Making the Other 90% Observable
How OpenInfer's multi-SLA inference scheduling and ClawMetry's observability layer make heterogeneous compute visible and debuggable.
Read more →Vertical Disaggregation: Maximizing Model Throughput on Heterogeneous Silicon
Co-executing Qwen 3.5 27B across CPU and GPU on a single node achieved +50% capacity with no additional GPU spend.
OpenInfer Solves Infrastructure Inefficiency in Agentic AI Exposed by Anthropic's Claude Restrictions
How OpenInfer's infrastructure solves the efficiency problems in agentic AI that Anthropic's Claude usage restrictions exposed.
2026
Inference Is No Longer a Single Execution Model — It's a Routing Problem
Agents broke the single-request serving model. Inference is now a routing problem across latency tiers, and serving systems need to catch up.
OpenInfer Launches Jean: Sovereign Agentic AI System Built for Enterprises With Cost and Data Control in Mind
Jean is a private, email-native agentic AI system that runs on your hardware — no cloud costs, no data exposure, no vendor lock-in.
Silicon Valley Startup OpenInfer Hires Revenue Chief, Eyes San Mateo Expansion
Silicon Valley Business Journal covers OpenInfer's growth, new revenue leadership, and San Mateo expansion plans.
Decode is repetitive: why caching primitives and kernels matters
Optimizing the LLM decode loop by caching execution primitives and graph captures to reduce per-token overhead.
2025
OpenInfer Joins Forces with Intel® and Microsoft to Accelerate the Future of Collaboration in Physical AI
OpenInfer joins the Intel Partner Alliance and Microsoft's Pegasus Program to advance physical AI and edge inference.
Why Desktop File Operations Fail on Android: A Developer's Guide
A practical guide to the file system differences between desktop and Android, and how to handle assets, sandboxing, and content URIs.
Introducing Mementos: A New Concept Demo from OpenInfer
Mementos is a concept demo exploring what a local-first, private-by-design AI runtime could look like for enterprises.
AI Journal Publication: The End of the AI Singularity Dream — Welcome to the Age of Multiplicity
Our CEO's AI Journal article on why the future of AI is multiplicity — many specialized agents collaborating — not a single superintelligence.
On-Device Model Architecture: Where GPT-OSS Fits in the Edge AI Landscape
Why Mixture of Experts models with active parameter selection are the optimal architecture for deploying AI reasoning on edge devices.
Boosting Local Inference with Speculative Decoding
How speculative decoding uses a small draft model to accelerate inference on bandwidth-bound systems without sacrificing output quality.
AI Inference at the Edge: A Deep Dive into CPU Workload Bottlenecks and Scaling Behavior
A deep dive into CPU inference bottlenecks — cache utilization, thread scheduling, and how adaptive schedulers improve throughput.
Rethinking the CPU: Unlocking Hidden Performance for Client-Side AI Inference
On client devices with unified memory, the CPU is often just as capable as specialized processors for AI inference — if you know how to use it.
Client-Side Inference, Reimagined: Llama 4 Scout Goes Local
Running Llama 4 Scout locally on client devices using OpenInfer Studio's optimization tools — a model that typically wouldn't fit.
Unlocking the Full Potential of GPUs for AI Inference
Why most GPUs run at 30-50% utilization during inference, and how to close the gap through memory bandwidth, core occupancy, and precision optimization.
OpenInfer Featured in VentureBeat: $8M to Revolutionize AI Inference at the Edge!
VentureBeat covers OpenInfer's $8M funding round and our mission to build the first Inference OS for edge AI.
Introducing the First Preview Build of the OpenInfer Engine
The first preview build of the OpenInfer Engine with automated onboarding and native LangChain, Ollama, and vLLM support.
Introducing OpenInfer API: The Zero-Rewrite Inference Engine That Integrates Effortlessly Into Your Stack
A drop-in inference engine that works with LangChain, Ollama, and vLLM — just change the endpoint URL.
Introducing Performance Boosts in OpenInfer: 2-3x Faster Than Ollama/Llama.cpp
Benchmarks showing 2-3x faster tokens per second compared to Ollama and Llama.cpp on consumer hardware.
Unlocking Efficiency: OpenInfer's Breakthrough in Memory Optimization
How OpenInfer's memory optimization engine lets you run large language models with dramatically less VRAM.
Running large models and context within a small fixed memory footprint.
A demo of running large models and large context within a fixed memory footprint using the OpenInfer Engine.