★ Reading this for free? Get 20 structured AI courses + per-chapter AI tutor — the first chapter of every course free, no card.Start free in 30 seconds
Reference

Ollama Latest Version & Changelog: What's New

April 10, 2026
18 min read
Local AI Master Research Team

Want to go deeper than this article?

Free account unlocks the first chapter of all 20 courses — RAG, agents, MCP, voice AI, MLOps, real GitHub repos.

📚AI Learning Path

Ollama’s running. Here’s what to build with it. Go from “ollama run” to RAG apps, agents, and fine-tuned models — structured and hands-on. First chapter free.

Start free
Or own it for life — Lifetime $149, pay once

Published on April 10, 2026 · Updated June 19, 2026 — 18 min read

The latest Ollama version is v0.30.10 as of June 2026 (released June 17, 2026). Run ollama --version to see what you have — if it is anything below 0.19, you are missing the MLX Apple Silicon backend (roughly 2× faster on Macs) plus a long list of new models. This page tracks every major Ollama release so you can decide whether to update and what to expect when you do.


What you will find here:

  • Current stable version and what shipped in it
  • Full release timeline from v0.1.0 to present
  • Breaking changes that might affect your setup
  • How to check, update, and roll back versions
  • Version comparison table with key features

Ollama moves fast. The project has shipped over 40 releases since its first public beta, and the pace has only accelerated. Some releases add model support. Others overhaul the inference engine or change API behavior. Knowing what changed — and what broke — saves you hours of debugging.

If you are setting up Ollama for the first time, start with our complete Ollama guide instead. This page is for people who already run Ollama and want to understand the release cadence.

Table of Contents

  1. How to Check Your Ollama Version
  2. Current Stable Release
  3. How to Update Ollama
  4. Complete Version Timeline
  5. Breaking Changes by Version
  6. Version Comparison Table
  7. How to Roll Back to a Previous Version
  8. Release Cadence and Roadmap
  9. Troubleshooting Update Issues
  10. FAQ

Reading articles is good. Building is better.

Free account = 20+ free chapters across 20 courses, with a per-chapter AI tutor. No card. Cancel anytime if you ever upgrade.

How to Check Your Ollama Version {#check-version}

Three ways to find your current version:

Command Line

# Primary method
ollama --version
# Output: ollama version is 0.30.10

# Alternative — the version subcommand
ollama version

API Endpoint

# If Ollama is running as a service
curl http://localhost:11434/api/version
# Output: {"version":"0.30.10"}

System-Specific Locations

# macOS — check the app bundle
mdls -name kMDItemVersion /Applications/Ollama.app

# Linux — check the binary directly
ollama --version

# Windows — PowerShell
ollama --version
# Or check: Settings → Apps → Ollama

If ollama --version returns nothing or errors out, your installation is older than v0.1.17 (the version that added the flag) or the binary is not on your PATH. See the troubleshooting section below.


Current Stable Release {#current-release}

Ollama v0.30.10 (June 17, 2026)

This is the latest stable release. The 0.30 line (which opened with v0.30.0 on May 13, 2026) pairs the new MLX engine on Apple Silicon with continued llama.cpp improvements, so it runs well across both Mac and NVIDIA/AMD hardware.

Highlights of the 0.30 series:

  • Improved compatibility and performance via an updated llama.cpp engine, alongside the MLX backend on Apple Silicon
  • Broader hardware support, including GGUF-based models from Hugging Face and your own fine-tuned GGUF models
  • Faster performance on NVIDIA hardware
  • Metal GPU offload for multimodal models on Apple Silicon (fixing earlier cases where vision models ran on CPU)
  • Command A and the North family now run on Apple Silicon through the MLX engine (added in v0.30.10)

Recent patch notes:

  • v0.30.10 (Jun 17) — Command A / North family on Apple Silicon MLX, llama.cpp engine bump, MLX build-artifact fixes
  • v0.30.9 (Jun 15) — Cohere2Moe architecture support, LFM2 parser/render fixes
  • v0.30.8 (Jun 12) — ollama launch provider-selection fix, improved prompt caching, more stable MLX inference

Note: nomic-embed-text now lowercases inputs to match the model card. If you previously relied on mixed-case embeddings, re-embed your corpus after updating.

# Update to the latest version
# macOS (Homebrew)
brew upgrade ollama

# Linux
curl -fsSL https://ollama.com/install.sh | sh

# Windows — download installer from ollama.com/download

How to Update Ollama {#update-ollama}

macOS

# Homebrew (recommended)
brew update && brew upgrade ollama

# Verify update
ollama --version

# If using the .app bundle, it auto-updates on launch.
# Force a manual check:
open -a Ollama
# Click the menu bar icon → Check for Updates

Linux

# Official install script (always fetches latest)
curl -fsSL https://ollama.com/install.sh | sh

# If you installed via snap
sudo snap refresh ollama

# systemd users — restart the service after update
sudo systemctl restart ollama

Windows

# Download latest installer
# https://ollama.com/download/windows

# Or via winget
winget upgrade Ollama.Ollama

# Restart the Ollama service
net stop ollama && net start ollama

Docker

# Pull latest image
docker pull ollama/ollama:latest

# Stop and remove old container
docker stop ollama && docker rm ollama

# Start with new image
docker run -d --gpus all -v ollama:/root/.ollama \
  -p 11434:11434 --name ollama ollama/ollama:latest

Important: Your models survive updates. Ollama stores models in ~/.ollama/models (Linux/macOS) or C:\Users\<you>\.ollama\models (Windows). Updating the binary does not delete them. Docker users should mount a volume as shown above.


Reading articles is good. Building is better.

Free account = 20+ free chapters across 20 courses, with a per-chapter AI tutor. No card. Cancel anytime if you ever upgrade.

Complete Version Timeline {#version-timeline}

2026 Releases

v0.30.x Series (May–June 2026)

  • v0.30.10 (Jun 17): Command A and the North family run on Apple Silicon via the MLX engine; llama.cpp engine bump; MLX build fixes. Latest stable.
  • v0.30.9 (Jun 15): Cohere2Moe architecture support; LFM2 parser/render fixes
  • v0.30.8 (Jun 12): ollama launch provider-selection fix; improved prompt caching; more stable MLX inference
  • v0.30.0 (May 13): MLX engine on Apple Silicon now augmented by an updated llama.cpp engine for broader hardware support; GGUF models from Hugging Face and your own fine-tuned GGUFs; faster on NVIDIA; Metal GPU offload for multimodal models. Behavior change: nomic-embed-text now lowercases inputs to match the model card.

v0.19–v0.23 Series (March–May 2026)

  • v0.23.1 (May 5): Gemma 4 MTP speculative decoding on Macs
  • v0.21.1 (Apr 22): cloud-model launch shortcuts (e.g. ollama launch kimi --model kimi-k2.6:cloud)
  • v0.19 (March 30, 2026): MLX backend for Apple Silicon (preview). Ollama switched its Mac inference path from direct Metal calls to Apple's MLX framework to exploit unified memory — roughly 2× decode speed on supported chips (one published benchmark went from ~58 to ~112 tok/s). The MLX preview requires 32GB+ of unified memory; base 8GB/16GB Macs keep using the existing engine.

v0.12–v0.14 Series (Sept 2025–Jan 2026)

  • v0.14.0 (Jan 10, 2026): continued engine and model-support updates
  • v0.13.0 (Nov 19, 2025): new architecture and tooling support
  • v0.12.0 (Sept 18, 2025): cloud models, web search, and coding-agent integrations expanded across this period

2025 Releases

Mid-2025 highlights

  • Sept 23, 2025: enhanced model scheduling with more precise memory management
  • Web search API (2025): a hosted web-search endpoint with a free tier for individuals, letting local models pull current information to reduce hallucinations
  • May 15, 2025: new multimodal engine — first-class vision support for models like llama4:scout, gemma3, qwen2.5vl, and mistral-small3.1

v0.4.x Series (late 2024–early 2025)

  • v0.4.7: Apple M3 Ultra optimized Metal shaders
  • v0.4.5: ollama show command for model metadata inspection
  • v0.4.2: Multimodal model support (LLaVA, BakLLaVA)
  • v0.4.0: Breaking change — Model storage format migrated from blob-based to content-addressable. First run after update triggers automatic migration (can take 5–15 minutes depending on model count).

v0.3.x Series (October 2024–February 2025)

  • v0.3.12: GGUF v3 format support
  • v0.3.9: ollama create from Safetensors (no manual conversion needed)
  • v0.3.6: AMD ROCm 5.7 support, Radeon RX 7900 XTX validated
  • v0.3.0: Breaking change — Modelfile syntax updated. ADAPTER command replaced FROM ... ADAPTER pattern.

v0.2.x Series (May–September 2024)

  • v0.2.8: GPU layer offloading with num_gpu parameter
  • v0.2.5: OpenAI-compatible API endpoint at /v1/chat/completions
  • v0.2.0: Custom model creation via Modelfiles. SYSTEM, TEMPLATE, and PARAMETER directives introduced.

v0.1.x Series (Initial Release–April 2024)

  • v0.1.29: First Windows release
  • v0.1.17: Added ollama --version flag
  • v0.1.0: Initial public release. macOS and Linux only. Supported GGUF models via llama.cpp backend.

Breaking Changes by Version {#breaking-changes}

These are the releases where something in your workflow might stop working after an update. I maintain this list because the official release notes sometimes bury breaking changes in minor bullet points.

VersionWhat BrokeMigration
v0.30.0nomic-embed-text now lowercases inputs (to match the model card)Embeddings shift slightly vs. older Ollama. Re-embed your corpus with v0.30+ so queries and stored vectors match.
v0.19MLX backend (preview) only activates on Macs with 32GB+ unified memoryNone required. On 8GB/16GB Macs Ollama keeps the existing engine; no action needed, you just don't get the MLX speedup yet.
v0.5.0context field removed from chat APIUse conversation history instead of passing context tokens. See the official docs for the current API.
v0.4.0Model storage format migrationAutomatic on first run. Back up ~/.ollama before updating if you have custom models.
v0.3.0Modelfile syntax changeReplace FROM base ADAPTER lora.gguf with separate FROM and ADAPTER lines.
v0.2.0CLI argument changes--model flag replaced by positional argument. Old: ollama run --model llama2. New: ollama run llama2.

If you run Ollama behind an application (like Open WebUI or Continue.dev), check that your client version supports the Ollama version you are upgrading to. Open WebUI v0.5+ works with Ollama v0.5+.


Version Comparison Table {#version-comparison}

This table covers features across major version milestones. Use it to decide what minimum version you need.

Featurev0.1v0.2v0.3v0.4v0.12–v0.14v0.19+v0.30+
macOS supportYesYesYesYesYesYesYes
Linux supportYesYesYesYesYesYesYes
Windows supportv0.1.29+YesYesYesYesYesYes
Custom ModelfilesNoYesYesYesYesYesYes
GPU offloadingNov0.2.8+YesYesYesYesYes
OpenAI-compatible APINov0.2.5+YesYesYesYesYes
AMD ROCm supportNoNov0.3.6+YesYesYesYes
Multimodal / vision engineNoNoNoBasicYes (May 2025 engine)YesYes
Web search APINoNoNoNoYesYesYes
Cloud / hosted modelsNoNoNoNoYesYesYes
MLX Apple Silicon backendNoNoNoNoNoPreview (32GB+)Yes

How to Roll Back to a Previous Version {#rollback}

Sometimes an update breaks your workflow. Here is how to downgrade safely.

macOS (Homebrew)

# List available versions
brew search ollama

# Install a specific version (example: v0.30.0)
brew install ollama@0.30.0

# If that formula does not exist, install from the GitHub release:
curl -L https://github.com/ollama/ollama/releases/download/v0.30.0/Ollama-darwin.zip \
  -o ~/Downloads/Ollama-0.30.0.zip
unzip ~/Downloads/Ollama-0.30.0.zip -d /Applications/

Linux

# Download a specific version binary
curl -L https://github.com/ollama/ollama/releases/download/v0.30.0/ollama-linux-amd64 \
  -o /usr/local/bin/ollama
chmod +x /usr/local/bin/ollama

# Restart the service
sudo systemctl restart ollama

# Verify
ollama --version

Docker

# Use a specific tag instead of :latest
docker pull ollama/ollama:0.30.0
docker stop ollama && docker rm ollama
docker run -d --gpus all -v ollama:/root/.ollama \
  -p 11434:11434 --name ollama ollama/ollama:0.30.0

Pinning a Version (Preventing Auto-Updates)

# macOS — pin the Homebrew formula
brew pin ollama

# Linux — hold the package if installed via apt
sudo apt-mark hold ollama

# Docker — always use a specific tag, never :latest

Warning: Rolling back from v0.4.0+ to v0.3.x requires restoring ~/.ollama from a backup made before the upgrade, because the storage format migration in v0.4.0 is one-way. Always back up before major version jumps.


Release Cadence and Roadmap {#release-cadence}

Ollama ships extremely frequently — often several patch releases per week within a minor line, and a new minor version (0.29 → 0.30, etc.) every few weeks. As of mid-June 2026 it sits at v0.30.10, having moved through roughly 30 minor releases since the first public version in 2023.

The clearest recent direction is hardware acceleration and model breadth: the MLX backend for Apple Silicon (v0.19, March 2026) and the ongoing 0.30-series work pairing MLX with an updated llama.cpp engine for wider GPU support, plus a steady stream of new model architectures (Command A, the North family, Cohere2Moe, Gemma 4, and more) added almost every release.

Ollama does not publish a fixed public roadmap, so rather than guess at unreleased features, track development directly at github.com/ollama/ollama/releases and the official Ollama blog.


Troubleshooting Update Issues {#troubleshooting}

"ollama: command not found" after update

# macOS — Homebrew may have changed the symlink
brew unlink ollama && brew link ollama

# Linux — verify the binary path
which ollama
# If empty, re-run the install script
curl -fsSL https://ollama.com/install.sh | sh

# Windows — restart your terminal or reboot
# The installer adds Ollama to PATH, but existing terminals
# do not pick it up until reopened

Models disappear after update

Models should survive updates. If they are gone:

# Check if the models directory still exists
ls -la ~/.ollama/models/

# If it is empty, the update may have changed OLLAMA_MODELS path
# Check your environment
echo $OLLAMA_MODELS

# Re-pull missing models
ollama pull llama3.2

Service will not start after update

# Linux — check systemd logs
journalctl -u ollama -n 50

# macOS — check launchd logs
log show --predicate 'process == "ollama"' --last 5m

# Common fix: port conflict from old process
lsof -i :11434
kill -9 <PID>
ollama serve

CUDA / ROCm errors after update

# Verify your GPU driver version
nvidia-smi  # NVIDIA
rocm-smi    # AMD

# Recent Ollama versions generally need a reasonably current GPU stack:
# NVIDIA: Driver 535+ (CUDA 12.2+)
# AMD: ROCm 6.0+
# (Check the release notes for your exact version — minimums shift over time.)

# If your driver is too old, either:
# 1. Update your GPU driver
# 2. Roll back Ollama to a version that supports your driver

If you hit issues not covered here, check the general Ollama troubleshooting guide or the project's GitHub issues page. For platform-specific installation help, see our Windows installation guide or Mac setup guide.


Staying Current Without Breaking Things

My recommendation: update monthly, not on release day. Let the community shake out bugs for a week or two before you upgrade. Pin your version in production environments and always back up ~/.ollama before major version jumps.

Set a reminder to check your version:

# Add to your .bashrc or .zshrc
alias ollama-check='echo "Installed: $(ollama --version)" && echo "Latest: check https://github.com/ollama/ollama/releases"'

Ollama's release velocity is a strength — they ship features fast and respond to bugs quickly. But that pace means every update deserves a quick test before you trust it with production workloads.


Running Ollama for the first time? Start with the complete Ollama guide for setup instructions, or compare the best Ollama models for your hardware.

🎯
AI Learning Path

Ollama’s running. Here’s what to build with it.

Go from “ollama run” to RAG apps, agents, and fine-tuned models — structured and hands-on. First chapter free.

Or own it for life — Lifetime $149 $599, pay once

Liked this? 20 full AI courses are waiting.

From fundamentals to RAG, agents, MCP servers, voice AI, and production deployment with real GitHub repos. First chapter free, every course.

Reading now
Join the discussion

Local AI Master Research Team

Creator of Local AI Master. I've built datasets with over 77,000 examples and trained AI models from scratch. Now I help people achieve AI independence through local AI mastery.

Build Real AI on Your Machine

RAG, agents, NLP, vision, and MLOps - chapters across 20 courses that take you from reading about AI to building AI.

Want structured AI education?

20 courses, 495+ chapters, from $9. Understand AI, don't just use it.

AI Learning Path
More on Ollama
See the full Best Ollama Models 2026 guide.

Comments (0)

No comments yet. Be the first to share your thoughts!

📅 Published: April 10, 2026🔄 Last Updated: June 19, 2026✓ Manually Reviewed
LM

Written by the Local AI Master Team

The team behind Local AI Master

We build Local AI Master around practical, testable local AI workflows: model selection, hardware planning, RAG systems, agents, and MLOps. The goal is to turn scattered tutorials into a structured learning path you can follow on your own hardware.

✓ Local AI Curriculum✓ Hands-On Projects✓ Open Source Contributor

Get Ollama Release Alerts

Stay ahead of breaking changes. Get version updates, migration guides, and performance tips when new Ollama releases ship.

Build Real AI on Your Machine

RAG, agents, NLP, vision, and MLOps - chapters across 20 courses that take you from reading about AI to building AI.

Was this helpful?

📚
Free · no account required

Grab the AI Starter Kit — career roadmap, cheat sheet, setup guide

No spam. Unsubscribe with one click.

🎯
AI Learning Path

Ollama’s running. Here’s what to build with it.

Go from “ollama run” to RAG apps, agents, and fine-tuned models — structured and hands-on. First chapter free.

Or own it for life — Lifetime $149 $599, pay once
Free Tools & Calculators