2026

• Performance improvements with speculative decoding in vLLM for gpt-oss | Harshith Umesh Apr 16, 2026
• Red Hat and NVIDIA: Setting standards for high-performance AI inference | Ashish Kamra Apr 2, 2026
• Red Hat AI tops MLPerf Inference v6.0 with vLLM on Qwen3-VL, Whisper, and GPT-OSS-120B | Ashish Kamra, Diane Feddema, Michael Goin, Michey Mehta, Naveen Miriyalu, Nikhil Palaskar, Saša Zelenović, Aanya Sharma, Alberto Perdomo, Harika Pothina, Samuel Monson, Sayali Bhavsar Apr 1, 2026
• Configure NVIDIA Blackwell GPUs for Red Hat AI workloads | Erwan Gallen, Tarun Kumar, Antonin Stefanutti, Selbi Nuryyeva, Michey Mehta Mar 16, 2026
• 5 steps to triage vLLM performance | David Whyte-Gray, Thameem Abbas Ibrahim Bathusha, Michael Goin, Ashish Kamra Mar 9, 2026

2025

• How to deploy and benchmark vLLM with GuideLLM on Kubernetes | Harshith Umesh Dec 24, 2025
• Autoscaling vLLM with OpenShift AI model serving: Performance validation | Naveen Miriyalu, Diane Feddema, Michey Mehta, Keith Valin, Michael Goin, Ashish Kamra, Jean Hsiao Nov 26, 2025
• Efficient and reproducible LLM inference with Red Hat: MLPerf Inference v5.1 results | Naveen Miriyalu, Diane Feddema, Michey Mehta, Keith Valin, Michael Goin, Ashish Kamra, Jean Hsiao Oct 31, 2025
• vLLM or llama.cpp: Choosing the right LLM inference engine for your use case | Harshith Umesh Sep 30, 2025
• How to set up KServe autoscaling for vLLM with KEDA | Alberto Perdomo Sep 23, 2025
• Benchmarking with GuideLLM in air-gapped OpenShift clusters | Philip Hayes, Thameem Abbas Ibrahim Bathusha Sep 15, 2025
• Ollama vs. vLLM: A deep dive into performance benchmarking | Harshith Umesh Aug 8, 2025
• MLPerf Inference v5.0 results with Supermicro's GH200 Grace Hopper Superchip-based Server and Red Hat OpenShift | Diane Feddema, Dr Nikola Nikolov, Arpitha Srinivas May 1, 2025
• How to run performance and scale validation for OpenShift AI | Alberto Perdomo, Kevin Pouget Apr 30, 2025
• Unlocking the Effective Context Length: Benchmarking the Granite-3.1-8b Model | Tushar Katarki, Nikhil Palaskar Feb 12, 2025

2024

• Achieve better large language model inference with fewer GPUs | David Gray, Diane Feddema Dec 3, 2024
• Accelerating generative AI adoption: Red Hat OpenShift AI achieves impressive results in MLPerf inference benchmarks with vLLM runtime | Mustafa Eyceoz, Michey Mehta, Diane Feddema, Ashish Kamra, Dr Nikola Nikolov Nov 24, 2024
• Generative AI fine-tuning of LLMs: Red Hat and Supermicro showcase outstanding results for efficient Llama-2-70b fine tuning using LoRA in MLPerf Training v4.0 | Diane Feddema, Dr Nikola Nikolov Nov 1, 2024
• Sharing is caring: How to make the most of your GPUs (part 2 — Multi-instance GPU) | Carlos Camacho, Kevin Pouget, Will McGrath Sep 1, 2024
• Sharing is caring: How to make the most of your GPUs (part 1 — time-slicing) | Carlos Camacho, Kevin Pouget, David Gray, Will McGrath Jul 2, 2024
• Continuous performance and scale validation of Red Hat OpenShift AI model-serving stack | Kevin Pouget Jun 1, 2024
• Evaluating LLM inference performance on Red Hat OpenShift AI | David Gray Jan 16, 2024

2023

• A Guide to Scaling OpenShift Data Science to Hundreds of Users and Notebooks | Kevin Pouget Jan 1, 2023

2022

• Entitlement-Free Deployment of the NVIDIA GPU Operator on OpenShift | Kevin Pouget Jun 1, 2022

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