Gemini 2.0 Flash - In-Depth Overview

Google · Gemini

Current

Model ID: google-gemini-2.0-flash

Get all the details on Gemini 2.0 Flash, an AI model from Google. This page covers its token limits, pricing structure, key capabilities such as multimodal_input, long_context, vision, available API code samples, and performance strengths.

Key Metrics

Input Limit

1M tokens

Output Limit

No data tokens

Input Cost

$0.10/1M

Output Cost

$0.40/1M

Sample API Code

from google import genai

client = genai.Client(api_key="YOUR_API_KEY")

response = client.models.generate_content(
    model="gemini-2.0-flash", contents="Explain how AI works in a few words"
)
print(response.text)

Required Libraries

google-genai

@google/generative-ai

Benchmarks

Benchmark	Score	Source	Notes
lmarena text	1355	lmarena.ai	Rank 8 (as gemini-2.0-flash-001)
lmarena webdev	1039	lmarena.ai	Rank 17 (as Gemini-2.0-Flash-001)
lmarena vision	1224	lmarena.ai	Rank 8 (as gemini-2.0-flash-001)
lmarena search	1028	lmarena.ai	Rank 7 (as gemini-2.0-flash-grounding)
livebench global average	60.05	livebench.ai	-
livebench reasoning average	44.25	livebench.ai	-
livebench coding average	64.74	livebench.ai	-
livebench mathematics average	63.19	livebench.ai	-
livebench data analysis average	59.92	livebench.ai	-
livebench language average	42.39	livebench.ai	-
livebench if average	85.79	livebench.ai	-
grind	53.6	Vellum	-
gpqa	62.1	Vellum	-
swe bench	51.8	Vellum	-
math 500	89.7	Vellum	-
bfcl	60.42	Vellum	-
alder polyglot	22.2	Vellum	-

Notes

Our most balanced multimodal model with great performance across all tasks, with a 1 million token context window, and built for the era of Agents. Pricing varies by input type (text/image/video vs audio) and tier (Free vs Paid). Vertex AI pricing may differ.