What's Changed

• Fixed error that would occur when running Ollama on Linux machines with the ARM architecture
• Ollama will now show an improved error message when attempting to run unsupported models
• Fixed issue where Ollama would not auto-detect the chat template for Llama 3.1 models
• OLLAMA_HOST will now work with with URLs that contain paths

New Contributors

• @bryanhonof made their first contribution in #6074

Full Changelog: v0.3.8...v0.3.9

What's Changed

• Fixed error where the ollama CLI couldn't be found on the path when upgrading Ollama on Windows

New Contributors

• @seankhatiri made their first contribution in #6530

Full Changelog: v0.3.7...v0.3.8

New Models

• Hermes 3: Hermes 3 is the latest version of the flagship Hermes series of LLMs by Nous Research, which includes support for tool calling.
• Phi 3.5: A lightweight AI model with 3.8 billion parameters with performance overtaking similarly and larger sized models.
• SmolLM: A family of small models with 135M, 360M, and 1.7B parameters, trained on a new high-quality dataset.

What's Changed

• CUDA 12 support: improving performance by up to 10% on newer NVIDIA GPUs
• Improved performance of ollama pull and ollama push on slower connections
• Fixed issue where setting OLLAMA_NUM_PARALLEL would cause models to be reloaded on lower VRAM systems
• Ollama on Linux is now distributed as a tar.gz file, which contains the ollama binary along with required libraries.

New Contributors

• @pamelafox made their first contribution in #6345
• @eust-w made their first contribution in #5964

Full Changelog: v0.3.6...v0.3.7

What's Changed

• Fixed issue where /api/embed would return an error instead of loading the model when the input field was not provided.
• ollama create can now import Phi-3 models from Safetensors
• Added progress information to ollama create when importing GGUF files
• Ollama will now import GGUF files faster by minimizing file copies

Full Changelog: v0.3.5...v0.3.6

What's Changed

• Fixed Incorrect function error when downloading models on Windows
• Fixed issue where temporary files would not be cleaned up
• Fix rare error when Ollama would start up due to invalid model data
• Ollama will now provide an error instead of crashing on Windows when running models that are too large to fit into total memory

New Contributors

• @jessegross made their first contribution in #6145
• @rgbkrk made their first contribution in #5985
• @Nicholas42 made their first contribution in #6235
• @cognitivetech made their first contribution in #6305

Full Changelog: v0.3.4...v0.3.5

New embedding models

• BGE-M3: a large embedding model from BAAI distinguished for its versatility in Multi-Functionality, Multi-Linguality, and Multi-Granularity.
• BGE-Large: a large embedding model trained in english.
• Paraphrase-Multilingual: A multilingual embedding model trained on parallel data for 50 languages.

New embedding API with batch support

Ollama now supports a new API endpoint /api/embed for embedding generation:

curl http://localhost:11434/api/embed -d '{
  "model": "all-minilm",
  "input": ["Why is the sky blue?", "Why is the grass green?"]
}'

This API endpoint supports new features:

• Batches: generate embeddings for several documents in one request
• Normalized embeddings: embeddings are now normalized, improving similarity results
• Truncation: a new truncate parameter that will error if set to false
• Metrics: responses include load_duration, total_duration and prompt_eval_count metrics

See the API documentation for more details and examples.

What's Changed

• Fixed initial slow download speeds on Windows
• NUMA support will now be autodetected by Ollama to improve performance
• Fixed issue where the /api/embed would sometimes return embedding results out of order

New Contributors

• @av made their first contribution in #6147
• @sryu1 made their first contribution in #6151
• @rick-github made their first contribution in #6154

Full Changelog: v0.3.3...v0.3.4

What's Changed

• The /api/embed endpoint now returns statistics: total_duration, load_duration, and prompt_eval_count
• Added usage metrics to the /v1/embeddings OpenAI compatibility API
• Fixed issue where /api/generate would respond with an empty string if provided a context
• Fixed issue where /api/generate would return an incorrect value for context
• /show modefile will now render MESSAGE commands correctly

New Contributors

• @slouffka made their first contribution in #6115

Full Changelog: v0.3.2...v0.3.3

What's Changed

• Fixed issue where ollama pull would not resume download progress
• Fixed issue where phi3 would report an error on older versions

New Contributors

• @longseespace made their first contribution in #6096

Full Changelog: v0.3.1...v0.3.2

Google's Gemma 2 has a new 2B parameter small model!

ollama run gemma2:2b

New models

• Gemma 2 2B: A new 2B parameter model by Google DeepMind

What's Changed

• Added support for min_p sampling option
• ollama create will now autodetect required stop parameters when importing certain models
• Ollama on Windows will now show better error messages if required files are missing
• Fixed issue where /save would cause parameters to be saved incorrectly
• OpenAI-compatible API will now return a finish_reason of tool_calls if a tool call occured.
• Performance and reliability improvements when downloading models using ollama pull
• Ollama's Linux install script will now return a better error on unsupported CUDA versions

New Contributors

• @Robitx made their first contribution in #1825
• @hellerve made their first contribution in #6041

Full Changelog: v0.3.0...v0.3.1

Tool support

Ollama now supports tool calling with popular models such as Llama 3.1. This enables a model to answer a given prompt using tool(s) it knows about, making it possible for models to perform more complex tasks or interact with the outside world.

Example tools include:

• Functions and APIs
• Web browsing
• Code interpreter
• much more!

To use tools, provide the tools field when using Ollama's Chat API:

import ollama

response = ollama.chat(
    model='llama3.1',
    messages=[{'role': 'user', 'content': 'What is the weather in Toronto?'}],

    # provide a weather checking tool to the model
    tools=[{
      'type': 'function',
      'function': {
        'name': 'get_current_weather',
        'description': 'Get the current weather for a city',
        'parameters': {
          'type': 'object',
          'properties': {
            'city': {
              'type': 'string',
              'description': 'The name of the city',
            },
          },
          'required': ['city'],
        },
      },
    },
  ],
)

print(response['message']['tool_calls'])

More information:

• Python example
• JavaScript example
• API Reference

New models

• Llama 3.1: a new state-of-the-art model from Meta available in 8B, 70B and 405B parameter sizes with support for tool calling.
• Mistral Large 2: Mistral's new 123B flagship model that is significantly more capable in code generation, tool calling, mathematics, and reasoning with 128k context window and support for dozens of languages.
• Firefunction v2: An open weights function calling model based on Llama 3, competitive with GPT-4o function calling capabilities.
• Llama-3-Groq-Tool-Use: A series of models from Groq that represent a significant advancement in open-source AI capabilities for tool use/function calling.

What's Changed

• Fixed duplicate error message when running ollama create

New Contributors

• @lreed-mdsol made their first contribution in #5757
• @ajhai made their first contribution in #5799

Full Changelog: v0.2.8...v0.3.0