MA
Meta AI
Language model · United States ·Jul 2022

ESM2-650M

Language Open (Restricted)
650M
Parameters

About ESM2-650M

ESM2-650M is an AI model developed by Meta AI, in the language category, released in 2022, made available as an open-weights model with 0.7B params.

On this page you'll find ESM2-650M's full specifications. Review provider pricing and benchmark scores below, or compare ESM2-650M head-to-head with other language models.

→ More models by Meta AI → All language models → AI benchmarks leaderboard

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Run ESM2-650M locally — what to buy

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Sized to what ESM2-650M 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
120+ tok/s
33 options →
Apple
120+ tok/s
18 options →
Datacenter GPU
120+ tok/s
13 options →

Community

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Frequently asked questions

What is ESM2-650M? ▶

ESM2-650M is an AI model developed by Meta AI, in the language category, released in 2022. It is tracked on GenAIList with its specifications, benchmark scores and provider pricing.

Who created ESM2-650M? ▶

ESM2-650M was developed by Meta AI and released in 2022.

Is ESM2-650M open source or proprietary? ▶

ESM2-650M 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 ESM2-650M cost? ▶

Pricing for ESM2-650M depends on the provider. See the providers table on this page for the latest API rates.

How does ESM2-650M perform on benchmarks? ▶

Benchmark scores for ESM2-650M 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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