Harrier OSS v1 27B
Harrier OSS v1 27B is a released general LLM work model with open-source; evaluate it while provider pricing coverage matures.
Use it for
- Teams evaluating general LLM work
- Workloads that can use a 33k context window
Do not use it for
- Cost-sensitive launches that need sourced token pricing
- Vision or document-understanding workloads
- Strict JSON or tool-calling flows
Advancing the state-of-the-art in AI and computing.
No tracked provider token pricing is available yet.
About
Microsoft's largest open-source multilingual text embedding model, released March 30, 2026. Decoder-only architecture based on Gemma 3, with last-token pooling and L2 normalization. Produces 5,376-dimensional embeddings. Ranked #1 on multilingual MTEB-v2 benchmark (score: 74.3). Supports 94+ languages. MIT license. Available on HuggingFace and Azure AI Foundry.
Harrier OSS v1 27B is an open-source model in the Harrier family. The structured metadata tracks a 33k-token context window. No headline benchmark score is tracked for Harrier OSS v1 27B yet.
Top use-case fit
No primary decision-task fit is mapped for this model yet.
Provider price ladder
No tracked provider token pricing is available for this model yet.
Capabilities
No model capability flags are currently sourced.
Benchmark peer barsfor Coding
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.
Advancing the state-of-the-art in AI and computing.
No tracked provider token pricing is available yet.