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Activeloop Deep Lake

by Activeloop Inc.

System Card

OrganizationActiveloop Inc.
Released2021-02
Architecturevector-rag / multimodal AI data lakehouse
DetailsDeep Lake (by Activeloop) is an AI data runtime providing serverless multimodal data storage (tensors for text, images, audio, video, embeddings) alongside vector search. It is built on the Lance-compatible open format and integrates with PyTorch and TensorFlow for training data streaming as well as RAG retrieval. Supports both local and cloud-hosted deployments.
Parameters—
Domainrag-retrievallong-context
Open SourceYes
WebsiteVisit
multimodaldata-laketraining-datavector-searchPyTorch

Capability Profile

Benchmark Scores

6 of 14 benchmarks
Data Transparency:6 estimated
Long-Context Retrieval
4/5
RULER
70.746pEstimated
NIAH
no data
LooGLE
61.35pEstimated
LongBench
603pEstimated
∞Bench
69.33pEstimated
Multi-Turn Recall
0/2
LoCoMo
no data
MemoryBank
no data
Cross-Session Memory
0/1
LongMemEval
no data
Multi-Hop QA
2/3
BABILong
62.66pEstimated
MultiHop-RAG
no data
HotpotQA
60.614pEstimated
Agent Task Memory
0/1
AgentBench-Mem
no data
Personalization
0/1
PerLTQA
no data
Factuality / Grounding
0/1
RAGAS
no data
Sources:Arena estimate — derived from capability profile, not independently verified