Gemini Flash

Our lightweight model, optimized for speed and efficiency

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Lightweight, fast and cost-efficient while featuring multimodal reasoning and a breakthrough long context window of up to one million tokens.

Built for speed

Sub-second average first-token latency for the vast majority of developer and enterprise use cases.

Quality at lower cost

On most common tasks, 1.5 Flash achieves comparable quality to larger models, at a fraction of the cost.

Long-context understanding

Process hours of video and audio, and hundreds of thousands of words or lines of code.

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Capability	Benchmark	Description	Gemini 1.0 Pro	Gemini 1.0 Ultra	Gemini 1.5 Pro (Feb 2024)	Gemini 1.5 Flash	Gemini 1.5 Pro (May 2024)
General MMLU Representation of questions in 57 subjects (incl. STEM, humanities, and others)
General	MMLU	Representation of questions in 57 subjects (incl. STEM, humanities, and others)	Gemini 1.0 Pro 71.8%	Gemini 1.0 Ultra 83.7%	Gemini 1.5 Pro (Feb 2024) 81.9%	Gemini 1.5 Flash 78.9%	Gemini 1.5 Pro (May 2024) 85.9%
Code Natural2Code Python code generation. Held out dataset HumanEval-like, not leaked on the web
Code	Natural2Code	Python code generation. Held out dataset HumanEval-like, not leaked on the web	Gemini 1.0 Pro 69.6%	Gemini 1.0 Ultra 74.9%	Gemini 1.5 Pro (Feb 2024) 77.7%	Gemini 1.5 Flash 77.2%	Gemini 1.5 Pro (May 2024) 82.6%
Math MATH Challenging math problems (incl. algebra, geometry, pre-calculus, and others)
Math	MATH	Challenging math problems (incl. algebra, geometry, pre-calculus, and others)	Gemini 1.0 Pro 32.6%	Gemini 1.0 Ultra 53.2%	Gemini 1.5 Pro (Feb 2024) 58.5%	Gemini 1.5 Flash 54.9%	Gemini 1.5 Pro (May 2024) 67.7%
Reasoning GPQA (main) Challenging dataset of questions written by domain experts in biology, physics, and chemistry
Reasoning	GPQA (main)	Challenging dataset of questions written by domain experts in biology, physics, and chemistry	Gemini 1.0 Pro 27.9%	Gemini 1.0 Ultra 35.7%	Gemini 1.5 Pro (Feb 2024) 41.5%	Gemini 1.5 Flash 39.5%	Gemini 1.5 Pro (May 2024) 46.2%
Reasoning Big-Bench Hard Diverse set of challenging tasks requiring multi-step reasoning
	Big-Bench Hard	Diverse set of challenging tasks requiring multi-step reasoning	Gemini 1.0 Pro 75.0%	Gemini 1.0 Ultra 83.6%	Gemini 1.5 Pro (Feb 2024) 84.0%	Gemini 1.5 Flash 85.5%	Gemini 1.5 Pro (May 2024) 89.2%
Multilingual WMT23 Language translation
Multilingual	WMT23	Language translation	Gemini 1.0 Pro 71.7	Gemini 1.0 Ultra 74.4	Gemini 1.5 Pro (Feb 2024) 75.2	Gemini 1.5 Flash 74.1	Gemini 1.5 Pro (May 2024) 75.3
Image MMMU Multi-discipline college-level reasoning problems
Image	MMMU	Multi-discipline college-level reasoning problems	Gemini 1.0 Pro 47.9%	Gemini 1.0 Ultra 59.4%	Gemini 1.5 Pro (Feb 2024) 58.5%	Gemini 1.5 Flash 56.1%	Gemini 1.5 Pro (May 2024) 62.2%
Image MathVista Multi-discipline college-level reasoning problems
	MathVista	Mathematical reasoning in visual contexts	Gemini 1.0 Pro 46.6%	Gemini 1.0 Ultra 53.0%	Gemini 1.5 Pro (Feb 2024) 54.7%	Gemini 1.5 Flash 58.4%	Gemini 1.5 Pro (May 2024) 63.9%
Audio FLEURS (55 languages) Automatic speech recognition (based on word error rate, lower is better)
Audio	FLEURS (55 languages)	Automatic speech recognition (based on word error rate, lower is better)	Gemini 1.0 Pro 6.4%	Gemini 1.0 Ultra 6.0%	Gemini 1.5 Pro (Feb 2024) 6.6%	Gemini 1.5 Flash 9.8%	Gemini 1.5 Pro (May 2024) 6.5%
Video EgoSchema Video question answering
Video	EgoSchema	Video question answering	Gemini 1.0 Pro 55.7%	Gemini 1.0 Ultra 61.5%	Gemini 1.5 Pro (Feb 2024) 65.1%	Gemini 1.5 Flash 65.7%	Gemini 1.5 Pro (May 2024) 72.2%

May 2024

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

December 2023

Gemini 1.0: A family of highly capable multimodal models

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