Understand and compare
Gemini 1.5 Pro
vs.
Claude 3 Sonnet
Overview
Gemini 1.5 Pro was released
18 days before
Claude 3 Sonnet.
Gemini 1.5 Pro
|
Claude 3 Sonnet
|
|
---|---|---|
Provider
The entity that provides this model.
|
Google
|
Anthropic
|
Input Context Window
The number of tokens supported by the input context window.
|
1M
tokens
|
200K
tokens
|
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
|
8,192
tokens
|
4,096
tokens
|
Release Date
When the model was first released.
|
2024-02-15
|
2024-03-04
|
Pricing
Gemini 1.5 Pro is
roughly 2.3x more expensive compared
to Claude 3 Sonnet for input tokens and
roughly 40.0% more expensive
for output tokens.
Gemini 1.5 Pro
|
Claude 3 Sonnet
|
|
---|---|---|
Input
Cost of input data provided to the model.
|
$7.00
per million tokens
|
$3.00
per million tokens
|
Output
Cost of output tokens generated by the model.
|
$21.00
per million tokens
|
$15.00
per million tokens
|
Benchmarks
Compare relevant benchmarks between Gemini 1.5 Pro
and Claude 3 Sonnet.
Gemini 1.5 Pro
|
Claude 3 Sonnet
|
|
---|---|---|
MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
81.9
(5-shot)
|
81.5
(5-shot CoT)
|
MMMU
A wide ranging multi-discipline and multimodal benchmark.
|
58.5
(0-shot)
|
53.1
|
HellaSwag
A challenging sentence completion benchmark.
|
Benchmark not available.
|
89.0
(10-shot)
|
Gemini 1.5 Pro by Google features a vast context window of 1,000,000 tokens. The model is priced at 0.7 cents per thousand tokens for input and 2.1 cents per thousand tokens for output. It was launched on February 15, 2024. In benchmark tests, it achieved a score of 58.5 in MMMU with a 0-shot scenario and 81.9 in MMLU with a 5-shot scenario.
Claude 3 Sonnet, developed by Anthropic, features a context window of 200,000 tokens. The model costs 0.3 cents per thousand tokens for input and 1.5 cents per thousand tokens for output. It was released on March 4, 2024, and has achieved benchmark scores of 53.1 in MMMU, 89.0 in HellaSwag (10-shot), and 81.5 in MMLU (5-shot CoT).
Measure & Improve LLM
Product Performance.
Get Started