Microsoft
Microsoft
Multimodal model · United States ·Aug 2022

BEIT-3

Multimodal Open (Restricted)
1.9B
Parameters

About BEIT-3

BEIT-3 is an AI model developed by Microsoft, in the multimodal category, released in 2022, made available as an open-weights model with 1.9B params.

On this page you'll find BEIT-3's full specifications. Review provider pricing and benchmark scores below, or compare BEIT-3 head-to-head with other multimodal models.

→ More models by Microsoft → All multimodal models → AI benchmarks leaderboard

Links

Announcement ↗

Run BEIT-3 locally — what to buy

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Sized to what BEIT-3 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.

Best
Intel Arc B580 12GB
Consumer GPU · ~$249
~120 tok/s
Q4 · fits full context · up to 8k ctx
Runs with: ExLlamaV2, KoboldCpp, LM Studio
See full estimate →

Software support

·ExLlamaV2 ·KoboldCpp ·LM Studio ·MLX ·Ollama ·SGLang ·TensorRT-LLM ·llama.cpp ·vLLM ?KTransformers ?text-generation-webui

✓ measured · · compatible · — not supported. Informational only — speed is hardware-based.

Consumer GPU
91.6–120+ tok/s
33 options →
Apple
91.6–120+ tok/s
18 options →
Datacenter GPU
120+ tok/s
13 options →

Community

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Frequently asked questions

What is BEIT-3? ▶

BEIT-3 is an AI model developed by Microsoft, in the multimodal category, released in 2022. It is tracked on GenAIList with its specifications, benchmark scores and provider pricing.

Who created BEIT-3? ▶

BEIT-3 was developed by Microsoft and released in 2022.

Is BEIT-3 open source or proprietary? ▶

BEIT-3 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 BEIT-3 cost? ▶

Pricing for BEIT-3 depends on the provider. See the providers table on this page for the latest API rates.

How does BEIT-3 perform on benchmarks? ▶

Benchmark scores for BEIT-3 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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