F2LLM 1.7B measured on 12 of 261 Embeddings benchmarks12
BenchmarkByScoreRank
No benchmark matches
self-host onlyprice
57.8MTEB English v2
Sep 2025released
2,048Dimensions
41K tokensMax input
enLanguages
Rankingconfiguration unstated?
Full ranking →···
118Snowflake Arctic Embed M v1.529.9119F2LLM 1.7B29.9120Bilingual Embedding Small29.8Strong at
Alternatives?
ModelScoreCostPriceWhat changes
BetterEmbeddingGemma 300MunstatedOpen+26%—$0.002Max input: 41K tokens → 2K tokens+1aOpenLGAI Embedding Previewunstated+30%——Max input: 41K tokens → 33K tokens+1iBetterE5 Base v2unstatedOpen+15%—$0.005Max input: 41K tokens → 1K tokens
BetterQwen 3 Embedding 8BunstatedOpen+17%—$0.01Max input: 41K tokens → 33K tokens+2
BetterBge M3unstatedOpen+16%—$0.01Max input: 41K tokens → 8K tokens+1ModelScoreCostPriceWhat changes
Nothing here yet.
ModelScoreCostPriceWhat changes
EmbeddingGemma 300MunstatedOpen+26%—$0.002Max input: 41K tokens → 2K tokens+1iE5 Base v2unstatedOpen+15%—$0.005Max input: 41K tokens → 1K tokensQwen 3 Embedding 8BunstatedOpen+17%—$0.01Max input: 41K tokens → 33K tokens+2Bge M3unstatedOpen+16%—$0.01Max input: 41K tokens → 8K tokens+1Qwen 3 Embedding 0.6BunstatedOpen+12%—$0.01Max input: 41K tokens → 33K tokens+1ModelScoreCostPriceWhat changes
aLGAI Embedding PreviewunstatedOpen+30%——Max input: 41K tokens → 33K tokens+1IICT TIME And Querit Embedding v1unstatedOpen+27%——Max input: 41K tokens → 33K tokens+2aGiga Embeddings InstructunstatedOpen+26%——Max input: 41K tokens → 4K tokens+1EmbeddingGemma 300MunstatedOpen+26%—$0.002Max input: 41K tokens → 2K tokens+1LLinq Embed MistralunstatedOpen+25%——Max input: 41K tokens → 33K tokens+1ModelScoreCostPriceWhat changes
cF2LLM v2 1.7BunstatedOpen+21%——cF2LLM v2 4BunstatedOpen+16%——Memory (4-bit): 1 GB → 2.4 GBcF2LLM v2 8BunstatedOpen+12%——Memory (4-bit): 1 GB → 4.5 GBcF2LLM 4BunstatedOpen+11%——Memory (4-bit): 1 GB → 2.4 GBcF2LLM v2 0.6BunstatedOpen+9%——cF2LLM v2 80MunstatedOpensame——cF2LLM v2 160MunstatedOpen-4%——cF2LLM v2 14BunstatedOpen-5%——Memory (4-bit): 1 GB → 8.4 GBAll 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 1.7B cost?›
There is no per-unit API price: self-host only.
Is F2LLM 1.7B free to use?›
There is no free API. The weights are open, so you can run it yourself.
How good is F2LLM 1.7B, and what is it best at?›
#40 of 200 in Embeddings. Strongest at: Embeddings & Retrieval.
Is F2LLM 1.7B better than Snowflake Arctic Embed M v1.5?›
On MTEB English v2 · Summarization · English, F2LLM 1.7B scores 29.9 vs 29.9 — about the same.
When was F2LLM 1.7B released? Is there a newer version?›
Released 2025-09-18. It is the current version in its line.
Is F2LLM 1.7B open source?›
Yes, the weights are open (Apache-2.0 licence).
Can I run F2LLM 1.7B locally?›
The weights are open and can be self-hosted; hardware needs are not confirmed yet.
What is F2LLM 1.7B?›
F2LLM 1.7B is an open-weights embeddings & retrieval model from codefuse-ai, released Sep 2025.
What are the best alternatives to F2LLM 1.7B?›
EmbeddingGemma 300M (better), LGAI Embedding Preview (open weights).