vLLM
Model ● Covered in 16 stories + Follow
vLLM is an LLM inference system used as a serving component across multiple AI deployments and training pipelines. Recent coverage shows it being integrated with RL and inference workflows—such as Amazon SageMaker’s disaggregated prefill/decode using vLLM plus LMCache, Netflix’s in-house model serving with vLLM constrained decoding, and GRPO training setups where vLLM is co-located on the same GPUs. The reports also include operational updates like running a vLLM server on Hugging Face Jobs and debugging efforts addressing correctness discrepancies between vLLM versions and a reported memory leak in disaggregated serving scenarios.
Updated 15 September 2026
Specifications
No specifications recorded yet.
Latest developments
NVIDIA AI Releases Molt: A PyTorch-Native Agentic Reinforcement Learning Framework
MarkTechPost · 1 month ago ·
21
In-House LLM Serving at Netflix
Medium · 1 month ago ·
10
Welcome Inkling by Thinking Machines
Hugging Face · 2 months ago ·
45
Disaggregated prefill and decode for LLM inference on SageMaker HyperPod
AWS · 2 months ago ·
17
Run a vLLM Server on HF Jobs in One Command
Hugging Face · 2 months ago ·
7
vLLM V0 to V1: Correctness Before Corrections in RL
Hugging Face · 4 months ago ·
51
Heaps do lie: debugging a memory leak in vLLM.
Mistral AI · 7 months ago ·
28
Introducing AutoJudge: Streamlined inference acceleration via automated dataset curation
Together AI · 9 months ago ·
16
2026
Thinking Machines releases Inkling, an open-source multimodal language model with 975 billion parameters Open source release
- NVIDIA AI Releases Molt: A PyTorch-Native Agentic Reinforcement Learning Framework
- In-House LLM Serving at Netflix
- Welcome Inkling by Thinking Machines
- Disaggregated prefill and decode for LLM inference on SageMaker HyperPod
- Run a vLLM Server on HF Jobs in One Command
- vLLM V0 to V1: Correctness Before Corrections in RL
- Heaps do lie: debugging a memory leak in vLLM.
2025
Together AI Integrates PyTorch Reinforcement Learning Capabilities into AI Cloud Platform Partnership
Alibaba releases Qwen2.5 model family including vision-language, extended-context, and mixture-of-experts variants Model release
- Introducing AutoJudge: Streamlined inference acceleration via automated dataset curation
- How to run TorchForge reinforcement learning pipelines in the Together AI Native Cloud
- No GPU left behind: Unlocking Efficiency with Co-located vLLM in TRL
- The Transformers Library: standardizing model definitions
- Blazingly fast whisper transcriptions with Inference Endpoints
- Efficient Request Queueing – Optimizing LLM Performance
- Qwen2.5-1M: Deploy Your Own Qwen with Context Length up to 1M Tokens
- Introducing multi-backends (TRT-LLM, vLLM) support for Text Generation Inference
2023
Mistral AI releases Mixtral 8x7B, an open-weights mixture-of-experts language model Model release
Relationships
Products & technology
- Integrated with LMCache · 1 source
- Integrated with DeepSpeed · 1 source
- TorchForge integrated with this model · 1 source
- Netflix integrated with this model · 1 source
- AutoJudge integrated with this model · 1 source
- SageMaker HyperPod integrated with this model · 1 source
- Mistral AI deploys this model · 1 source
- Text Generation Inference integrated with this model · 1 source
- TRL integrated with this model · 1 source
- Hugging Face deploys this model · 1 source
- PipelineRL deploys this model · 1 source
- TNG Technology Consulting integrated with this model · 1 source