F2LLM 0.6B measured on 19 of 261 Embeddings benchmarks19
BenchmarkByScoreRank
No benchmark matches
self-host onlyprice
55.7MTEB English v2
Sep 2025released
1,024Dimensions
41K tokensMax input
enLanguages
Rankingconfiguration unstated?
Full ranking →···
61KaLM Embedding Multilingual Mini v168.962F2LLM 0.6B68.863F2LLM v2 160M68.8Strong at
Alternatives?
ModelScoreCostPriceWhat changes
BetterEmbeddingGemma 300MunstatedOpen+18%—$0.002Max input: 41K tokens → 2K tokens+1
OpenQwen 3 Embedding 8Bunstated+29%—$0.01Max input: 41K tokens → 33K tokens+2BetterQwen 3 Embedding 0.6BunstatedOpen+18%—$0.01Max input: 41K tokens → 33K tokens+1
BetterBge M3unstatedOpen+14%—$0.01Max input: 41K tokens → 8K tokens+1iBetterMultilingual E5 Large InstructunstatedOpen+14%—$0.01Max input: 41K tokens → 1K tokensModelScoreCostPriceWhat changes
Nothing here yet.
ModelScoreCostPriceWhat changes
EmbeddingGemma 300MunstatedOpen+18%—$0.002Max input: 41K tokens → 2K tokens+1Qwen 3 Embedding 8BunstatedOpen+29%—$0.01Max input: 41K tokens → 33K tokens+2Qwen 3 Embedding 0.6BunstatedOpen+18%—$0.01Max input: 41K tokens → 33K tokens+1Bge M3unstatedOpen+14%—$0.01Max input: 41K tokens → 8K tokens+1iMultilingual E5 Large InstructunstatedOpen+14%—$0.01Max input: 41K tokens → 1K tokensModelScoreCostPriceWhat changes
Qwen 3 Embedding 8BunstatedOpen+29%—$0.01Max input: 41K tokens → 33K tokens+2oArabic English Sts MatryoshkaunstatedOpen+29%——Max input: 41K tokens → 1K tokensQwen 3 Embedding 4BunstatedOpen+26%—$0.02Max input: 41K tokens → 33K tokens+2OOcten Embedding 8BOpen+25%——Memory (4-bit): 0.4 GB → 4.5 GB
KaLM Embedding Gemma3 12B 2511Open+24%——Languages: not verified+1ModelScoreCostPriceWhat changes
cF2LLM v2 14BunstatedOpen+10%——Memory (4-bit): 0.4 GB → 8.4 GBcF2LLM v2 8BunstatedOpen+10%——Memory (4-bit): 0.4 GB → 4.5 GBcF2LLM v2 4BunstatedOpen+9%——Memory (4-bit): 0.4 GB → 2.4 GBcF2LLM v2 1.7BunstatedOpen+9%——Memory (4-bit): 0.4 GB → 1 GBcF2LLM v2 0.6BunstatedOpen+6%——cF2LLM v2 330MunstatedOpen+3%——cF2LLM v2 160MunstatedOpensame——cF2LLM v2 80MunstatedOpen-2%——All codefuse-ai models →Run it yourself
estimateFits on✓ 8 GB (phone, laptop) · full quality✓ 16 GB · full quality✓ 24 GB GPU · full quality✓ 48 GB GPU · full quality✓ 80 GB GPU · full quality
LicenceApache-2.0free for commercial use
History
2 versionsBenchmarks
in Embeddings & RetrievalFAQ
How much does F2LLM 0.6B cost?›
There is no per-unit API price: self-host only.
Is F2LLM 0.6B free to use?›
There is no free API. The weights are open, so you can run it yourself.
How good is F2LLM 0.6B, and what is it best at?›
#52 of 200 in Embeddings.
Is F2LLM 0.6B better than KaLM Embedding Multilingual Mini v1?›
On MTEB Thai v1 · Pair Classification · Thai, F2LLM 0.6B scores 68.8 vs 68.9 — about the same.
When was F2LLM 0.6B released? Is there a newer version?›
Released 2025-09-18. It is the current version in its line.
Is F2LLM 0.6B open source?›
Yes, the weights are open (Apache-2.0 licence).
Can I run F2LLM 0.6B locally?›
The weights are open and can be self-hosted; hardware needs are not confirmed yet.
What is F2LLM 0.6B?›
F2LLM 0.6B is an open-weights embeddings & retrieval model from codefuse-ai, released Sep 2025.
What are the best alternatives to F2LLM 0.6B?›
EmbeddingGemma 300M (better), Qwen 3 Embedding 8B (open weights).