Static Retrieval Mrl En v1 measured on 16 of 261 Embeddings benchmarks16
BenchmarkByScoreRank
No benchmark matches
self-host onlyprice
35MTEB English v2
Oct 2024released
enLanguages
Rankingconfiguration unstated?
Full ranking →···
167Potion Retrieval 32M35.1168Static Retrieval Mrl En v135169LaBSE Ru Turbo34.2Strong at
Alternatives?
ModelScoreCostPriceWhat changes
BetterEmbeddingGemma 300MunstatedOpen+59%—$0.002Languages: not verified+1IOpenYuan Embedding 2.0 Enunstated×2——Memory (4-bit): 0 GB → 0.4 GB
BetterBge Base En v1.5unstatedOpen+57%—$0.005Memory (4-bit): 0 GB → 0.1 GBtBetterGte BaseunstatedOpen+48%—$0.005Memory (4-bit): 0 GB → 0.1 GBiBetterE5 Base v2unstatedOpen+42%—$0.005Memory (4-bit): 0 GB → 0.1 GBModelScoreCostPriceWhat changes
Nothing here yet.
ModelScoreCostPriceWhat changes
EmbeddingGemma 300MunstatedOpen+59%—$0.002Languages: not verified+1Bge Base En v1.5unstatedOpen+57%—$0.005Memory (4-bit): 0 GB → 0.1 GBtGte BaseunstatedOpen+48%—$0.005Memory (4-bit): 0 GB → 0.1 GBiE5 Base v2unstatedOpen+42%—$0.005Memory (4-bit): 0 GB → 0.1 GBsAll Mpnet Base v2unstatedOpen+27%—$0.005Memory (4-bit): 0 GB → 0.1 GBModelScoreCostPriceWhat changes
IYuan Embedding 2.0 EnunstatedOpen×2——Memory (4-bit): 0 GB → 0.4 GB
Qwen 3 Embedding 8BunstatedOpen+99%—$0.01Languages: not verified+1Qwen 3 Embedding 4BunstatedOpen+96%—$0.02Languages: not verified+1KQZhou EmbeddingunstatedOpen+92%——Memory (4-bit): 0 GB → 4.2 GBiJasper Token Compression 600MunstatedOpen+89%——Memory (4-bit): 0 GB → 0.4 GBModelScoreCostPriceWhat changes
sAll Mpnet Base v2unstatedOpen+27%—$0.005Memory (4-bit): 0 GB → 0.1 GBsAll MiniLM L12 v2unstatedOpen+25%—$0.005sAll MiniLM L6 v2unstatedOpen+23%—$0.005sParaphrase Multilingual Mpnet Base v2unstatedOpen+6%——Memory (4-bit): 0 GB → 0.2 GBsParaphrase Multilingual MiniLM L12 v2unstatedOpensame——Memory (4-bit): 0 GB → 0.1 GBsStatic Similarity Mrl Multilingual v1unstatedOpen-18%——Memory (4-bit): 0 GB → 0.1 GBsLaBSEunstatedOpen-48%——Memory (4-bit): 0 GB → 0.3 GBsSentence T5 XlunstatedOpenn/a——Memory (4-bit): 0 GB → 0.7 GBAll sentence-transformers 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
Benchmarks
in Embeddings & RetrievalBEIR · Mean over tasks · English34.1#159
BEIR · Retrieval · English34.1#159
FAQ
How much does Static Retrieval Mrl En v1 cost?›
There is no per-unit API price: self-host only.
Is Static Retrieval Mrl En v1 free to use?›
There is no free API. The weights are open, so you can run it yourself.
How good is Static Retrieval Mrl En v1, and what is it best at?›
#157 of 200 in Embeddings.
Is Static Retrieval Mrl En v1 better than Potion Retrieval 32M?›
On MTEB English v2 · Retrieval · English, Static Retrieval Mrl En v1 scores 35 vs 35.1 — about the same.
When was Static Retrieval Mrl En v1 released? Is there a newer version?›
Released 2024-10-24. It is the current version in its line.
Is Static Retrieval Mrl En v1 open source?›
Yes, the weights are open (Apache-2.0 licence).
Can I run Static Retrieval Mrl En v1 locally?›
The weights are open and can be self-hosted; hardware needs are not confirmed yet.
What is Static Retrieval Mrl En v1?›
Static Retrieval Mrl En v1 is an open-weights embeddings & retrieval model from sentence-transformers, released Oct 2024.
What are the best alternatives to Static Retrieval Mrl En v1?›
EmbeddingGemma 300M (better), Yuan Embedding 2.0 En (open weights).