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.
Advancing the state-of-the-art in AI and computing.
No tracked provider 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.
Providers
No active provider routes are tracked 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.
Benchmark scores(1)
| Benchmark | Score | Version | Evaluation | Source |
|---|---|---|---|---|
| 74.27 | MTEB(Multilingual, v2)Observed 2026-10-17 | Harness: mteb 2.26.6 leaderboard aggregation, Mean (Task) over 131 tasks Evaluator: MTEB (embeddings-benchmark/results) Confidence: confirmed Notes: MTEB(Multilingual, v2) Mean (Task) 74.27 over 131 tasks; Mean (TaskType) 64.20. Computed with the leaderboard's own code (mteb 2.26.6 Benchmark summary table) from embeddings-benchmark/results @ 4bb41dd (2026-10-17). Source: MTEB (embeddings-benchmark/results, CC0). Retrieved 2026-10-17. Microsoft's harrier-oss-v1 card reports 74.3 (1 dp), consistent with this value. |
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 pricing is available yet.