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Grover-Mega
About Grover-Mega
Grover-Mega is an AI model developed by University of Washington, in the language category, released in 2019, made available as an open-weights model with 1.5B params.
On this page you'll find Grover-Mega's full specifications. Review provider pricing and benchmark scores below, or compare Grover-Mega head-to-head with other language models.
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Run Grover-Mega locally — what to buy
Share this build ↗Sized to what Grover-Mega 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 Grover-Mega? ▶
Grover-Mega is an AI model developed by University of Washington, in the language category, released in 2019. It is tracked on GenAIList with its specifications, benchmark scores and provider pricing.
Who created Grover-Mega? ▶
Grover-Mega was developed by University of Washington and released in 2019.
Is Grover-Mega open source or proprietary? ▶
Grover-Mega 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 Grover-Mega cost? ▶
Pricing for Grover-Mega depends on the provider. See the providers table on this page for the latest API rates.
How does Grover-Mega perform on benchmarks? ▶
Benchmark scores for Grover-Mega 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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