Nano Em1 0.6B v2 measured on 11 of 261 Embeddings benchmarks11
BenchmarkByScoreRank
No benchmark matches
self-host onlyprice
43.2MTEB English v2
Jul 2026released
1,024Dimensions
41K tokensMax input
enLanguages
Rankingconfiguration unstated?
Full ranking →···
58NV Embed v184.159Nano Em1 0.6B v283.460Cde Small v183.3Strong at
Alternatives?
ModelScoreCostPriceWhat changes
BetterEmbeddingGemma 300MunstatedOpen+5%—$0.002Max input: 41K tokens → 2K tokens+1cOpenF2LLM 4Bunstated+10%——Memory (4-bit): 0.4 GB → 2.4 GB
BetterQwen 3 Embedding 8BunstatedOpen+8%—$0.01Max input: 41K tokens → 33K tokens+2
BetterBge En IclunstatedOpen+8%—$0.01Max input: 41K tokens → 33K tokens+2
BetterJina Embeddings v5 Text NanounstatedOpen+8%—$0.02Max input: 41K tokens → 8K tokens+1ModelScoreCostPriceWhat changes
Nothing here yet.
ModelScoreCostPriceWhat changes
EmbeddingGemma 300MunstatedOpen+5%—$0.002Max input: 41K tokens → 2K tokens+1Qwen 3 Embedding 8BunstatedOpen+8%—$0.01Max input: 41K tokens → 33K tokens+2Bge En IclunstatedOpen+8%—$0.01Max input: 41K tokens → 33K tokens+2Jina Embeddings v5 Text NanounstatedOpen+8%—$0.02Max input: 41K tokens → 8K tokens+1Qwen 3 Embedding 4BunstatedOpen+8%—$0.02Max input: 41K tokens → 33K tokens+2ModelScoreCostPriceWhat changes
cF2LLM 4BunstatedOpen+10%——Memory (4-bit): 0.4 GB → 2.4 GBcF2LLM v2 4BunstatedOpen+10%——Memory (4-bit): 0.4 GB → 2.4 GBaGiga Embeddings Instruct 10B A1.8B 0826unstatedOpen+10%——Max input: 41K tokens → 8K tokens+1cF2LLM v2 8BunstatedOpen+10%——Memory (4-bit): 0.4 GB → 4.5 GBaGiga Embeddings Instruct 3B 0826unstatedOpen+10%——Max input: 41K tokens → 8K tokens+1ModelScoreCostPriceWhat changes
KNano Em1 0.6B v2.1unstatedOpen+5%——Max input: 41K tokens → 8K tokensAll KiteFishAI 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 & RetrievalBEIR · Mean over tasks · English40.6#143
BEIR · Retrieval · English40.6#143
FAQ
How much does Nano Em1 0.6B v2 cost?›
There is no per-unit API price: self-host only.
Is Nano Em1 0.6B v2 free to use?›
There is no free API. The weights are open, so you can run it yourself.
How good is Nano Em1 0.6B v2, and what is it best at?›
#133 of 200 in Embeddings.
Is Nano Em1 0.6B v2 better than NV Embed v1?›
On MTEB English v2 · Classification · English, Nano Em1 0.6B v2 scores 83.4 vs 84.1 — about the same.
When was Nano Em1 0.6B v2 released? Is there a newer version?›
Released 2026-07-20. It is the current version in its line.
Is Nano Em1 0.6B v2 open source?›
Yes, the weights are open (Apache-2.0 licence).
Can I run Nano Em1 0.6B v2 locally?›
The weights are open and can be self-hosted; hardware needs are not confirmed yet.
What is Nano Em1 0.6B v2?›
Nano Em1 0.6B v2 is an open-weights embeddings & retrieval model from KiteFishAI, released Jul 2026.
What are the best alternatives to Nano Em1 0.6B v2?›
EmbeddingGemma 300M (better), F2LLM 4B (open weights).