Gemini Ultra, developed by Google, features a large context window of 32768 tokens. The model has excelled in benchmarks like MMMU with a score of 59.4 in a 0-shot pass@1 scenario and MMLU with a score of 83.7 in a 5-shot scenario.
Overview
Gemini Ultra
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Provider
The entity that provides this model.
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Google
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Input Context Window
The number of tokens supported by the input context window.
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32.8K
characters
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Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
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8,192
characters
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Open Source
Whether the model's code is available for public use.
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No
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Release Date
When the model was first released.
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Unknown
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Knowledge Cut-off Date
When the model's knowledge was last updated.
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Unknown
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API Providers
The providers that offer this model. (This is not an exhaustive list.)
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Empirical Throughput
The number of tokens the model can generate per second.
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Pricing
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Gemini Ultra
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Input
Cost of input data provided to the model.
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Pricing not available.
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Output
Cost of output tokens generated by the model.
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Pricing not available.
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Benchmarks
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Gemini Ultra
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MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
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83.7
(5-shot)
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MMMU
A wide ranging multi-discipline and multimodal benchmark.
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59.4
(0-shot pass@1)
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HellaSwag
A challenging sentence completion benchmark.
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Benchmark not available.
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HumanEval
A benchmark to measure functional correctness for synthesizing programs from docstrings.
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74.4
(0-shot)
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MATH
Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.
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53.2
(4-shot Minerva Prompt)
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