Ollama

New models

• WizardLM 2: State of the art large language model from Microsoft AI with improved performance on complex chat, multilingual, reasoning and agent use cases.
  • wizardlm2:8x22b: large 8x22B model based on Mixtral 8x22B
  • wizardlm2:7b: fast, high-performing model based on Mistral 7B
• Snowflake Arctic Embed: A suite of text embedding models by Snowflake, optimized for performance.
• Command R+: a powerful, scalable large language model purpose-built for RAG use cases
• DBRX: A large 132B open, general-purpose LLM created by Databricks.
• Mixtral 8x22B: the new leading Mixture of Experts (MoE) base model by Mistral AI.

What's Changed

• Ollama will now better utilize available VRAM, leading to less out-of-memory errors, as well as better GPU utilization
• When running larger models that don't fit into VRAM on macOS, Ollama will now split the model between GPU and CPU to maximize performance.
• Fixed several issues where Ollama would hang upon encountering an error
• Fix issue where using quotes in OLLAMA_ORIGINS would cause an error

New Contributors

• @sugarforever made their first contribution in https://github.com/ollama/ollama/pull/3400
• @yaroslavyaroslav made their first contribution in https://github.com/ollama/ollama/pull/3378
• @Nagi-ovo made their first contribution in https://github.com/ollama/ollama/pull/3423
• @ParisNeo made their first contribution in https://github.com/ollama/ollama/pull/3436
• @philippgille made their first contribution in https://github.com/ollama/ollama/pull/3437
• @cesto93 made their first contribution in https://github.com/ollama/ollama/pull/3461
• @ThomasVitale made their first contribution in https://github.com/ollama/ollama/pull/3515
• @writinwaters made their first contribution in https://github.com/ollama/ollama/pull/3539
• @alexmavr made their first contribution in https://github.com/ollama/ollama/pull/3555

Full Changelog: https://github.com/ollama/ollama/compare/v0.1.31...v0.1.32