LLM2Vec Sheared Llama Mntp Supervised measured on 6 of 261 Embeddings benchmarks6
BenchmarkByScoreRank
No benchmark matches
self-host onlyprice
86.2MTEB English v2
Apr 2024released
33K tokensMax input
enLanguages
Alternatives?
ModelScoreCostPriceWhat changes
iBetterE5 Mistral 7B InstructunstatedOpen+3%—$0.022Memory (4-bit): 0.8 GB → 4.3 GBKOpenQZhou Embeddingunstated+7%——Memory (4-bit): 0.8 GB → 4.2 GBVBetterVoyage Large 2 Instructunstated+6%—$0.12Max input: 33K tokens → 16K tokens+1jBetterIngot 8B R3unstated+9%——Languages: not verifiedTBetterConan Embedding v2unstated+8%——ModelScoreCostPriceWhat changes
Nothing here yet.
ModelScoreCostPriceWhat changes
iE5 Mistral 7B InstructunstatedOpen+3%—$0.022Memory (4-bit): 0.8 GB → 4.3 GBVVoyage Large 2 Instructunstated+6%—$0.12Max input: 33K tokens → 16K tokens+1jIngot 8B R3unstated+9%——Languages: not verifiedTConan Embedding v2unstated+8%——KQZhou EmbeddingunstatedOpen+7%——Memory (4-bit): 0.8 GB → 4.2 GBModelScoreCostPriceWhat changes
KQZhou EmbeddingunstatedOpen+7%——Memory (4-bit): 0.8 GB → 4.2 GBiJasper Token Compression 600MunstatedOpen+5%——KNano Em1 0.6B v2.1unstatedOpen+4%——Max input: 33K tokens → 8K tokens
NV Embed v2unstatedOpen+3%——Memory (4-bit): 0.8 GB → 4.7 GBaLGAI Embedding PreviewunstatedOpen+3%——Memory (4-bit): 0.8 GB → 4.3 GBModelScoreCostPriceWhat changes
MLLM2Vec Llama 2 7B Chat Hf Mntp SupervisedunstatedOpen+2%——Memory (4-bit): 0.8 GB → 4 GBMLLM2Vec Mistral 7B Instruct v2 Mntp SupervisedunstatedOpen+2%——Memory (4-bit): 0.8 GB → 4.3 GBMLLM2Vec Meta Llama 3 8B Instruct Mntp SupervisedunstatedOpen+2%——Max input: 33K tokens → 8K tokens+1MLLM2Vec Mistral 7B Instruct v2 Mntp Unsup SimcseunstatedOpen-6%——Memory (4-bit): 0.8 GB → 4.3 GBMLLM2Vec Meta Llama 3 8B Instruct Mntp Unsup SimcseunstatedOpen-9%——Max input: 33K tokens → 8K tokens+1MLLM2Vec Llama 2 7B Chat Hf Mntp Unsup SimcseunstatedOpen-10%——Memory (4-bit): 0.8 GB → 4 GBMLLM2Vec Sheared Llama Mntp Unsup SimcseunstatedOpen-16%——All McGill-NLP 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
LicenceMITfree for commercial use
Benchmarks
in Embeddings & RetrievalBEIR · Retrieval · English51.4#86
FAQ
How much does LLM2Vec Sheared Llama Mntp Supervised cost?›
There is no per-unit API price: self-host only.
Is LLM2Vec Sheared Llama Mntp Supervised free to use?›
There is no free API. The weights are open, so you can run it yourself.
How good is LLM2Vec Sheared Llama Mntp Supervised, and what is it best at?›
#50 of 238 in Embeddings.
Is LLM2Vec Sheared Llama Mntp Supervised better than Multilingual E5 Large Instruct?›
On MTEB English v2 · Pair Classification · English, LLM2Vec Sheared Llama Mntp Supervised scores 86.2 vs 86.2 — about the same.
When was LLM2Vec Sheared Llama Mntp Supervised released? Is there a newer version?›
Released 2024-04-09. It is the current version in its line.
Is LLM2Vec Sheared Llama Mntp Supervised open source?›
Yes, the weights are open (MIT licence).
Can I run LLM2Vec Sheared Llama Mntp Supervised locally?›
The weights are open and can be self-hosted; hardware needs are not confirmed yet.
What is LLM2Vec Sheared Llama Mntp Supervised?›
LLM2Vec Sheared Llama Mntp Supervised is an open-weights embeddings & retrieval model from McGill-NLP, released Apr 2024.
What are the best alternatives to LLM2Vec Sheared Llama Mntp Supervised?›
E5 Mistral 7B Instruct (better), QZhou Embedding (open weights).