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Google · Efficient

Gemini 2.5 Flash Preview (09/2025)

Added Sep 25, 2025

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Use in the app

State-of-the-art Gemini 2.5 Flash checkpoint tuned for advanced reasoning, coding, math, and scientific tasks. Built-in thinking for higher accuracy and nuanced context handling. Routed to Gemini 2.5 Flash (stable).

  • Reasoning
  • Tools
  • Vision
  • Structured output
  • PDF input
  • Audio input
Input
Text, Images, Audio
Output
Text
Reasoning effort
low · medium · high
Discovery tier
Efficient

Pricing

USD per 1M tokens
Input
$0.30
Output
$2.50
Cache read
$0.03

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
65.5K

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TryOpenAI o1 ProKimi K2 0711 FastNvidia Nemotron 3 Super 120BAll 3

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

Intelligence Index

12.4

Better than 26% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Math Index

    56.7

    Composite of the math evaluations

    Better than 50% of 118 scored models

Document reasoning

  • AA-LCRv1.1

    60.0%

    Reasoning across long documents

    Better than 36% of 309 scored models

Reasoning and knowledge

  • Humanity’s Last Exam

    8.7%

    Expert-level questions across academic fields

    Better than 29% of 323 scored models

  • GPQA Diamond

    76.6%

    Graduate-level science questions

    Better than 39% of 291 scored models

  • MMLU-Pro

    83.6%

    Multi-subject knowledge and reasoning

    Better than 76% of 132 scored models

  • IFBench

    43.5%

    Following precise output instructions

    Better than 38% of 215 scored models

Coding

  • LiveCodeBench

    62.5%

    Recent competitive programming problems

    Better than 61% of 129 scored models

Math

  • AIME 2025

    56.7%

    Competition mathematics, 2025 problems

    Better than 50% of 118 scored models

Legacy evaluations

  • Terminal-Bench Hard

    14.4%

    Earlier terminal task suite

    Better than 31% of 212 scored models

  • τ²-Bench Telecom

    28.4%

    Tool use in a customer-support simulation

    Better than 19% of 214 scored models

  • AA-LCR (unversioned)

    60.0%

    Long-context reasoning, earlier grading

    Better than 36% of 309 scored models

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Prompt cache hits
41.0%
About $0.19 per 1M input tokens with caching
Request success (24h)
98.4%
Reliable

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Hourly request success · last 72 hoursLowest hour 80.0%
  • Healthy (98% or more)
  • Degraded (90–98%)
  • Down (under 90%)
  • No requests

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-2.5-flash-preview-09-2025",
    "reasoning_effort": "medium",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="gemini-2.5-flash-preview-09-2025",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Google

Other Google models, starting with the same family.