All tasks / Comparisons
F2LLM-v2-14B vs harrier-oss-v1-27b
Compared only on public benchmark results, across the 1 task where both are listed: harrier-oss-v1-27b is a tier higher in 1 of 1 shared task.
F2LLM-v2-14B
Open-weights Apache-2.0 multilingual text embedding models from codefuse-ai, from 80M to 14B parameters.
- Vendor
- Ant Group (codefuse-ai)
- Weights
- Open: run it yourself
- Released
- Mar 2026
- GPU memory to run locally
- ~28 GB
- License
- Apache-2.0
- Last verified
- 19 Oct 2026
harrier-oss-v1-27b
Microsoft's MIT-licensed open-weights multilingual text embedding models, in 27B, 0.6B and 270M sizes.
- Vendor
- Microsoft
- Weights
- Open: run it yourself
- Released
- Mar 2026
- GPU memory to run locally
- ~54 GB
- License
- MIT
- Last verified
- 19 Oct 2026
Task by task
| Task | F2LLM-v2-14B | harrier-oss-v1-27b | Higher tier |
|---|---|---|---|
| Embeddings & retrieval Models | A68.7% on MTEB(Multilingual, v2) · Local | S74.3% on MTEB(Multilingual, v2) · Local | harrier-oss-v1-27b |
A tier spans a range of scores, and small gaps on a leaderboard are often within its margin of error, so only a different tier counts as ahead. How we rank.
Same benchmark, both results
| Benchmark | F2LLM-v2-14B | harrier-oss-v1-27b | Snapshot |
|---|---|---|---|
| MTEB(Multilingual, v2) Mean (Task): average main score over 131 multilingual tasks (bitext mining, classification, clustering, retrieval, reranking, STS, instruction reranking), higher is better | 68.7% | 74.3% | 19 Oct 2026 |