Understand and compare
Mistral Large
vs.
GPT-3.5 Turbo 16K
Overview
Mistral Large was released
9 months after
GPT-3.5 Turbo 16K.
Mistral Large
|
GPT-3.5 Turbo 16K
|
|
|---|---|---|
|
Provider
The entity that provides this model.
|
Mistral
|
OpenAI
|
|
Input Context Window
The number of tokens supported by the input context window.
|
32K
tokens
|
16.4K
tokens
|
|
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
|
4,096
tokens
|
16.4K
tokens
|
|
Release Date
When the model was first released.
|
2024-02-26
|
2023-06-13
|
Pricing
Mistral Large is
roughly 2.7x more expensive compared
to GPT-3.5 Turbo 16K for input tokens and
roughly 2.0x more expensive
for output tokens.
|
Mistral Large
|
GPT-3.5 Turbo 16K
|
|
|---|---|---|
|
Input
Cost of input data provided to the model.
|
$8.00
per million tokens
|
$3.00
per million tokens
|
|
Output
Cost of output tokens generated by the model.
|
$8.00
per million tokens
|
$4.00
per million tokens
|
Benchmarks
Compare relevant benchmarks between Mistral Large
and GPT-3.5 Turbo 16K.
|
Mistral Large
|
GPT-3.5 Turbo 16K
|
|
|---|---|---|
|
MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
81.2
(5-shot)
|
Benchmark not available.
|
|
MMMU
A wide ranging multi-discipline and multimodal benchmark.
|
Benchmark not available.
|
Benchmark not available.
|
|
HellaSwag
A challenging sentence completion benchmark.
|
89.2
(10-shot)
|
Benchmark not available.
|
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-3.5 Turbo 16K, developed by OpenAI, features a context window of 16384 tokens. The model costs 0.3 cents per thousand tokens for input and 0.4 cents per thousand tokens for output. It was released on June 13, 2023.
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