Intfloat/OtherActive

E5-Base-v2

Text Embeddings by Weakly-Supervised Contrastive Pre-training. Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, Furu Wei, arXiv 2022

Compare this modelView primary source
Context
512
Max output
Unknown
Input
$0.005
Output
$0.00
DECISION SUMMARY

Recommended use cases

MultimodalValue

Strengths in this dataset

  • 512-token context window
  • text input
  • 11 supported API parameters listed

Limits and caveats

  • Provider behavior and pricing can change; verify the linked sources before production use.
CAPABILITIES

Capability

Model-native facts

Model
Reasoning
Unknown
Open weights
Unknown

Provider endpoint facts

Provider endpoint
Tool calling
Not supported
Structured output
Supported
Streaming
Unknown
Prompt cache
Unknown
Batch
Unknown
Fine-tuning
Unknown
PROVIDER PRICING

E5-Base-v2 Provider pricing

Provider endpoint: intfloat/e5-base-v2

Input
$0.005
per 1M tokens
Output
$0.00
per 1M tokens
Cached input
Unknown
per 1M tokens
Image output
Unknown
per 1M tokens
SOURCE RECORDS

Sources and verification

Hugging Face model card

Fields: tags, gated, license, summary, languages, library name, pipeline tag

OpenRouter Models API

Fields: identity, description, modalities, context window, maximum output, pricing, supported parameters

MODEL FAQ

Frequently asked questions

Answers are generated from the same sourced model and provider facts shown above.

Text Embeddings by Weakly-Supervised Contrastive Pre-training. Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, Furu Wei, arXiv 2022

Model specifications and prices may vary by provider and change over time. AIToolly displays sources and verification dates so users can confirm critical details before production use.