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 →···
181E5 Omni 7B72.1182Static Retrieval Mrl En v172.1183USER Base71.9Strong at
Alternatives?
ModelScoreCostPriceWhat changes
BetterEmbeddingGemma 300MunstatedOpen+16%—$0.002Languages: not verified+1KOpenQZhou Embeddingunstated+27%——Memory (4-bit): 0 GB → 4.2 GBtBetterGte BaseunstatedOpen+14%—$0.005Memory (4-bit): 0 GB → 0.1 GB
BetterBge Base En v1.5unstatedOpen+14%—$0.005Memory (4-bit): 0 GB → 0.1 GBiBetterE5 Base v2unstatedOpen+12%—$0.005Memory (4-bit): 0 GB → 0.1 GBModelScoreCostPriceWhat changes
Nothing here yet.
ModelScoreCostPriceWhat changes
EmbeddingGemma 300MunstatedOpen+16%—$0.002Languages: not verified+1tGte BaseunstatedOpen+14%—$0.005Memory (4-bit): 0 GB → 0.1 GBBge Base En v1.5unstatedOpen+14%—$0.005Memory (4-bit): 0 GB → 0.1 GBiE5 Base v2unstatedOpen+12%—$0.005Memory (4-bit): 0 GB → 0.1 GBsAll Mpnet Base v2unstatedOpen+11%—$0.005Memory (4-bit): 0 GB → 0.1 GBModelScoreCostPriceWhat changes
KQZhou EmbeddingunstatedOpen+27%——Memory (4-bit): 0 GB → 4.2 GBiJasper Token Compression 600MunstatedOpen+23%——Memory (4-bit): 0 GB → 0.4 GB
Qwen 3 Embedding 4BunstatedOpen+23%—$0.02Languages: not verified+1Qwen 3 Embedding 8BunstatedOpen+23%—$0.01Languages: not verified+1
Jina Embeddings v5 Text NanounstatedOpen+22%—$0.02Languages: not verified+1ModelScoreCostPriceWhat changes
sParaphrase Multilingual Mpnet Base v2unstatedOpen+12%——Memory (4-bit): 0 GB → 0.2 GBsAll Mpnet Base v2unstatedOpen+11%—$0.005Memory (4-bit): 0 GB → 0.1 GBsAll MiniLM L12 v2unstatedOpen+11%—$0.005sAll MiniLM L6 v2unstatedOpen+9%—$0.005sParaphrase Multilingual MiniLM L12 v2unstatedOpen+9%——Memory (4-bit): 0 GB → 0.1 GBsStatic Similarity Mrl Multilingual v1unstatedOpen+3%——Memory (4-bit): 0 GB → 0.1 GBsLaBSEunstatedOpen-2%——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 E5 Omni 7B?›
On MTEB English v2 · STS · English, Static Retrieval Mrl En v1 scores 72.1 vs 72.1 — 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), QZhou Embedding (open weights).