Understand and compare
Claude Instant 1.2
vs.
Mistral Large
Overview
Claude Instant 1.2 was released
7 months before
Mistral Large.
Claude Instant 1.2
|
Mistral Large
|
|
|---|---|---|
|
Provider
The entity that provides this model.
|
Anthropic
|
Mistral
|
|
Input Context Window
The number of tokens supported by the input context window.
|
100K
tokens
|
32K
tokens
|
|
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
|
Not specified.
|
4,096
tokens
|
|
Release Date
When the model was first released.
|
2023-08-09
|
2024-02-26
|
Pricing
Claude Instant 1.2 is
roughly 10.0x cheaper compared
to Mistral Large for input tokens and
roughly 3.3x cheaper
for output tokens.
|
Claude Instant 1.2
|
Mistral Large
|
|
|---|---|---|
|
Input
Cost of input data provided to the model.
|
$0.80
per million tokens
|
$8.00
per million tokens
|
|
Output
Cost of output tokens generated by the model.
|
$2.40
per million tokens
|
$8.00
per million tokens
|
Benchmarks
Compare relevant benchmarks between Claude Instant 1.2
and Mistral Large.
|
Claude Instant 1.2
|
Mistral Large
|
|
|---|---|---|
|
MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
73.4
(5-shot)
|
81.2
(5-shot)
|
|
MMMU
A wide ranging multi-discipline and multimodal benchmark.
|
Benchmark not available.
|
Benchmark not available.
|
|
HellaSwag
A challenging sentence completion benchmark.
|
Benchmark not available.
|
89.2
(10-shot)
|
Claude Instant 1.2, created by Anthropic, features a context window of 100,000 tokens. The model is priced at 0.8 cents per thousand tokens for input and 2.4 cents per thousand tokens for output. It was launched on August 9, 2023, and has shown strong performance in the MMLU benchmark with a score of 73.4 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).
GPT-4 0613
Llama 3.1 405B Instruct
Measure & Improve LLM
Product Performance.
Get Started
© 2023-2024 Context