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Google · Efficient

Gemini 3.8 Flash

Added Sep 2, 2026

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Use in the app

Google's fast multimodal model for agentic workloads, including coding, tool use, image understanding, PDF and document extraction, audio, and video. Its capabilities, limits, reasoning behavior, and pricing currently mirror Gemini 3.7 Flash.

  • 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
$0.75
Output
$3.75
Cache read
$0.075
Cache write
$0.0417

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
65.5K
Average output (7 days)
1.2K tokens
Longer than 79% of 465 models

Side by side

Gemini 3.8 Flash compared

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

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Gemini 3.8 FlashGoogleThis modelMuse Spark 1.2MetaRemove
ProviderGoogleMeta
Discovery tierEfficientFrontier
AddedSep 2, 2026Aug 5, 2026
Limits
Context window1.05MBest1M
Max output65.54K65.54K
Average output1.2K tokens172 tokens
Pricing, USD per 1M tokens
Input$0.75Best$1.25
Output$3.75Best$4.25
Cache read$0.075Best$0.15
Cache write$0.0417—
Performance
Throughput164.7 tok/s—
Time to first token5.9 s—
Request success (24h)99.8%—
Benchmark indexes
Intelligence Index39.8Best39.6
Coding Index74.1Best72.2
Capabilities
ReasoningYesYes
ToolsYesYes
VisionYesYes
Structured outputYesYes
PDF inputYesYes
Audio inputYesYes
Video inputYesYes
Parallel toolsNoYes
Reasoning effortminimal, low, medium, highminimal, low, medium, high, xhigh

Public evaluations

Benchmarks

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

  • Gemini 3.8 Flash
  • Muse Spark 1.2

Intelligence Index

  • Gemini 3.8 Flash39.8
  • Muse Spark 1.239.6

Gemini 3.8 Flash tested at medium reasoning effort

Gemini 3.8 Flash: Better than 84% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Gemini 3.8 Flash: 74.1Top
    • Muse Spark 1.2: 72.2

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Gemini 3.8 Flash: 60.9%Top
    • Muse Spark 1.2: 40.6%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Gemini 3.8 Flash: 31.1%Top
    • Muse Spark 1.2: 15.7%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Gemini 3.8 Flash: 1,181 Elo
    • Muse Spark 1.2: 1,327 EloTop

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Gemini 3.8 Flash: 1,423 Elo
    • Muse Spark 1.2: 1,475 EloTop

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Gemini 3.8 Flash: 22.8%Top
    • Muse Spark 1.2: 17.4%

  • AA-LCRv1.1

    Reasoning across long documents

    • Gemini 3.8 Flash: 84.0%Top
    • Muse Spark 1.2: 79.0%

  • MLCR-AA

    Long-context reasoning over medical records

    • Gemini 3.8 Flash: 12.8%Top
    • Muse Spark 1.2: 7.2%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Gemini 3.8 Flash: 42.1%
    • Muse Spark 1.2: 45.5%Top

  • GPQA Diamond

    Graduate-level science questions

    • Gemini 3.8 Flash: 93.5%Top
    • Muse Spark 1.2: 90.4%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Gemini 3.8 Flash: 19.7%Top
    • Muse Spark 1.2: 7.1%

  • SciCode

    Scientific computing in Python

    • Gemini 3.8 Flash: 55.1%
    • Muse Spark 1.2: 57.4%Top

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Gemini 3.8 Flash: 84.0%Top
    • Muse Spark 1.2: 79.0%

Scores from Artificial Analysis, updated Oct 26, 2026. Gemini 3.8 Flash was tested at medium reasoning effort; compare scores measured at the same effort.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
164.7 tok/s
Faster than 80% of 250 models
Time to first token
5.9 s
Quicker than 27% of 250 models
Prompt cache hits
9.6%
About $0.69 per 1M input tokens with caching
Request success (24h)
99.8%
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 92.5%
  • 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-3.8-flash",
    "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-3.8-flash",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Google

Other Google models, starting with the same family.