Compare Gemini Ultra vs. Mistral Large

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Overview

	Gemini Ultra	Mistral Large
Provider The entity that provides this model.	Google	Mistral
Input Context Window The number of tokens supported by the input context window.	32.8K characters	32K tokens
Maximum Output Tokens The number of tokens that can be generated by the model in a single request.	8,192 characters	4,096 tokens
Release Date When the model was first released.	Unknown	February 26th, 2024 10 months ago 2024-02-26
Knowledge Cutoff Limit on the knowledge base used by the model.	Unknown	Unknown
Open Source	No	Yes
API Providers The providers that offer this model. (This is not an exhaustive list.)	Google Cloud Vertex AI Model Garden	Azure AI, AWS Bedrock, Google Cloud Vertex AI Model Garden, Snowflake Cortex

Pricing

	Gemini Ultra	Mistral Large
Input Cost of input data provided to the model.	Pricing not available.	$8.00 per million tokens
Output Cost of output tokens generated by the model.	Pricing not available.	$8.00 per million tokens

Benchmarks

Compare relevant benchmarks between Gemini Ultra and Mistral Large.

	Gemini Ultra	Mistral Large
MMLU Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.	83.7 (5-shot) Source	81.2 (5-shot) Source
MMMU A wide ranging multi-discipline and multimodal benchmark.	59.4 (0-shot pass@1) Source	Benchmark not available.
HellaSwag A challenging sentence completion benchmark.	Benchmark not available.	89.2 (10-shot) Source
GSM8K Grade-school math problems benchmark.	88.9 (11-shot) Source	Benchmark not available.
HumanEval A benchmark to measure functional correctness for synthesizing programs from docstrings.	74.4 (0-shot) Source	Benchmark not available.
MATH Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.	53.2 (4-shot Minerva Prompt) Source	Benchmark not available.

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.

Mistral Large, developed by Mistral, features a context window of 32000 tokens. The model is priced at 0.8 cents per thousand tokens for both input and output. It was released on February 26, 2024, and has achieved impressive scores in benchmarks like MMLU (81.2 in a 5-shot scenario) and HellaSwag (89.2 in a 10-shot scenario).

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