Impact Score: 5/10
Ollama v0.1.32 — Release Notes & Engineering Impact
Source available — automated, not human-reviewed
Component: ollama · Channel: stable. Automated analysis, not a compatibility certification. How this works.
Analysis updated: 2026-11-01.
⚡ Executive Summary (TL;DR)
Ollama v0.1.32. Source highlight: WizardLM 2: State of the art large language model from Microsoft AI with improved performance on complex chat, multilingual, reasoning and agent use cases.
Who Does This Impact? (Role-Based Analysis)
💻 Software Engineers & Devs
Check the source notes against the package and APIs you use before upgrading.
📊 Product & Engineering Leads
Use the documented changes to assess relevance to your product; release frequency alone is not a quality measure.
⚙️ DevOps & Security
Verify the target version, runtime requirements and rollback procedure in the official documentation.
⚡ Performance & Enhancements (4)
- WizardLM 2: State of the art large language model from Microsoft AI with improved performance on complex chat, multilingual, reasoning and agent use cases.
- `wizardlm2:7b`: fast, high-performing model based on Mistral 7B
- Snowflake Arctic Embed: A suite of text embedding models by Snowflake, optimized for performance.
- 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.
🔧 Bug Fixes & Patches (2)
- Fixed several issues where Ollama would hang upon encountering an error
- Fix issue where using quotes in `OLLAMA_ORIGINS` would cause an error
📄 View Raw Release Notes (Original Developer Log)
## New models
* [WizardLM 2](https://ollama.com/library/wizardlm2): 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](https://ollama.com/library/snowflake-arctic-embed): A suite of text embedding models by Snowflake, optimized for performance.
* [Command R+](https://ollama.com/library/command-r-plus): a powerful, scalable large language model purpose-built for RAG use cases
* [DBRX](https://ollama.com/library/dbrx): A large 132B open, general-purpose LLM created by Databricks.
* [Mixtral 8x22B](https://ollama.com/library/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