Gemini 2.0 Flash

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Gemini 2.0 Flash is Google's high-performance, low-latency model designed to drive advanced agentic experiences. Equipped with native tool integration, it supports multimodal inputs, including text, images, video, and audio. Offering substantial improvements over previous versions, the model balances efficiency, speed, and enhanced capabilities for seamless real-time interactions.

4052
628

Position in the overall ranking as of
June 2026
23
User rating
https://compare-ai.foundtt.com
4

Model Overview

Web Site
AI Model Web Page
Provider
The entity that provides this model.
Chat
Input a message to start chatting
-
Release Date
When the model was first released.
1 year ago
Dec 11, 2024
Modalities
Types of data this model can process
text ?
images ?
voice ?
video ?
API Providers
The providers that offer this model. (This is not an exhaustive list.)
Google AI Studio, Vertex AI
Knowledge Cut-off Date
When the model's knowledge was last updated.
08.2024
Open Source
Whether the model's code is available for public use.
No
Pricing Input
Cost for processing tokens in your prompts
$0.10 per million tokens
Pricing Output
Cost for tokens generated by the model
$0.40 per million tokens
MMLU
Massive Multitask Language Understanding - Tests knowledge across 57 subjects including mathematics, history, law, and more
Not available
MMLU-Pro
A more robust MMLU benchmark with harder, reasoning-focused questions, a larger choice set, and reduced prompt sensitivity
77.6%
Source
MMMU
Massive Multitask Multimodal Understanding - Tests understanding across text, images, audio, and video
71.7%
Source
HellaSwag
A challenging sentence completion benchmark
Not available
HumanEval
Evaluates code generation and problem-solving capabilities
Not available
MATH
Tests mathematical problem-solving abilities across various difficulty levels
90.9%
Source
GPQA
Tests PhD-level knowledge in chemistry, biology, and physics through multiple choice questions that require deep domain expertise
60.1%
Diamond
Source
IFEval
Tests model's ability to accurately follow explicit formatting instructions, generate appropriate outputs, and maintain consistent instruction adherence across different tasks
Not available
SimpleQA
Assessing the accuracy of simple questions
-
AIME 2024
-
AIME 2025
-
Aider Polyglot
Multilingual programming benchmark.
-
LiveCodeBench v5
Benchmark for real-time programming
-
Global MMLU (Lite)
A simplified version of the benchmark for assessing the universality of models at the global level.
-
MathVista
Evaluates the mathematical reasoning abilities of AI models within visual contexts
-
Mobile Application

VideoGameBench ?

Total score0%
Doom II0%
Dream DX0%
Awakening DX0%
Civilization I0%
Pokemon Crystal0%
The Need for Speed0%
The Incredible Machine0%
Secret Game 10%
Secret Game 20%
Secret Game 30%

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