Google: Gemini 2.5 Flash

by Google

Gemini 2.5 Flash is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in "thinking" capabilities, enabling it to provide responses with greater accuracy and nuanced context handling. Additionally, Gemini 2.5 Flash is configurable through the "max tokens for reasoning" parameter, as described in the documentation (https://openrouter.ai/docs/use-cases/reasoning-tokens#max-tokens-for-reasoning).

Avg Score

80.9%

269 answers

Avg Latency

2.3s

36 runs

Pricing

$0.30

input

$2.50

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
Google: Gemini 2.0 Flash	-95%
DeepSeek: DeepSeek V3.2	-90%
DeepSeek: DeepSeek V3 0324	-84%
MoonshotAI: Kimi K2 Thinking	-64%
Mistral: Mistral Large 3 2512	-62%

Same Quality, Faster

Models with similar or better performance but lower latency.

Model	Latency
Google: Gemini 2.0 Flash	-45%
Google: Gemini 3 Flash Preview	-19%
Anthropic: Claude Haiku 4.5	-13%

Same Cost, Better

Models at a similar price point with higher benchmark scores.

Model	Score
Google: Gemini 3 Flash Preview	+9%
MoonshotAI: Kimi K2 Thinking	+0%

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 2.0 Flash	80.0%	2.2s	$0.25
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
Math Bench: Subtraction (1-10)	100.0%	3 / 35
Enhancing FIDO UV Consistency with UXWG 2026 priority plan	100.0%	9 / 23
Math Bench: Arithmetic (1-100)	100.0%	3 / 35
Customer service	100.0%	3 / 17
Math Bench: Division (1-10)	100.0%	4 / 35
Testing_website	100.0%	2 / 17
Venture Capital Terms Benchmark	100.0%	3 / 25
solve n-queens in clojure in one shot	100.0%	5 / 17
Best bathroom technique	100.0%	3 / 17
Breakfast	100.0%	3 / 17
Repetitive Onomatopoeia Response Benchmark	100.0%	3 / 17
KUKA force Torque control programming skills	100.0%	3 / 17
Math Bench: Addition (1-10)	100.0%	3 / 35
Customer support	100.0%	3 / 17
Cheeky_test	100.0%	3 / 17
Motor production test	100.0%	22 / 36
Customer Support Ticket Generation	100.0%	3 / 17
Math Bench: Multiplication (1-10)	100.0%	2 / 35
Structured Customer Support Extraction	100.0%	5 / 17
Smell test	100.0%	3 / 17
SaaS Customer Support Extraction and Strategy	100.0%	2 / 17
Product Recommendations	96.7%	4 / 17
Spatial Reasoning: Germany	90.5%	20 / 35
Rust performance	90.0%	2 / 16
Math Bench: Arithmetic (1-1000)	90.0%	25 / 35
Karlsruhe Local Knowledge Benchmark	78.3%	16 / 35
Product Recommendations	71.9%	20 / 36
Character Frequency Bench	67.3%	26 / 35
moose	50.0%	15 / 17
Money Boy Cultural Literacy Test	44.3%	12 / 35
Define data taxonomy for product catalog suitable for PIM	40.0%	15 / 17
German Memelord Bench	24.1%	11 / 35
Karl Lorey knowlege	11.1%	5 / 36
Current Global Political Leaders	0.0%	15 / 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-2.5-flash",
  messages: [
    {
      role: "user",
      content: "Hello!"
    }
  ]
});

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

Get your API key at openrouter.ai/keys