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Google · Efficient

Gemini 3.5 Flash Lite

Added Jul 21, 2026

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Use in the app

Google's cost-efficient Gemini 3.5 Flash Lite model for high-volume multimodal reasoning, tool use, and structured-output workloads.

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

Pricing

USD per 1M tokens
Input
$0.30
Output
$2.50
Cache read
$0.03
Cache write
$0.0833

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
65.5K
Average output (7 days)
178 tokens
Longer than 19% of 465 models

Side by side

Gemini 3.5 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 3.5 Flash LiteGoogleThis modelOpenAI o3-pro (2025-06-10)OpenAIRemove
ProviderGoogleOpenAI
Discovery tierEfficientFrontier
AddedJul 21, 2026Jan 1, 2024
Limits
Context window1.05MBest200K
Max output65.54K100KBest
Average output178 tokens—
Pricing, USD per 1M tokens
Input$0.30Best$22.00
Output$2.50Best$88.00
Cache read$0.03Best$11.00
Cache write$0.0833—
Performance
Throughput237.4 tok/s—
Time to first token1.4 s—
Request success (24h)99.9%—
Benchmark indexes
Intelligence Index22.2Best21.9
Coding Index49.3—
Capabilities
ReasoningYesYes
ToolsYesYes
VisionYesNo
Structured outputYesYes
PDF inputYesNo
Audio inputYesNo
Video inputYesNo
Reasoning effortminimal, low, medium, highlow, medium, high

Public evaluations

Benchmarks

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

  • Gemini 3.5 Flash Lite
  • OpenAI o3-pro (2025-06-10)

Intelligence Index

  • Gemini 3.5 Flash Lite22.2
  • OpenAI o3-pro (2025-06-10)21.9

Gemini 3.5 Flash Lite: Better than 53% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Gemini 3.5 Flash Lite: 49.3
    • OpenAI o3-pro (2025-06-10): —

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Gemini 3.5 Flash Lite: 25.0%
    • OpenAI o3-pro (2025-06-10): —

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Gemini 3.5 Flash Lite: 3.3%
    • OpenAI o3-pro (2025-06-10): —

  • Harvey LAB-AAv1.1

    Legal tasks passed in full, with no material hallucination

    • Gemini 3.5 Flash Lite: 0.0%
    • OpenAI o3-pro (2025-06-10): —

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Gemini 3.5 Flash Lite: 650 Elo
    • OpenAI o3-pro (2025-06-10): —

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Gemini 3.5 Flash Lite: 985 Elo
    • OpenAI o3-pro (2025-06-10): —

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Gemini 3.5 Flash Lite: 13.6%
    • OpenAI o3-pro (2025-06-10): —

  • AA-LCRv1.1

    Reasoning across long documents

    • Gemini 3.5 Flash Lite: 76.0%
    • OpenAI o3-pro (2025-06-10): —

  • MLCR-AA

    Long-context reasoning over medical records

    • Gemini 3.5 Flash Lite: 10.6%
    • OpenAI o3-pro (2025-06-10): —

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Gemini 3.5 Flash Lite: 18.8%
    • OpenAI o3-pro (2025-06-10): —

  • GPQA Diamond

    Graduate-level science questions

    • Gemini 3.5 Flash Lite: 83.8%
    • OpenAI o3-pro (2025-06-10): 84.5%Top

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Gemini 3.5 Flash Lite: 1.0%
    • OpenAI o3-pro (2025-06-10): —

  • SciCode

    Scientific computing in Python

    • Gemini 3.5 Flash Lite: 41.3%
    • OpenAI o3-pro (2025-06-10): —

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Gemini 3.5 Flash Lite: 76.0%
    • OpenAI o3-pro (2025-06-10): —

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
237.4 tok/s
Faster than 89% of 250 models
Time to first token
1.4 s
Quicker than 88% of 250 models
Prompt cache hits
21.4%
About $0.24 per 1M input tokens with caching
Request success (24h)
99.9%
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 94.7%
  • 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": "google/gemini-3.5-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="google/gemini-3.5-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.