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Google · Efficient

Gemini 2.5 Flash Lite

Added Jun 17, 2025

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Use in the app

Ultra-lightweight and fast variant of Gemini 2.5 Flash. Stable release optimized for speed and efficiency. Audio input costs $0.30 per million audio tokens.

  • Reasoning
  • Tools
  • Vision
  • Audio input
  • Video input
Input
Text, Images, Video, 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
Average output (7 days)
42 tokens
Longer than 3% of 465 models

Side by side

Gemini 2.5 Flash Lite 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 LiteGoogleThis modelGemini 3.5 Flash LiteGoogleRemove
ProviderGoogleGoogle
Discovery tierEfficientEfficient
AddedJun 17, 2025Jul 21, 2026
Limits
Context window1.05M1.05M
Max output65.54K65.54K
Average output42 tokens178 tokens
Pricing, USD per 1M tokens
Input$0.10Best$0.30
Output$0.40Best$2.50
Cache read$0.01Best$0.03
Cache write—$0.0833
Performance
Throughput250.0 tok/sBest228.5 tok/s
Time to first token0.5 sBest0.8 s
Request success (24h)99.5%99.8%Best
Benchmark indexes
Intelligence Index6.722.2Best
Coding Index—49.3
Math Index35.3—
Capabilities
ReasoningYesYes
ToolsYesYes
VisionYesYes
Structured outputNoYes
PDF inputNoYes
Audio inputYesYes
Video inputYesYes
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
  • Gemini 3.5 Flash Lite

Intelligence Index

  • Gemini 2.5 Flash Lite6.7
  • Gemini 3.5 Flash Lite22.2

Gemini 2.5 Flash Lite: Better than 6% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Gemini 2.5 Flash Lite: —
    • Gemini 3.5 Flash Lite: 49.3

  • Math Index

    Composite of the math evaluations

    • Gemini 2.5 Flash Lite: 35.3
    • Gemini 3.5 Flash Lite: —

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Gemini 2.5 Flash Lite: —
    • Gemini 3.5 Flash Lite: 25.0%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Gemini 2.5 Flash Lite: —
    • Gemini 3.5 Flash Lite: 3.3%

  • Harvey LAB-AAv1.1

    Legal tasks passed in full, with no material hallucination

    • Gemini 2.5 Flash Lite: —
    • Gemini 3.5 Flash Lite: 0.0%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Gemini 2.5 Flash Lite: —
    • Gemini 3.5 Flash Lite: 650 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Gemini 2.5 Flash Lite: —
    • Gemini 3.5 Flash Lite: 985 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Gemini 2.5 Flash Lite: —
    • Gemini 3.5 Flash Lite: 13.6%

  • AA-LCRv1.1

    Reasoning across long documents

    • Gemini 2.5 Flash Lite: 32.0%
    • Gemini 3.5 Flash Lite: 76.0%Top

  • MLCR-AA

    Long-context reasoning over medical records

    • Gemini 2.5 Flash Lite: —
    • Gemini 3.5 Flash Lite: 10.6%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Gemini 2.5 Flash Lite: 3.7%
    • Gemini 3.5 Flash Lite: 18.8%Top

  • GPQA Diamond

    Graduate-level science questions

    • Gemini 2.5 Flash Lite: 47.4%
    • Gemini 3.5 Flash Lite: 83.8%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Gemini 2.5 Flash Lite: 72.4%
    • Gemini 3.5 Flash Lite: —

  • IFBench

    Following precise output instructions

    • Gemini 2.5 Flash Lite: 31.5%
    • Gemini 3.5 Flash Lite: —

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Gemini 2.5 Flash Lite: —
    • Gemini 3.5 Flash Lite: 1.0%

  • SciCode

    Scientific computing in Python

    • Gemini 2.5 Flash Lite: —
    • Gemini 3.5 Flash Lite: 41.3%

  • LiveCodeBench

    Recent competitive programming problems

    • Gemini 2.5 Flash Lite: 40.0%
    • Gemini 3.5 Flash Lite: —

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Gemini 2.5 Flash Lite: 35.3%
    • Gemini 3.5 Flash Lite: —

  • AIME

    Competition mathematics

    • Gemini 2.5 Flash Lite: 50.0%
    • Gemini 3.5 Flash Lite: —

  • MATH-500

    Competition math problems

    • Gemini 2.5 Flash Lite: 92.6%
    • Gemini 3.5 Flash Lite: —

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Gemini 2.5 Flash Lite: 2.3%
    • Gemini 3.5 Flash Lite: —

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Gemini 2.5 Flash Lite: 19.0%
    • Gemini 3.5 Flash Lite: —

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Gemini 2.5 Flash Lite: 32.0%
    • Gemini 3.5 Flash Lite: 76.0%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.

Throughput
250.0 tok/s
Faster than 90% of 250 models
Time to first token
0.5 s
Quickest of 250 models
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",
    "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",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Google

Other Google models, starting with the same family.