Understand and compare
Mistral Large
vs.
Claude 3 Opus
Overview
Mistral Large was released
7 days before
Claude 3 Opus.
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|
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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.
|
32K
tokens
|
200K
tokens
|
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
|
4,096
tokens
|
4,096
tokens
|
Release Date
When the model was first released.
|
2024-02-26
|
2024-03-04
|
Pricing
Mistral Large is
roughly 46.7% cheaper compared
to Claude 3 Opus for input tokens and
roughly 9.4x cheaper
for output tokens.
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Input
Cost of input data provided to the model.
|
$8.00
per million tokens
|
$15.00
per million tokens
|
Output
Cost of output tokens generated by the model.
|
$8.00
per million tokens
|
$75.00
per million tokens
|
Benchmarks
Compare relevant benchmarks between Mistral Large
and Claude 3 Opus.
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|
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MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
81.2
(5-shot)
|
88.2
(5-shot CoT)
|
MMMU
A wide ranging multi-discipline and multimodal benchmark.
|
Benchmark not available.
|
59.4
|
HellaSwag
A challenging sentence completion benchmark.
|
89.2
(10-shot)
|
95.4
(10-shot)
|
![](https://with.context.ai/assets/mistral-9e9f2d79ccfc3f09ad90b1a79c4072f3ce8345e5582acb227da152e6db07b217.png)
Claude 3 Opus, developed by Anthropic, features a context window of 200,000 tokens. The model costs 1.5 cents per thousand tokens for input and 7.5 cents per thousand tokens for output. It was released on March 4, 2024, and has achieved impressive scores in benchmarks like HellaSwag with a score of 95.4 in a 10-shot scenario, MMLU with a score of 88.2 in a 5-shot CoT scenario, and MMMU with a score of 59.4.
![](https://with.context.ai/assets/anthropic-80870c3e4c4b59465f693246e7ac24d65d785686adf82cc682d05d7bcb81796d.png)
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