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Hybrid H3-2.7B
About Hybrid H3-2.7B
Hybrid H3-2.7B is an AI model developed by Stanford University, in the language category, released in 2022, made available as an open-weights model with 2.7B params.
On this page you'll find Hybrid H3-2.7B's full specifications. Review provider pricing and benchmark scores below, or compare Hybrid H3-2.7B head-to-head with other language models.
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Run Hybrid H3-2.7B locally — what to buy
Share this build ↗Sized to what Hybrid H3-2.7B 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 Hybrid H3-2.7B? ▶
Hybrid H3-2.7B is an AI model developed by Stanford University, in the language category, released in 2022. It is tracked on GenAIList with its specifications, benchmark scores and provider pricing.
Who created Hybrid H3-2.7B? ▶
Hybrid H3-2.7B was developed by Stanford University and released in 2022.
Is Hybrid H3-2.7B open source or proprietary? ▶
Hybrid H3-2.7B 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 Hybrid H3-2.7B cost? ▶
Pricing for Hybrid H3-2.7B depends on the provider. See the providers table on this page for the latest API rates.
How does Hybrid H3-2.7B perform on benchmarks? ▶
Benchmark scores for Hybrid H3-2.7B 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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