Understand and compare
Gemini Ultra
vs.
Mistral 8x7B Instruct
Overview
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Provider
The entity that provides this model.
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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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32K
tokens
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Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
|
8,192
characters
|
4,096
tokens
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Release Date
When the model was first released.
|
Unknown
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2023-12-11
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Pricing
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Input
Cost of input data provided to the model.
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Pricing not available.
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$0.70
per million tokens
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Output
Cost of output tokens generated by the model.
|
Pricing not available.
|
$0.70
per million tokens
|
Benchmarks
Compare relevant benchmarks between Gemini Ultra
and Mistral 8x7B Instruct.
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MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
83.7
(5-shot)
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70.6
(5-shot)
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MMMU
A wide ranging multi-discipline and multimodal benchmark.
|
59.4
(0-shot pass@1)
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Benchmark not available.
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HellaSwag
A challenging sentence completion benchmark.
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Benchmark not available.
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Benchmark not available.
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![](https://with.context.ai/assets/google-c8f988d7a45b564da5965132d7479ae30327702e3e9fbc3df8f03c2842e0834e.png)
Mistral 8x7B Instruct, developed by Mistral, features a context window of 32000 tokens. The model costs 0.07 cents per thousand tokens for both input and output. It was released on December 11, 2023, and achieved a score of 70.6 in the MMLU benchmark in a 5-shot scenario.
![](https://with.context.ai/assets/mistral-9e9f2d79ccfc3f09ad90b1a79c4072f3ce8345e5582acb227da152e6db07b217.png)
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