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Google · Efficient

Gemini 2.5 Flash Lite Preview (09/2025)

Added Sep 25, 2025

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Use in the app

Deprecated compatibility alias. Requests route to the stable Gemini 2.5 Flash Lite model.

  • 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
$0.10
Output
$0.40
Cache read
$0.01

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
65.5K

Side by side

Gemini 2.5 Flash Lite Preview (09/2025) compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Gemini 2.5 Flash Lite Preview (09/2025)GoogleThis modelGemini 3.1 Flash LiteGoogleRemove
ProviderGoogleGoogle
Discovery tierEfficientEfficient
AddedSep 25, 2025Mar 3, 2026
Limits
Context window1.05M1.05M
Max output65.54K65.54K
Average output—669 tokens
Pricing, USD per 1M tokens
Input$0.10Best$0.25
Output$0.40Best$1.50
Cache read$0.01Best$0.025
Cache write—$0.0833
Performance
Request success (24h)99.5%100.0%Best
Benchmark indexes
Intelligence Index9.315.6Best
Coding Index—34.7
Math Index46.7—
Capabilities
ReasoningYesYes
ToolsYesYes
VisionYesYes
Structured outputYesYes
PDF inputYesYes
Audio inputYesYes
Video inputNoYes
Reasoning effortlow, medium, highminimal, low, medium, high

Public evaluations

Benchmarks

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

  • Gemini 2.5 Flash Lite Preview (09/2025)
  • Gemini 3.1 Flash Lite

Intelligence Index

  • Gemini 2.5 Flash Lite Preview (09/2025)9.3
  • Gemini 3.1 Flash Lite15.6

Gemini 2.5 Flash Lite Preview (09/2025): Better than 18% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Gemini 2.5 Flash Lite Preview (09/2025): —
    • Gemini 3.1 Flash Lite: 34.7

  • Math Index

    Composite of the math evaluations

    • Gemini 2.5 Flash Lite Preview (09/2025): 46.7
    • Gemini 3.1 Flash Lite: —

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Gemini 2.5 Flash Lite Preview (09/2025): —
    • Gemini 3.1 Flash Lite: 6.8%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Gemini 2.5 Flash Lite Preview (09/2025): —
    • Gemini 3.1 Flash Lite: 0.5%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Gemini 2.5 Flash Lite Preview (09/2025): —
    • Gemini 3.1 Flash Lite: 207 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Gemini 2.5 Flash Lite Preview (09/2025): —
    • Gemini 3.1 Flash Lite: 430 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Gemini 2.5 Flash Lite Preview (09/2025): —
    • Gemini 3.1 Flash Lite: 7.8%

  • AA-LCRv1.1

    Reasoning across long documents

    • Gemini 2.5 Flash Lite Preview (09/2025): 49.7%
    • Gemini 3.1 Flash Lite: 74.3%Top

  • MLCR-AA

    Long-context reasoning over medical records

    • Gemini 2.5 Flash Lite Preview (09/2025): —
    • Gemini 3.1 Flash Lite: 5.0%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Gemini 2.5 Flash Lite Preview (09/2025): 5.1%
    • Gemini 3.1 Flash Lite: 17.2%Top

  • GPQA Diamond

    Graduate-level science questions

    • Gemini 2.5 Flash Lite Preview (09/2025): 65.1%
    • Gemini 3.1 Flash Lite: 82.2%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Gemini 2.5 Flash Lite Preview (09/2025): 79.6%
    • Gemini 3.1 Flash Lite: —

  • IFBench

    Following precise output instructions

    • Gemini 2.5 Flash Lite Preview (09/2025): 41.8%
    • Gemini 3.1 Flash Lite: 77.2%Top

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Gemini 2.5 Flash Lite Preview (09/2025): —
    • Gemini 3.1 Flash Lite: 0.5%

  • SciCode

    Scientific computing in Python

    • Gemini 2.5 Flash Lite Preview (09/2025): —
    • Gemini 3.1 Flash Lite: 43.4%

  • LiveCodeBench

    Recent competitive programming problems

    • Gemini 2.5 Flash Lite Preview (09/2025): 64.1%
    • Gemini 3.1 Flash Lite: —

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Gemini 2.5 Flash Lite Preview (09/2025): 46.7%
    • Gemini 3.1 Flash Lite: —

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Gemini 2.5 Flash Lite Preview (09/2025): 7.6%
    • Gemini 3.1 Flash Lite: 24.2%Top

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Gemini 2.5 Flash Lite Preview (09/2025): 30.4%
    • Gemini 3.1 Flash Lite: 31.3%Top

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Gemini 2.5 Flash Lite Preview (09/2025): 49.7%
    • Gemini 3.1 Flash Lite: 74.3%Top

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
0.0%
About $0.10 per 1M input tokens with caching
Request success (24h)
99.5%
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 76.0%
  • 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-lite-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-lite-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.