gemini-2.5-flash-preview-09-2025

completions

byopenrouter

gemini-2.5-flash-preview-09-2025

completions

Published by: googleProvider:

openrouter

Gemini 2.5 Flash Preview September 2025 Checkpoint 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).

Released

Sep 25, 2025

Knowledge

Jan 1, 2025

Context

1048576

Input

$0.3 / 1M tokens

Output

$2.5 / 1M tokens

Capabilities: tools, reasoning

Accepts: text, image

Returns: text

Released Sep 25, 2025Knowledge Cutoff: Jan 1, 2025

Context: 1048576 Input: $0.3 / 1M tokensOutput: $2.5 / 1M tokensCapabilities: tools, reasoningAccepts: text, imageReturns: text

Access gemini-2.5-flash-preview-09-2025 through LangDB AI Gateway

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Benchmark Results for gemini-2.5-flash-preview-09-2025

Category Performance Scores:

Maths: Score 78.30 (Top 23% - Rank #74)
Finance: Score 66.35 (Top 21% - Rank #68)
Science: Score 73.81 (Top 19% - Rank #61)
Writing: Score 63.37 (Top 19% - Rank #61)
Academia: Score 66.85 (Top 15% - Rank #48)
Marketing: Score 65.44 (Top 15% - Rank #48)
Programming: Score 42.50 (Top 24% - Rank #77)

Overall Performance: 65.22936507936508 average score across all categories

Detailed Benchmark Scores:

Benchmark	Score	Percentile	Domain
HLE	12.70	Top 15%	General Knowledge
GPQA	79.30	Top 17%	STEM (Physics, Chemistry, Biology)
SciCode	40.50	Top 11%	Scientific
MMLU-Pro	84.20	Top 14%	General Knowledge
LiveCodeBench	71.30	Top 19%	Programming
AA Math Index	78.30	Top 23%	Mathematics
AA Coding Index	42.50	Top 24%	Programming
AAII	54.40	Top 15%	General

GPQA Score: 79.30 - Graduate-level reasoning benchmark

Model Comparison:

Provider: openrouter

Model Type: completions

Context Size: 1048576 tokens

Comparing against 320 models in the database

Performance Analytics for gemini-2.5-flash-preview-09-2025

Usage Statistics (Last 1 Days):

Total Requests: 2 API calls
Average TPS: 6307.13 tokens per second
Average Response Time: 2494.30ms
Average Time to First Token: 780.20ms
Total Cost: $0.01
Average Request Cost: $0.0064

Daily Performance Breakdown:

Date	Requests	TPS	Response Time	TTFT	Cost
11/11/2025	2	6307.13	2494.30ms	780.20ms	$0.01

Performance Summary:

Model: gemini-2.5-flash-preview-09-2025 by openrouter

Monitoring Period: 11/11/2025 to 11/18/2025

Average Daily Requests: 2

Peak Daily Requests: 2

Statistics

View Full Statistics

Request Volume

Daily API requests

Performance (TPS)

Tokens per second

6307.13 tokens/s

Category Scores

Benchmark Tests

View Other Benchmarks

HLE

12.7

General Knowledge

GPQA

79.3

STEM (Physics, Chemistry, Biology)

SciCode

40.5

Scientific

MMLU-Pro

84.2

General Knowledge

LiveCodeBench

71.3

Programming

AA Math Index

78.3

Mathematics

AA Coding Index

42.5

Programming

AAII

54.4

General

Metric	HLE	GPQA	SciCode	MMLU-Pro	LiveCodeBench	AA Math Index	AA Coding Index	AAII
Score	12.7	79.3	40.5	84.2	71.3	78.3	42.5	54.4

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Code Examples

Integration samples and API usage

Code Samples for gemini-2.5-flash-preview-09-2025

Python SDK Example:

from openai import OpenAI

client = OpenAI(
    base_url="https://api.us-east-1.langdb.ai//projects/<your_project_id>",
    api_key="<your_api_key>"
)

response = client.chat.completions.create(
    model="gemini-2.5-flash-preview-09-2025",
    messages=[
        {"role": "user", "content": "Hello, how are you?"}
    ]
)

print(response.choices[0].message.content)

TypeScript SDK Example:

import OpenAI from 'openai';

const client = new OpenAI({
    baseURL: "https://api.us-east-1.langdb.ai//projects/<your_project_id>",
    apiKey: "<your_api_key>"
});

const response = await client.chat.completions.create({
    model: "gemini-2.5-flash-preview-09-2025",
    messages: [
        { role: "user", content: "Hello, how are you?" }
    ]
});

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

cURL Example:

curl -X POST "https://api.us-east-1.langdb.ai//projects/<your_project_id>/v1/chat/completions" \
  -H "Authorization: Bearer <your_api_key>" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-2.5-flash-preview-09-2025",
    "messages": [
        {"role": "user", "content": "Hello, how are you?"}
    ]
  }'

Model: gemini-2.5-flash-preview-09-2025

Provider: openrouter

API Endpoint: $https://api.us-east-1.langdb.ai/

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gemini-2.5-flash-preview-09-2025 by openrouter - AI Model Details, Pricing, and Performance Metrics

gemini-2.5-flash-preview-09-2025

gemini-2.5-flash-preview-09-2025

Access gemini-2.5-flash-preview-09-2025 through LangDB AI Gateway

Statistics

Category Scores

Benchmark Tests

Compare with Similar Models

Code Examples

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