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 26 benchmarks · BenchGecko score 61.3. Top scores: Chatbot Arena Elo — Coding (1505.5%), Chatbot Arena Elo — Overall (1476.3%), OTIS Mock AIME 2024-2025 (95.5%).
gpt-oss-20b (free) scores 61.0 (100% as good) at $0.00/1M input · 100% cheaper
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.
Unusual and adversarial machine learning challenges. Tests robustness of reasoning about edge cases in ML systems.
Abstraction and Reasoning Corpus. Tests fluid intelligence through novel visual pattern recognition puzzles. Core measure of general intelligence.
ARC-AGI 2, harder sequel to ARC. More complex abstract reasoning patterns that test generalization ability beyond training data.
Deceptively simple questions that humans find easy but AI models often get wrong. Tests common sense and reasoning gaps.
Mock AIME (American Invitational Mathematics Exam) problems from OTIS. Tests mathematical competition performance.
Original research-level math problems created by professional mathematicians. Problems are unpublished and cannot be memorized.
- Typemultimodal
- Context1.0M tokens (~524 books)
- ReleasedMay 2026
- LicenseProprietary
- StatusActive
- Cost / Message~$0.012
Frequently Asked Questions
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- Gemini 3.5 Flash by Google DeepMind. BenchGecko score 61.3, rank 79 of 312 scored models (normalized average of public benchmark scores).
- List price $1.50 input · $9.00 output per 1M tokens (as of 2026-10-05).
- Gecko Tests: Who Are You B (Knows who made it).
How to cite · data as of 2026-10-05
Gemini 3.5 Flash · benchmarks, pricing and providers. BenchGecko, data as of 2026-10-05. https://benchgecko.ai/model/gemini-3-5-flash
Credit "Source: BenchGecko" with a link. Prices per provider and Gecko Tests are BenchGecko data (CC BY 4.0); benchmark scores keep their original source, listed in the JSON. JSON · llms.txt · MCP