FU
Fudan University
Language model · China ·Sep 2024

ProtRNA

Language Open (Restricted)
650M
Parameters

About ProtRNA

ProtRNA is an AI model developed by Fudan University, in the language category, released in 2024, made available as an open-weights model with 0.7B params.

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

→ More models by Fudan University → All language models → AI benchmarks leaderboard

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Run ProtRNA locally — what to buy

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Sized to what ProtRNA 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 ProtRNA? ▶

ProtRNA is an AI model developed by Fudan University, in the language category, released in 2024. It is tracked on GenAIList with its specifications, benchmark scores and provider pricing.

Who created ProtRNA? ▶

ProtRNA was developed by Fudan University and released in 2024.

Is ProtRNA open source or proprietary? ▶

ProtRNA 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 ProtRNA cost? ▶

Pricing for ProtRNA depends on the provider. See the providers table on this page for the latest API rates.

How does ProtRNA perform on benchmarks? ▶

Benchmark scores for ProtRNA 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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