Google: Gemini 2.0 Flash

by Google

Gemini Flash 2.0 offers a significantly faster time to first token (TTFT) compared to [Gemini Flash 1.5](/google/gemini-flash-1.5), while maintaining quality on par with larger models like [Gemini Pro 1.5](/google/gemini-pro-1.5). It introduces notable enhancements in multimodal understanding, coding capabilities, complex instruction following, and function calling. These advancements come together to deliver more seamless and robust agentic experiences.

Avg Score

80.0%

271 answers

Avg Latency

2.2s

36 runs

Pricing

$0.10

input

$0.40

output

per 1M tokens

Context

1049K

tokens

Alternatives

Models with similar or better quality but different tradeoffs

Same Quality, Cheaper

Models with similar or better performance at a lower cost per token.

Model	Cost
DeepSeek: DeepSeek V3.2	-21%

Same Quality, Faster

Models with similar or better performance but lower latency.

Model	Latency
Google: Gemini 2.5 Flash	-33%
Anthropic: Claude 3 Haiku	-23%
Google: Gemini 3 Flash Preview	-14%
Anthropic: Claude Haiku 4.5	-8%

Same Cost, Better

Models at a similar price point with higher benchmark scores.

No alternatives found

Other Models from Google

Compare performance with other models from the same creator

Model	Score	Latency	Cost/1M
Google: Gemini 3 Pro Preview	91.5%	10.8s	$7.00
Google: Gemini 3 Flash Preview	91.2%	2.4s	$1.75
Google: Gemini 2.5 Pro	87.5%	10.0s	$5.63
Google: Gemini 2.5 Flash	80.9%	2.3s	$1.40
Google: Gemini 2.5 Flash Lite	75.4%	1.7s	$0.25
Google: Nano Banana Pro (Gemini 3 Pro Image Preview)	—	—	$7.00
Google: Gemini 2.5 Flash Image (Nano Banana)	—	—	$1.40
Google: Gemini 2.5 Flash Preview 09-2025	—	—	$1.40
Google: Gemini 2.5 Flash Lite Preview 09-2025	—	—	$0.25
Google: Gemini 2.5 Flash Image Preview (Nano Banana)	—	—	$1.40
Google: Gemma 3n 2B (free)	—	—	$0.0000
Google: Gemini 2.5 Pro Preview 06-05	—	—	$5.63
Google: Gemma 3n 4B	—	—	$0.0000
Google: Gemma 3n 4B	—	—	$0.03
Google: Gemini 2.5 Pro Preview 05-06	—	—	$5.63
Google: Gemma 3 4B	—	—	$0.0000
Google: Gemma 3 4B	—	—	$0.04
Google: Gemma 3 12B	—	—	$0.0000
Google: Gemma 3 12B	—	—	$0.07
Google: Gemma 3 27B	—	—	$0.0000
Google: Gemini 2.0 Flash Lite	—	—	$0.19
Google: Gemini 2.0 Flash Experimental (free)	—	—	$0.0000
Google: Gemma 2 27B	—	—	$0.65
Google: Gemma 2 9B	—	—	$0.06
Google: Gemma 3 27B	—	—	$0.09

Benchmark Performance

How this model performs across different benchmarks

Benchmark	Score	Rank
moose	100.0%	3 / 17
Math Bench: Subtraction (1-10)	100.0%	24 / 35
Customer service	100.0%	10 / 17
Testing_website	100.0%	10 / 17
solve n-queens in clojure in one shot	100.0%	3 / 17
Best bathroom technique	100.0%	10 / 17
Breakfast	100.0%	12 / 17
Define data taxonomy for product catalog suitable for PIM	100.0%	4 / 17
Repetitive Onomatopoeia Response Benchmark	100.0%	9 / 17
Math Bench: Addition (1-10)	100.0%	22 / 35
Customer support	100.0%	5 / 17
Cheeky_test	100.0%	10 / 17
Motor production test	100.0%	21 / 36
Customer Support Ticket Generation	100.0%	10 / 17
Math Bench: Multiplication (1-10)	100.0%	24 / 35
Structured Customer Support Extraction	100.0%	11 / 17
Smell test	100.0%	9 / 17
SaaS Customer Support Extraction and Strategy	100.0%	11 / 17
Math Bench: Arithmetic (1-100)	96.0%	29 / 35
Product Recommendations	93.3%	5 / 17
Math Bench: Division (1-10)	91.5%	30 / 35
Spatial Reasoning: Germany	90.3%	22 / 35
Enhancing FIDO UV Consistency with UXWG 2026 priority plan	90.0%	14 / 23
KUKA force Torque control programming skills	90.0%	8 / 17
Math Bench: Arithmetic (1-1000)	90.0%	21 / 35
Venture Capital Terms Benchmark	88.9%	19 / 25
Karlsruhe Local Knowledge Benchmark	85.4%	9 / 35
Character Frequency Bench	72.7%	23 / 35
Money Boy Cultural Literacy Test	57.1%	8 / 35
Product Recommendations	55.0%	30 / 36
Rust performance	30.0%	10 / 16
German Memelord Bench	23.8%	13 / 35
Karl Lorey knowlege	11.1%	7 / 36
Current Global Political Leaders	0.0%	7 / 17

Price vs Performance

Compare cost efficiency across all models

Current model

Other models

X-axis uses log scale for better visualization of price range

Score Over Time

Performance trends across all benchmark runs

Benchmark Activity

Number of benchmark runs over time

Quickstart

Get started with this model using OpenRouter

View on OpenRouter

import { OpenRouter } from "@openrouter/sdk";

const openrouter = new OpenRouter({
  apiKey: "<OPENROUTER_API_KEY>"
});

const completion = await openrouter.chat.completions.create({
  model: "google/gemini-2.0-flash-001",
  messages: [
    {
      role: "user",
      content: "Hello!"
    }
  ]
});

console.log(completion.choices[0].message.content);

Get your API key at openrouter.ai/keys