System using Local / free tier API model0 votes
- Mar 14, 2025Max len error when using Huggingface model0 votes
4 more on Stack Overflow
- Apr 27, 2024How does one use vllm with pytorch 2.2.2 and python 3.11?0 votes · 1 answer
- Dec 13, 2023ImportError: libcudart.so.12: cannot open shared object file: No such file or directory0 votes
- Nov 20, 2023How to send data in batches to a LLM0 votes
- Jan 24, 2024OSError: libcudart.so.10.2: cannot open shared object file: No such file or directory-1 votes
Where files are headingNew AGENTS.md files have more rules about keeping secrets out of the code, and fewer about code style.
Of the AGENTS.md files we read, the 31,439 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.
In this repository12 other files it gives its agents.
- AGENTS.mdAGENTS.md
- rust/AGENTS.mdAGENTS.md
- tests/AGENTS.mdAGENTS.md
- check-api-compatSkill
- ci-fails-buildkiteSkill
- debug-imaSkill
- kernel-microbenchmarkSkill
- model-microbenchmarkSkill
- model-recipesSkill
- pr-checklistSkill
- transformers-upgradeSkill
- triton-kernel-writingSkill
The file
We split this AGENTS.md into the rules it gives an agent
1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 6
Before adding instantiations, find the slowest unit of a cold build from .ninja_log (end minus start per object, MAX_JOBS fixed).
≈ “Common” is an estimate: at least 1 in 5 of the 40,246 AGENTS.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
csrc
- A
.cuis one unit of build parallelism, and it is compiled once per GPU architecture (-gencodeon CUDA,--offload-archon ROCm), so a file instantiating every variant of an op can be the build's whole critical path. Before adding instantiations, find the slowest unit of a cold build from.ninja_log(end minus start per object,MAX_JOBSfixed). - Split on the instantiation axis (head size, output width, dtype, block
size), never on line count: kernels in an include-only header, one thin
.cuper variant, and an entry-point unit that only declares and dispatches, so every entry it declares is defined in a variant unit. Keep<torch/all.h>out of kernel headers. Copy an existing split incsrc/and its CMake wiring, including the arch-gated source list of the file it came from. - Never vary a shared function body with a per-unit
#define. Identical symbol names with different bodies are an ODR violation, and the linker keeps one copy, so the other variants silently run the wrong code or fail: give each variant its own symbol instead. Derive the variant list, the dispatch arms and the CMake sources from one place, generating them where you can so no unit compiles without a dispatch arm. - Call every variant from one test, and measure cold. A build-time claim
needs ccache off,
MAX_JOBSfixed, before and after, naming the unit that was the critical path: a split only pays off once its unit is, or is about to become, that path, and a compiler flag is no substitute without a measurement.
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Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

