Ollama - Package Updates

[Package Updates]

[1.1.0]

• Update ollama to 0.13.0
• Full Changelog
• DeepSeek-OCR is now supported
• DeepSeek-V3.1 architecture is now supported in Ollama's engine
• Fixed performance issues that arose in Ollama 0.12.11 on CUDA
• Fixed issue where Linux install packages were missing required Vulkan libraries
• Improved CPU and memory detection while in containers/cgroups
• Improved VRAM information detection for AMD GPUs
• Improved KV cache performance to no longer require defragmentation

[Package Updates]

[1.1.1]

• Update ollama to 0.13.1
• Full Changelog
• nomic-embed-text will now use Ollama's engine by default
• Tool calling support for cogito-v2.1
• Fixed issues with CUDA VRAM discovery
• Fixed link to docs in Ollama's app
• Fixed issue where models would be evicted on CPU-only systems
• Ollama will now better render errors instead of showing Unmarshal: errors
• Fixed issue where CUDA GPUs would fail to be detected with older GPUs
• Added thinking and tool parsing for cogito-v2.1

[Package Updates]

[1.1.2]

• Increase the proxy read timeout to 1h

[Package Updates]

[1.1.3]

• Disable body size check within the app

[Package Updates]

[1.1.4]

• Update ollama to 0.13.3

[Package Updates]

[1.1.5]

• Update ollama to 0.13.4
• Full Changelog
• Nemotron 3 Nano: A new Standard for Efficient, Open, and Intelligent Agentic Models
• Olmo 3 and Olmo 3.1: A series of Open language models designed to enable the science of language models. These models are pre-trained on the Dolma 3 dataset and post-trained on the Dolci datasets.
• Enable Flash Attention automatically for models by default
• Fixed handling of long contexts with Gemma 3 models
• Fixed issue that would occur with Gemma 3 QAT models or other models imported with the Gemma 3 architecture

[Package Updates]

[1.1.6]

• Update ollama to 0.13.5
• Full Changelog
• Google's FunctionGemma is now available on Ollama
• bert architecture models now run on Ollama's engine
• Added built-in renderer & tool parsing capabilities for DeepSeek-V3.1
• Fixed issue where nested properties in tools may not have been rendered properly

[Package Updates]

[1.2.0]

• Update ollama to 0.14.0
• Full Changelog
• ollama run --experimental CLI will now open a new Ollama CLI that includes an agent loop and the bash tool
• Anthropic API compatibility: support for the /v1/messages API
• A new REQUIRES command for the Modelfile allows declaring which version of Ollama is required for the model
• For older models, Ollama will avoid an integer underflow on low VRAM systems during memory estimation
• More accurate VRAM measurements for AMD iGPUs
• Ollama's app will now highlight swift soure code
• An error will now return when embeddings return NaN or -Inf
• Ollama's Linux install bundles files now use zst compression
• New experimental support for image generation models, powered by MLX

[Package Updates]

[1.2.1]

• Update ollama to 0.14.1
• Full Changelog
• fix macOS auto-update signature verification failure

[Package Updates]

[1.2.3]

• Update ollama to 0.14.3
• Full Changelog
• Z-Image Turbo: 6 billion parameter text-to-image model from Alibabas Tongyi Lab. It generates high-quality photorealistic images.
• Flux.2 Klein: Black Forest Labs fastest image-generation models to date.
• Fixed issue where Ollama's macOS app would interrupt system shutdown
• Fixed ollama create and ollama show commands for experimental models
• The /api/generate API can now be used for image generation
• Fixed minor issues in Nemotron-3-Nano tool parsing
• Fixed issue where removing an image generation model would cause it to first load
• Fixed issue where ollama rm would only stop the first model in the list if it were running

[Package Updates]

[1.3.0]

• Update ollama to 0.15.0
• Full Changelog
• A new ollama launch command to use Ollama's models with Claude Code, Codex, OpenCode, and Droid without separate configuration.
• New ollama launch command for Claude Code, Codex, OpenCode, and Droid
• Fixed issue where creating multi-line strings with """ would not work when using ollama run
• <kbd>Ctrl</kbd>+<kbd>J</kbd> and <kbd>Shift</kbd>+<kbd>Enter</kbd> now work for inserting newlines in ollama run
• Reduced memory usage for GLM-4.7-Flash models

[Package Updates]

[1.3.1]

• Update ollama to 0.15.1
• Full Changelog
• GLM-4.7-Flash performance and correctness improvements, fixing repetitive answers and tool calling quality
• Fixed performance issues on macOS and arm64 Linux
• Fixed issue where ollama launch would not detect claude and would incorrectly update opencode configurations

[Package Updates]

[1.3.2]

• Update ollama to 0.15.2
• Full Changelog
• New ollama launch clawdbot command for launching Clawdbot using Ollama models

[Package Updates]

[1.3.3]

• Update ollama to 0.15.4
• Full Changelog
• ollama launch openclaw will now enter the standard OpenClaw onboarding flow if this has not yet been completed.
• Renamed ollama launch clawdbot to ollama launch openclaw to reflect the project's new name
• Improved tool calling for Ministral models
• ollama launch will now use the value of OLLAMA_HOST when running it

[Package Updates]

[1.3.4]

• Update ollama to 0.15.5
• Full Changelog
• Improvements to ollama launch
• Sub-agent support for ollama launch for planning, deep research, and similar tasks
• ollama signin will now open a browser window to make signing in easier
• Ollama will now default to the following context lengths based on VRAM:
• GLM-4.7-Flash support on Ollama's experimental MLX engine
• ollama signin will now open the browser to the connect page
• Fixed off by one error when using num_predict in the API
• Fixed issue where tokens from a previous sequence would be returned when hitting num_predict

[Package Updates]

[1.3.5]

• Update ollama to 0.15.6
• Full Changelog
• Fixed context limits when running ollama launch droid
• ollama launch will now download missing models instead of erroring
• Fixed bug where ollama launch claude would cause context compaction when providing images

[Package Updates]

[1.4.0]

• Update ollama to 0.16.1
• Full Changelog
• Installing Ollama via the curl install script on macOS will now only prompt for your password if its required
• Installing Ollama via the iem install script in Windows will now show progress
• Image generation models will now respect the OLLAMA_LOAD_TIMEOUT variable
• GLM-5: A strong reasoning and agentic model from Z.ai with 744B total parameters (40B active), built for complex systems engineering and long-horizon tasks.
• MiniMax-M2.5: a new state-of-the-art large language model designed for real-world productivity and coding tasks.
• The new ollama command makes it easy to launch your favorite apps with models using Ollama
• Launch Pi with ollama launch pi
• Improvements to Ollama's MLX runner to support GLM-4.7-Flash
• Ctrl+G will now allow for editing text prompts in a text editor when running a model

[Package Updates]

[1.4.1]

• Update ollama to 0.16.2
• Full Changelog
• ollama launch claude now supports searching the web when using :cloud models
• Fixed rendering issue when running ollama in PowerShell
• New setting in Ollama's app makes it easier to disable cloud models for sensitive and private tasks where data cannot leave your computer. For Linux or when running ollama serve manually, set OLLAMA_NO_CLOUD=1.
• Fixed issue where experimental image generation models would not run in 0.16.0 and 0.16.1

[Package Updates]

[1.4.2]

• Update ollama to 0.16.3
• Full Changelog
• New ollama launch cline added for the Cline CLI
• ollama launch <integration> will now always show the model picker
• Added Gemma 3, Llama and Qwen 3 architectures to MLX runner

[Package Updates]

[1.5.0]

• Update ollama to 0.17.0
• Full Changelog
• OpenClaw can now be installed and configured automatically via Ollama, making it the easiest way to get up and running with OpenClaw with open models like Kimi-K2.5, GLM-5, and Minimax-M2.5.
• When using cloud models, websearch is enabled - allowing OpenClaw to search the internet.
• Improved tokenizer performance
• Ollama's macOS and Windows apps will now default to a context length based on available VRAM