Google · Efficient

Gemini 3.6 Flash

Added Jul 21, 2026

Google's GA Flash model delivers near-Pro coding and agentic capability at Flash-tier speed and cost, with improved token efficiency over Gemini 3.5 Flash. It is optimized for multi-step orchestration, full-stack code refactoring, general reasoning, and multimodal workflows.

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): 932 tokens; Longer than 69% of 473 models

Side by side

Compare models

Put Gemini 3.6 Flash next to up to three other models. The comparison stays in the link, so you can share it.

TryDeepSeek V4 Flash Vision Exp Muse Spark 1.1 GLM 5.2 Thinking TEE All 3

Public evaluations

Benchmarks

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

Intelligence Index

34.0

Tested at high reasoning effort

Better than 77% of 326 scored models

3.8Catalog models by score55.1

Indexes

Coding Index
69.2
Composite of the coding evaluations
Better than 76% of 168 scored models

Agentic work

AutomationBench-AA
53.0%
Workflow automation, penalized for guardrail violations
Better than 66% of 173 scored models
AutomationBench-AA tasks completed
16.4%
Workflows finished end to end without a guardrail violation
Better than 62% of 173 scored models
AA-Briefcasev1.1
955 Elo
Agentic knowledge work, rated head to head
Better than 42% of 166 scored models
GDPval-AAv2.1
1,286 Elo
Economically valuable occupational tasks, rated head to head
Better than 58% of 187 scored models

Document reasoning

GDP.pdf
17.4%
Professional reasoning over PDF documents, all-pass rate
Better than 68% of 171 scored models
AA-LCRv1.1
80.0%
Reasoning across long documents
Better than 80% of 309 scored models
MLCR-AA
10.0%
Long-context reasoning over medical records
Better than 33% of 121 scored models

Reasoning and knowledge

Humanity’s Last Exam
40.8%
Expert-level questions across academic fields
Better than 78% of 323 scored models
GPQA Diamond
92.8%
Graduate-level science questions
Better than 89% of 291 scored models

Coding

Terminal-Benchv4.0
7.1%
Practical software engineering in a terminal
Better than 58% of 171 scored models
SciCode
53.4%
Scientific computing in Python
Better than 63% of 174 scored models

Legacy evaluations

AA-LCR (unversioned)
80.0%
Long-context reasoning, earlier grading
Better than 80% of 309 scored models

Scores from Artificial Analysis, updated Oct 26, 2026. Gemini 3.6 Flash was tested at high 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: 189.5 tok/s; Faster than 83% of 256 models
Time to first token: 7.5 s; Quicker than 15% of 256 models
Prompt cache hits: 29.7%; About $0.55 per 1M input tokens with caching
Request success (24h): 99.4%; 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 96.2%

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-3.6-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-3.6-flash",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Google

Other Google models, starting with the same family.

Indexes

Coding Index

Agentic work

AutomationBench-AA

AutomationBench-AA tasks completed

AA-Briefcasev1.1

GDPval-AAv2.1

Document reasoning

GDP.pdf

AA-LCRv1.1

MLCR-AA

Reasoning and knowledge

Humanity’s Last Exam

GPQA Diamond

Coding

Terminal-Benchv4.0

SciCode

Legacy evaluations

AA-LCR (unversioned)