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BGE-M3 Embedding
About BGE-M3 Embedding
BGE-M3 Embedding is an AI model developed by Beijing Academy of Artificial Intelligence / BAAI, in the language category, released in 2024, made available as an open-weights model with 0.3B params.
On this page you'll find BGE-M3 Embedding's full specifications. Review provider pricing and benchmark scores below, or compare BGE-M3 Embedding head-to-head with other language models.
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Run BGE-M3 Embedding locally — what to buy
Share this build ↗Sized to what BGE-M3 Embedding actually needs (~8k context at Q4), not to the biggest GPU: Good = cheapest that runs it, Better = best value, Best = most headroom. Speed is a hardware estimate; anything past ~120 tok/s is shown as instant.
Software support
✓ measured · · compatible · — not supported. Informational only — speed is hardware-based.
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Frequently asked questions
What is BGE-M3 Embedding? ▶
BGE-M3 Embedding is an AI model developed by Beijing Academy of Artificial Intelligence / BAAI, in the language category, released in 2024. It is tracked on GenAIList with its specifications, benchmark scores and provider pricing.
Who created BGE-M3 Embedding? ▶
BGE-M3 Embedding was developed by Beijing Academy of Artificial Intelligence / BAAI and released in 2024.
Is BGE-M3 Embedding open source or proprietary? ▶
BGE-M3 Embedding ships as an open-weights model: you can download and self-host the weights, though the licence may place some restrictions on use.
How much does BGE-M3 Embedding cost? ▶
Pricing for BGE-M3 Embedding depends on the provider. See the providers table on this page for the latest API rates.
How does BGE-M3 Embedding perform on benchmarks? ▶
Benchmark scores for BGE-M3 Embedding are listed on this page as they are published. You can compare it head-to-head with other models on the GenAIList compare tool.
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