All tasks / Comparisons

F2LLM-v2-14B vs harrier-oss-v1-0.6b

Compared only on public benchmark results, across the 1 task where both are listed: they share a tier in 1.

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

Alternatives to F2LLM-v2-14B

harrier-oss-v1-0.6b

0.6B member of Microsoft's MIT-licensed Harrier OSS embedding family, sized for consumer GPUs and CPUs.

Vendor
Microsoft
Weights
Open: run it yourself
Released
Mar 2026
GPU memory to run locally
~2 GB
License
MIT
Last verified
19 Oct 2026

Alternatives to harrier-oss-v1-0.6b

Task by task

TaskF2LLM-v2-14Bharrier-oss-v1-0.6bHigher tier
Embeddings & retrieval
Models
A68.7% on MTEB(Multilingual, v2) · LocalA69% on MTEB(Multilingual, v2) · LocalSame tier

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

BenchmarkF2LLM-v2-14Bharrier-oss-v1-0.6bSnapshot
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%69%19 Oct 2026