Ollama: Memory Management Revolution

The Ollama team shipped seven major pull requests focused heavily on memory optimization and user experience improvements. Jesse Gross led a complete overhaul of MLX memory management, fixing critical memory leaks and crashes, while Eva H added user-controlled auto-updates and smarter web search detection. Jeffrey Morgan also delivered major improvements to LiquidAI's LFM2 architecture with vision model support.

Duration: PT4M1S

Episode overview

This episode is a short developer briefing from Ollama.

It explains recent repository work in plain language.

  • Show: Ollama
  • Published: 2026-02-24T11:06:08Z
  • Audio duration: PT4M1S

Transcript excerpt

This excerpt keeps the crawler page concise. Listen to the episode or use the RSS feed for the full update.

Hey there, developers! Welcome back to another episode of the Ollama podcast. I'm your host, and wow, do we have an exciting day to dive into. February 24th brought us some absolutely fantastic updates, and I'm genuinely excited to walk through what the team has been cooking up.

Let me start with the biggest story of the day, and honestly, it's a bit of a hero's journey. Jesse Gross tackled what might be one of the most challenging problems in AI infrastructure - memory management. If you've been running MLX models and noticed your system getting sluggish or even crashing during long…

Jesse merged a massive pull request that completely reimagines how Ollama handles MLX memory usage. Now, here's what makes this so cool - instead of trying to track every little memory reference manually, which is honestly like trying to count every grain of sand on a beach, they switched to what they call a "pin…

But that's not all Jesse did. They also simplified the KV cache system. The old approach was storing full copies of cache data for every conversation path, which sounds smart until you realize it's like keeping a photocopy of your entire filing cabinet every time you add a new document. The…

Sp…

Nearby episodes from Ollama

  1. MLX Runner Gets Rock Solid
  2. Tool Calling Gets Smarter
  3. Cleaner Shutdowns and Faster Startups
  4. Qwen 3.5 Architecture Lands with Safety Upgrades
  5. Nemotron Architecture Lands with Unified Cache Vision
  6. Fixing the WSL Plugin Problem
  7. Smarter UIs and Smoother Onboarding
  8. Tokenizer Consolidation & MLX Library Improvements