Updatify / Ollama | Release notes

What’s Changed

• Support for CUDA 13
• Improved memory usage when using gpt-oss in Ollama’s app
• Better scrolling better in Ollama’s app when submitting long prompts
• Cmd +/- will now zoom and shrink text in Ollama’s app
• Assistant messages can now by copied in Ollama’s app
• Fixed error that would occur when attempting to import satefensor files by @rick-github in https://github.com/ollama/ollama/pull/12176
• Improved memory estimates for hybrid and recurrent models by @gabe-l-hart in https://github.com/ollama/ollama/pull/12186
• Fixed error that would occur when when batch size was greater than context length
• Flash attention & KV cache quantization validation fixes by @jessegross in https://github.com/ollama/ollama/pull/12231
• Add dimensions field to embed requests by @mxyng in https://github.com/ollama/ollama/pull/12242
• Enable new memory estimates in Ollama’s new engine by default by @jessegross in https://github.com/ollama/ollama/pull/12252
• Ollama will no longer load split vision models in the Ollama engine by @jessegross in https://github.com/ollama/ollama/pull/12241

New Contributors

• @KashyapTan made their first contribution in https://github.com/ollama/ollama/pull/12188
• @carbonatedWaterOrg made their first contribution in https://github.com/ollama/ollama/pull/12230
• @fengyuchuanshen made their first contribution in https://github.com/ollama/ollama/pull/12249

Full Changelog: https://github.com/ollama/ollama/compare/v0.11.10…v0.11.11

New models

• EmbeddingGemma a new open embedding model that delivers best-in-class performance for its size

What’s Changed

• Support for EmbeddingGemma

Full Changelog: https://github.com/ollama/ollama/compare/v0.11.9…v0.11.10

What’s Changed

• Improved performance via overlapping GPU and CPU computations
• Fixed issues where unrecognized AMD GPU would cause an error
• Reduce crashes due to unhandled errors in some Mac and Linux installations of Ollama

New Contributors

• @alpha-nerd-nomyo made their first contribution in https://github.com/ollama/ollama/pull/12129
• @pxwanglu made their first contribution in https://github.com/ollama/ollama/pull/12123

Full Changelog: https://github.com/ollama/ollama/compare/v0.11.8…v0.11.9-rc0

What’s Changed

• gpt-oss now has flash attention enabled by default for systems that support it
• Improved load times for gpt-oss

Full Changelog: https://github.com/ollama/ollama/compare/v0.11.7…v0.11.8

DeepSeek-V3.1

DeepSeek-V3.1 is now available to run via Ollama.

This model supports hybrid thinking, meaning thinking can be enabled or disabled by setting think in Ollama’s API:

curl http://localhost:11434/api/chat -d '{
  "model": "deepseek-v3.1",
  "messages": [
    {
      "role": "user",
      "content": "why is the sky blue?"
    }
  ],
  "think": true
}'

In Ollama’s CLI, thinking can be enabled or disabled by running the /set think or /set nothink commands.

Turbo (in preview)

DeepSeek-V3.1 has over 671B parameters, and so a large amount of VRAM is required to run it. Ollama’s Turbo mode (in preview) provides access to powerful hardware in the cloud you can use to run the model.

Turbo via Ollama’s app

1. Download Ollama for macOS or Windows
2. Select deepseek-v3.1:671b from the model selector
3. Enable Turbo

Turbo via Ollama’s CLI and libraries

1. Create an account on ollama.com/signup
2. Follow the docs for Ollama’s CLI to upload authenticate your Ollama installation
3. Run the following:

OLLAMA_HOST=ollama.com ollama run deepseek-v3.1

What’s Changed

• Ollama’s app will now switch between chats faster
• Improved layout of messages in Ollama’s app
• Fixed issue where command prompt would show when Ollama’s app detected an old version of Ollama running
• Improved performance when using flash attention
• Fixed boundary case when encoding text using BPE

Full Changelog: https://github.com/ollama/ollama/compare/v0.11.5…v0.11.6

What’s Changed

• Performance improvements for the gpt-oss models
• New memory management: this release of Ollama includes improved memory management for scheduling models on GPUs, leading to better VRAM utilization, model performance and less out of memory errors. These new memory estimations can be enabled with OLLAMA_NEW_ESTIMATES=1 ollama serve and will soon be enabled by default.
• Improved multi-GPU scheduling and reduced VRAM allocation when using more than 2 GPUs
• Ollama’s new app will now remember default selections for default model, Turbo and Web Search between restarts
• Fix error when parsing bad harmony tool calls
• OLLAMA_FLASH_ATTENTION=1 will also enable flash attention for pure-CPU models
• Fixed OpenAI-compatible API not supporting reasoning_effort
• Reduced size of installation on Windows and Linux

New Contributors

• @vorburger made their first contribution in https://github.com/ollama/ollama/pull/11755
• @dan-and made their first contribution in https://github.com/ollama/ollama/pull/10678
• @youzichuan made their first contribution in https://github.com/ollama/ollama/pull/11880

Full Changelog: https://github.com/ollama/ollama/compare/v0.11.4…v0.11.5

What’s Changed

• openai: allow for content and tool calls in the same message by @drifkin in https://github.com/ollama/ollama/pull/11759
• openai: when converting role=tool messages, propagate the tool name by @drifkin in https://github.com/ollama/ollama/pull/11761
• openai: always provide reasoning by @drifkin in https://github.com/ollama/ollama/pull/11765

New Contributors

• @gao-feng made their first contribution in https://github.com/ollama/ollama/pull/11170

Full Changelog: https://github.com/ollama/ollama/compare/v0.11.3…v0.11.4

What’s Changed

• Fixed issue where gpt-oss would consume too much VRAM when split across GPU & CPU or multiple GPUs
• Statically link C++ libraries on windows for better compatibility

Full Changelog: https://github.com/ollama/ollama/compare/v0.11.2…v0.11.3

What’s Changed

• Fix crash in gpt-oss when using kv cache quanitization
• Fix gpt-oss bug with “currentDate” not defined

Full Changelog: https://github.com/ollama/ollama/compare/v0.11.1…v0.11.2

Welcome OpenAI’s gpt-oss models

Ollama partners with OpenAI to bring its latest state-of-the-art open weight models to Ollama. The two models, 20B and 120B, bring a whole new local chat experience, and are designed for powerful reasoning, agentic tasks, and versatile developer use cases.

Feature highlights

• Agentic capabilities: Use the models’ native capabilities for function calling, web browsing (Ollama is providing a built-in web search that can be optionally enabled to augment the model with the latest information), python tool calls, and structured outputs.
• Full chain-of-thought: Gain complete access to the model’s reasoning process, facilitating easier debugging and increased trust in outputs.
• Configurable reasoning effort: Easily adjust the reasoning effort (low, medium, high) based on your specific use case and latency needs.
• Fine-tunable: Fully customize models to your specific use case through parameter fine-tuning.
• Permissive Apache 2.0 license: Build freely without copyleft restrictions or patent risk—ideal for experimentation, customization, and commercial deployment.

Quantization - MXFP4 format

What’s Changed

• Fixed unicode character input for Japanese and other languages in Ollama’s new app
• Fixed AMD download URL in the logs for ollama serve

New Contributors

• @skools-here made their first contribution in https://github.com/ollama/ollama/pull/11579

Full Changelog: https://github.com/ollama/ollama/compare/v0.10.0…v0.10.1

Ollama’s new app

Ollama’s new app is available for macOS and Windows: Download Ollama

What’s Changed

• ollama ps will now show the context length of loaded models
• Improved performance in gemma3n models by 2-3x
• Parallel request processing now defaults to 1. For more details, see the FAQ
• Fixed issue where tool calling would not work correctly with granite3.3 and mistral-nemo models
• Fixed issue where Ollama’s tool calling would not work correctly if a tool’s name was part of of another one, such as add and get_address
• Improved performance when using multiple GPUs by 10-30%
• Ollama’s OpenAI-compatible API will now support WebP images
• Fixed issue where ollama show would report an error
• ollama run will more gracefully display errors

New Contributors

• @sncix made their first contribution in https://github.com/ollama/ollama/pull/11189
• @mfornet made their first contribution in https://github.com/ollama/ollama/pull/11425
• @haiyuewa made their first contribution in https://github.com/ollama/ollama/pull/11427
• @warting made their first contribution in https://github.com/ollama/ollama/pull/11461

What’s Changed

• Fixed styling issue in launch screen
• tool_name can now be provided in messages with "role": "tool" using the /api/chat endpoint

New Contributors

• @vrampal made their first contribution in https://github.com/ollama/ollama/pull/9681

Full Changelog: https://github.com/ollama/ollama/compare/v0.9.5…v0.9.6-rc0

Updates to Ollama for macOS and Windows

A new version of Ollama’s macOS and Windows applications are now available. New improvements to the apps will be introduced over the coming releases:

• Download for macOS
• Download for Windows

New features

Expose Ollama on the network

Ollama can now be exposed on the network, allowing others to access Ollama on other devices or even over the internet. This is useful for having Ollama running on a powerful Mac, PC or Linux computer while making it accessible to less powerful devices.

Model directory

The directory in which models are stored can now be modified! This allows models to be stored on external hard disks or alternative directories than the default.

Smaller footprint and faster starting on macOS

The macOS app is now a native application and starts much faster while requiring a much smaller installation.

Additional changes in 0.9.5

• Fixed issue where the ollama CLI would not be installed by Ollama on macOS on startup
• Fixed issue where files in ollama-darwin.tgz were not notarized

Updates to Ollama for macOS and Windows

A new version of Ollama’s macOS and Windows applications are now available. New improvements to the apps will be introduced over the coming releases:

• Download for macOS
• Download for Windows

New features

Expose Ollama on the network

Ollama can now be exposed on the network, allowing others to access Ollama on other devices or even over the internet. This is useful for having Ollama running on a powerful Mac, PC or Linux computer while making it accessible to less powerful devices.

Model directory

The directory in which models are stored can now be modified! This allows models to be stored on external hard disks or alternative directories than the default.

Smaller footprint and faster starting on macOS

The macOS app is now a native application and starts much faster while requiring a much smaller installation.

What’s Changed

• Reduced download size and startup time for Ollama on macOS
• Tool calling with empty parameters will now work correctly
• Fixed issue when quantizing models with the Gemma 3n architecture

Gemma 3n

Ollama now supports Gemma 3n.

Gemma 3n models are designed for efficient execution on everyday devices such as laptops, tablets or phones. These models were trained with data in over 140 spoken languages.

Effective 2B

ollama run gemma3n:e2b

Effective 4B

ollama run gemma3n:e4b

What’s Changed

• Fixed issue where errors would not be properly reported on Apple Silicon Macs
• Ollama will now limit context length to what the model was trained against to avoid strange overflow behavior

New Contributors

• @Aj-Seven made their first contribution in https://github.com/ollama/ollama/pull/11169

Full Changelog: https://github.com/ollama/ollama/compare/v0.9.2…v0.9.3

What’s Changed

• Fixed issue where tool calls without parameters would not be returned correctly
• Fixed does not support generate errors
• Fixed issue where some special tokens would not be tokenized properly for some model architectures

New Contributors

• @NGC13009 made their first contribution in https://github.com/ollama/ollama/pull/11080

Full Changelog: https://github.com/ollama/ollama/compare/v0.9.1…v0.9.2

Tool calling improvements

New tool calling support

The following models now support tool calling:

• DeepSeek-R1-2508 (671B model)
• Magistral

Tool calling reliability has also been improved for the following models:

• Llama 4
• Mistral

To re-download the models, use ollama pull.

New Ollama for macOS and Windows preview

A new version of Ollama’s macOS and Windows applications are available to test for early feedback. New improvements to the apps will be introduced over the coming releases:

• Download for macOS
• Download for Windows

If you have feedback, please create an issue on GitHub with the app label. These apps will automatically update themselves to future versions of Ollama, so you may have to redownload new preview versions in the future.

New features

Expose Ollama on the network

New models

• DeepSeek-R1-2508: DeepSeek-R1 has received a minor version upgrade to DeepSeek-R1-0528 for the 8 billion parameter distilled model and the full 671 billion parameter model. In this update, DeepSeek R1 has significantly improved its reasoning and inference capabilities.

Thinking

Ollama now has the ability to enable or disable thinking. This gives users the flexibility to choose the model’s thinking behavior for different applications and use cases.

When thinking is enabled, the output will separate the model’s thinking from the model’s output. When thinking is disabled, the model will not think and directly output the content.

Models that support thinking:

• DeepSeek R1
• Qwen 3
• more will be added under thinking models.

When running a model that supports thinking, Ollama will now display the model’s thoughts:

% ollama run deepseek-r1
>>> How many Rs are in strawberry
Thinking...
First, I need to understand what the question is asking. It's asking how many letters 'R' are present in the word "strawberry."

Next, I'll examine each letter in the word individually.

I'll start from the beginning and count every occurrence of the letter 'R.'

What’s Changed

• Ollama will now stream responses with tool calls blog post
• Logs will now include better memory estimate debug information when running models in Ollama’s engine.

New Contributors

• @hellotunamayo made their first contribution in https://github.com/ollama/ollama/pull/10790

Full Changelog: https://github.com/ollama/ollama/compare/v0.7.1…v0.8.0

What’s Changed

• Improved model memory management to allocate sufficient memory to prevent crashes when running multimodal models in certain situations
• Enhanced memory estimation for models to prevent unintended memory offloading
• ollama show will now show ... when data is truncated
• Fixed crash that would occur with qwen2.5vl
• Fixed crash on Nvidia’s CUDA for llama3.2-vision
• Support for Alibaba’s Qwen 3 and Qwen 2 architectures in Ollama’s new multimodal engine

New Contributors

• @ronxldwilson made their first contribution in https://github.com/ollama/ollama/pull/10763
• @DarkCaster made their first contribution in https://github.com/ollama/ollama/pull/10779

Full Changelog: https://github.com/ollama/ollama/compare/v0.7.0…v0.7.1

Ollama now supports multimodal models via Ollama’s new engine, starting with new vision multimodal models:

• Meta Llama 4
• Google Gemma 3
• Qwen 2.5 VL
• Mistral Small 3.1
• and more vision models.

What’s Changed

• Ollama now supports providing WebP images as input to multimodal models
• Fixed issue where a blank terminal window would appear when runnings models on Windows
• Fixed error that would occur when running llama4 on NVIDIA GPUs
• Reduced log level of key not found message
• Ollama will now correct remove quotes from image paths when sending images as input with ollama run
• Improved performance of importing safetensors models via ollama create
• Improved prompt processing speeds of Qwen3 MoE on macOS
• Fixed issue where providing large JSON schemas in structured output requests would result in an error
• Ollama’s API will now return code 405 instead of 404 for methods that are not allowed
• Fixed issue where ollama processes would continue to run after a model was unloaded

New Contributors

• @ashokgelal made their first contribution in https://github.com/ollama/ollama/pull/8668

What’s Changed

• Performance improvements for Qwen 3 MoE models (30b-a3b and 235b-a22b) on NVIDIA and AMD GPUs
• Fixed GGML_ASSERT(tensor->op == GGML_OP_UNARY) failed issue caused by conflicting installations
• Fixed a memory leak that occurred when providing images as input
• ollama show will now correctly label older vision models such as llava
• Reduced out of memory errors by improving worst-case memory estimations
• Fix issue that resulted in a context canceled error

New Contributors

• @AliAhmedNada made their first contribution in https://github.com/ollama/ollama/pull/10522
• @HarshNevse made their first contribution in https://github.com/ollama/ollama/pull/10465

Full Changelog: https://github.com/ollama/ollama/compare/v0.6.7…v0.6.8

New models

• Qwen 3: Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models.
• Phi 4 reasoning and Phi-4-mini-reasoning: New state-of-the-art reasoning models from Microsoft
• Llama 4: state-of-the-art multi-modal models from Meta

What’s Changed

• Add support for Meta’s Llama 4 multimodal models
• Add support for Microsoft’s Phi 4 reasoning models, and Phi 4 mini reasoning model
• Increased default context window to 4096 tokens
• Fixed issue where image paths would not be recognized with ~ when being provided to ollama run
• Improved output quality when using JSON mode in certain scenarios
• Fixed tensor->op == GGML_OP_UNARY errors when running a model due to conflicting inference libraries
• Fixed issue where model would be stuck in the Stopping... state

New Contributors

• @greengrass821 made their first contribution in https://github.com/ollama/ollama/pull/10339
• @richardshiue made their first contribution in https://github.com/ollama/ollama/pull/10335
• @aduermael made their first contribution in https://github.com/ollama/ollama/pull/10386