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Gemini 3.5 Flash

by Google DeepMind · Released May 2026

Multimodal1M Context
78.5
avg score
Rank #26
Compare
Better than 91% of all models
Context
1.0M tokens (~524 books)
Input $/1M
$1.50
Output $/1M
$9.00
Type
multimodal
License
Proprietary
Benchmarks
19 tested
Data updated today
About

Gemini 3.5 Flash is Google's high-efficiency multimodal model, bringing near-Pro level coding and reasoning at Flash-tier cost and speed. It is highly optimized for coding proficiency and parallel agentic execution...

Tested on 19 benchmarks with 62.6% average. Top scores: Chatbot Arena Elo — Coding (1505.5%), Chatbot Arena Elo — Overall (1476.3%), OTIS Mock AIME 2024-2025 (95.5%).

Looking for similar performance at lower cost?
MiniMax M3 scores 79.7 (102% as good) at $0.30/1M input · 80% cheaper
Capabilities
coding
71.0
#22 globally
reasoning
78.9
#12 globally
math
47.7
#94 globally
knowledge
69.6
#21 globally
agentic
49.6
#4 globally
speed
87.7
#8 globally
Benchmark Scores
Compare All
Tested on 19 benchmarks · Ranked across 7 categories
Score Distribution (all 274 models)
0255075100
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SWE-Bench verified

Real-world software engineering tasks from GitHub issues. Models must diagnose bugs and write patches that pass test suites. Human-verified subset of SWE-bench.

79.3
WeirdML

Unusual and adversarial machine learning challenges. Tests robustness of reasoning about edge cases in ML systems.

62.6
ARC-AGI

Abstraction and Reasoning Corpus. Tests fluid intelligence through novel visual pattern recognition puzzles. Core measure of general intelligence.

92.5
ARC-AGI-2

ARC-AGI 2, harder sequel to ARC. More complex abstract reasoning patterns that test generalization ability beyond training data.

72.1
SimpleBench

Deceptively simple questions that humans find easy but AI models often get wrong. Tests common sense and reasoning gaps.

72.0
OTIS Mock AIME 2024-2025

Mock AIME (American Invitational Mathematics Exam) problems from OTIS. Tests mathematical competition performance.

95.5
FrontierMath-2025-02-28-Private

Original research-level math problems created by professional mathematicians. Problems are unpublished and cannot be memorized.

39.0
Excellent (85+) Good (70-85) Average (50-70) Below (<50)
Links
Documentation
BenchGecko API
gemini-3-5-flash
Specifications
  • Typemultimodal
  • Context1.0M tokens (~524 books)
  • ReleasedMay 2026
  • LicenseProprietary
  • StatusActive
  • Cost / Message~$0.012
Available On
Google DeepMind logoGoogle DeepMind$1.50
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Gemini 3.5 Flash is a proprietary multimodal AI model by Google DeepMind, released in May 2026. It has an average benchmark score of 78.5. Context window: 1M tokens.