EmbeddedLLM @EmbeddedLLM
Your open-source AI ally. We specialize in integrating LLM into your business. Joined October 2023-
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vLLM is proud to support the great Kimi update from @Kimi_Moonshot , better tool-calling, longer context, and more! Check the deployment guide at huggingface.co/moonshotai/Kim… 🔥
vLLM is proud to support the great Kimi update from @Kimi_Moonshot , better tool-calling, longer context, and more! Check the deployment guide at huggingface.co/moonshotai/Kim… 🔥 https://t.co/ysxqSJVTBU
Amazing blogpost from @gordic_aleksa explaining internals of vLLM😍
Amazing blogpost from @gordic_aleksa explaining internals of vLLM😍
Go LMCache 🚀
Big energy at the @vllm_project Meetup in Singapore! WEKA’s Ronald Pereira shared how NeuralMesh Axon + Augmented Memory Grid can boost vLLM inferencing. Shoutout to @EmbeddedLLM + @AMD for the strong collaboration.
🚀 Exciting news: DeepSeek-V3.1 from @deepseek_ai now runs on vLLM! 🧠 Seamlessly toggle Think / Non-Think mode per request ⚡ Powered by vLLM’s efficient serving — scale to multi-GPU with ease 🛠️ Perfect for agents, tools, and fast reasoning workloads 👉 Guide & examples:…
🚀 Exciting news: DeepSeek-V3.1 from @deepseek_ai now runs on vLLM! 🧠 Seamlessly toggle Think / Non-Think mode per request ⚡ Powered by vLLM’s efficient serving — scale to multi-GPU with ease 🛠️ Perfect for agents, tools, and fast reasoning workloads 👉 Guide & examples:… https://t.co/AiiFbGH8Go
Great example from @skypilot_org showing how to use vLLM to serve Kimi K2 from @Kimi_Moonshot 😀
Great example from @skypilot_org showing how to use vLLM to serve Kimi K2 from @Kimi_Moonshot 😀
🚀 GLM-4.5 meets vLLM @Zai_org 's latest GLM-4.5 & GLM-4.5V models bring hybrid reasoning, coding & intelligent agent capabilities—now fully supported in vLLM for fast, efficient inference on NVIDIA Blackwell & Hopper GPUs! Read more 👉 blog.vllm.ai/2025/08/19/glm…
Meet TokenVisor from @EmbeddedLLM: a first of its kind open-source command center for the AMD Instinct neocloud ecosystem. ✅ No proprietary walls ✅ Custom pricing + usage control ✅ Built with AMD, for real AI flexibility embeddedllm.com/newsroom
🇸🇬 Join us for the vLLM Meetup in Singapore on Aug 27, 2025 (Wednesday), 6-8:30 PM @SGInnovateWe will discuss efficient LLM inference with talks on: - @EmbeddedLLM on Latest vLLM advancements - @AMD on optimizing inference on Data Center GPUs - @WekaIO presenting vLLM + LMCache +…
GPT-OSS + Claude Code running 75 Tok/s locally on Macbook Pro 64GB is insane!
👀 we care a lot about correctness, ran many evals and stared at many tensors to compare them. numerics of vLLM on hopper should be solid and verified! if you run into any correctness issue on vLLM, we would love to know and debug them!
👀 we care a lot about correctness, ran many evals and stared at many tensors to compare them. numerics of vLLM on hopper should be solid and verified! if you run into any correctness issue on vLLM, we would love to know and debug them! https://t.co/mghuBdbK9f
Thank you @OpenAI for open-sourcing these great models! 🙌 We’re proud to be the official launch partner for gpt-oss (20B & 120B) – now supported in vLLM 🎉 ⚡ MXFP4 quant = fast & efficient 🌀 Hybrid attention (sliding + full) 🤖 Strong agentic abilities 🚀 Easy deployment 👉🏻…
Thank you @OpenAI for open-sourcing these great models! 🙌 We’re proud to be the official launch partner for gpt-oss (20B & 120B) – now supported in vLLM 🎉 ⚡ MXFP4 quant = fast & efficient 🌀 Hybrid attention (sliding + full) 🤖 Strong agentic abilities 🚀 Easy deployment 👉🏻…
.@vllm_project V1 is now fully optimized for AMD Instinct™ MI300X GPUs?! 🚀🚀🚀 This major architectural upgrade to the popular LLM inference engine brings significant performance gains to AMD hardware. Dive into the details in the thread below...
The future of optimization and GPU kernel writing, proud of the team!!! Generating Efficient AI-centric Kernels (GEAK) is our OpenAI Triton Kernel agent using inference-time scaling to generate a high performance numerically accurate kernel and two Triton evaluation benchmarks.…
🔥 Step 3 support just landed in vLLM! Both the 321B text-only and vision-language models are now fully supported ✌️ Step 3 is a blazing-fast, cost-effective VLM with MFA & AFD for efficient inference—even on modest GPUs. 🚄 Up to 4,039 tok/sec/GPU! We will optimize it further…
🔥 Step 3 support just landed in vLLM! Both the 321B text-only and vision-language models are now fully supported ✌️ Step 3 is a blazing-fast, cost-effective VLM with MFA & AFD for efficient inference—even on modest GPUs. 🚄 Up to 4,039 tok/sec/GPU! We will optimize it further…
🔥 vLLM @ PyTorch Conference 2025 🔥 We’re excited to share that 5 talks at this year’s PyTorch Conference will feature vLLM! Topics include: • Easy & Fast LLM Serving • Open-Source Post-Training Stack • Scaling Online LLM Training • AMD GPU support via Triton • vllm-triton…
🔥 vLLM @ PyTorch Conference 2025 🔥 We’re excited to share that 5 talks at this year’s PyTorch Conference will feature vLLM! Topics include: • Easy & Fast LLM Serving • Open-Source Post-Training Stack • Scaling Online LLM Training • AMD GPU support via Triton • vllm-triton… https://t.co/TAYZtNgrHt
You might know LMCache Lab for our KV cache optimizations that make LLM prefilling a breeze. But that’s not all! We’re now focused on speeding up decoding too—so your LLM agents can generate new content even faster. In other words: you can save on your LLM serving bills by…
AMD teams contributing to the llama.cpp codebase. Great support from the community with the review process. Exciting to see this open-source collaboration!
AMD teams contributing to the llama.cpp codebase. Great support from the community with the review process. Exciting to see this open-source collaboration!
Intern-S1 is supported in vLLM now, thanks for the joint efforts between the vLLM team and the InternLM team @intern_lm ♥️ The easy way: uv pip install vllm --extra-index-url wheels.vllm.ai/nightly vllm serve internlm/Intern-S1 --tensor-parallel-size 8 --trust-remote-code
Intern-S1 is supported in vLLM now, thanks for the joint efforts between the vLLM team and the InternLM team @intern_lm ♥️ The easy way: uv pip install vllm --extra-index-url wheels.vllm.ai/nightly vllm serve internlm/Intern-S1 --tensor-parallel-size 8 --trust-remote-code https://t.co/Aq1AfE8qjA
🚀 vLLM v0.10.0 is LIVE! Faster, leaner, and more powerful. The TL;DR: ⚡️ Performance & Hardware Highlights: Experimental Async Scheduling: +3-15% throughput by overlapping scheduling & GPU execution. Huge AMD Gains (from our team!): +68.3% throughput on Deepseek-V3/R1 with Full…
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Junchen Jiang @JunchenJiang
401 Followers 319 Following CS Prof @ UChicago https://t.co/U01oOWGnip (Fast distributed LLM inference) https://t.co/hoetjwXKIt (Best KV cache layer)
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Max Ng @maxnghello
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Binyuan Hui @huybery
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Daniel Romero @HyperTechInvest
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MJ @mjtechguy
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Chaoyue He @CYH37
354 Followers 4K Following AI Research Scientist@NTUsg 🇸🇬|LLM|Sustainability|GenRecSys|AGI|Productivity|UBI & Fortune|Disease Cures|Xi'an, China🇨🇳|Bodybuilder💪|Caregiver🤲❤
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