Google DeepMind Releases Gemini 3.5 & Gemini Flash 3.5

Google Gemini 3.5Actionable Frontier Intelligence

Optimized for autonomous agentic workflows. The high-performance Gemini Flash 3.5 model delivers exceptional multi-step reasoning with a 4x throughput speed multiplier, while the core Gemini 3.5 series cuts operational costs by 50% for complex long-horizon developer pipelines.

4xOutput Throughput
76.2%Terminal-Bench 2.1
1656GDPval-AA Elo
<50%Operational Cost
Antigravity Console

Real-time Generation Speed (Tokens/Sec)

Gemini 3.5 Flash delivers exceptional multi-step reasoning capabilities with industry-leading low latency.

Gemini 3.5 Flash (4x Speed Multiplier)0 tokens/s
Standard Frontier Model0 tokens/s
Source: Artificial Analysis Index
Google DeepMind Gemini 3.5 light illustration representing parallel workflow nodes and automated developer subagents
Frontier Safety Standard Active: Cybersecurity Risk Mitigated

CORE CAPABILITIES

Engineered for the Age of Autonomous Gemini 3.5 Agents

The Gemini 3.5 architecture redefines operational autonomy. Beyond simple chatbot answers, the Gemini Flash 3.5 pipeline enables high-throughput subagents to coordinate and solve complex challenges concurrently.

4x Throughput & Real-Time Speed

Powering the new Gemini Flash 3.5 model with output token throughput speeds up to 4 times faster than predecessor models, seamlessly resolving latency bottlenecks for complex tasks.

Standard Metric75% Latency Reduction

Collaborative Subagent Coordination

Engineered for native multi-agent coordination, enabling parallel Gemini 3.5 subagents to break down complex long-horizon developer targets, perform self-correction, and execute sequences.

Standard Metric1656 GDPval Elo Rating

Dominant AI Coding Capabilities

Highly tuned for structural refactoring, dependency compiling, and Next.js modern migrations. Runs automated debugging sequences to identify and fix build errors.

Standard Metric76.2% on Terminal-Bench 2.1

Advanced Multimodal Synthesis

Processes detailed statistical models, charts, and architectural assets. Renders fully interactive user interface layouts and dynamic diagrams from simple text directives.

Standard Metric84.2% CharXiv Reasoning

Frontier Safeguards & Interpretability

Developed strictly under the Frontier Safety Framework. Uses novel interpretability protocols to analyze inner reasoning structures before returning system responses.

Standard MetricEnterprise Grade Safety

REAL-WORLD IMPACT

Transitioning from Static QA to Autonomous Actions

See how the next-generation Gemini 3.5 architecture empowers enterprises like Shopify, Salesforce, and Macquarie Bank to boost efficiency.

DEVELOPERS

Developers: Autonomous Coding Copilot

Empowered by the Google Antigravity developer kit and the Gemini API, developers can deploy multi-agent code refactoring pipelines with full codebase context.

Legacy to Next.js Migration

Using the Antigravity toolkit, Gemini 3.5 Flash automatically refactored dozens of legacy files, upgrading system components to Next.js and Tailwind CSS v4.

Dual-Agent Self-Correction Loop

One subagent generates core application code while another plays and inspects compiler diagnostics, synthesizing AlphaZero algorithms in under 6 hours.

Generative UI in Seconds

Delivers complete visual interfaces featuring active state-management and payment checkout interfaces from simple wireframe doodles.

ENTERPRISES

Enterprises: Workflow Automation at Scale

By integrating Gemini 3.5 with low-latency document reading, enterprises automate workflows that previously spanned multiple days.

Macquarie Bank Onboarding

Leverages Gemini 3.5 Flash to parse complex, 100+ page contracts, extracting onboarding parameters and identifying abnormalities in seconds.

Shopify Merchant Growth Forecasts

Shopify runs concurrent subagents to calculate macro transaction patterns and yield high-probability multi-variable merchant forecast models.

Salesforce Agentforce Multitasking

Integrates Gemini 3.5 into Agentforce to support multi-turn tool calling pipelines, helping retain user context across platforms.

Xero & Ramp Tax / OCR Automation

Xero automates complex tax collection matching; Ramp leverages transaction records to run extreme-precision document classification.

RESEARCHERS

Researchers: Knowledge Synthesis

Breaks past the limitations of traditional text-only networks. Excels at multimodal inference, visual data mining, and mathematical chart reading.

CharXiv Multimodal Breakthrough

Achieves an outstanding 84.2% on CharXiv visual reasoning datasets, successfully parsing charts and formulas in dense academic whitepapers.

Databricks Diagnostic Agent

Actively monitors massive computational clusters, analyzes error traces, and deploys corrective source patches autonomously.

INDUSTRY COMPARISON

Proven Performance Against Industry Standards

We evaluated the high-performance Gemini Flash 3.5 model against leading industry networks. The results are clear: the Gemini 3.5 series delivers flagship-tier reasoning and coding capabilities at extreme speeds and a fraction of the cost.

Benchmark
Gemini 3.5 Flash
Primary Edition
Gemini 3 FlashGemini 3.1 ProClaude Sonnet 4.6Claude Opus 4.7GPT-5.5
Terminal-bench 2.1 (Coding)76.2%58.0%70.3%-66.1%78.2%
SWE-Bench Pro (Coding Task)55.1%49.6%54.2%-64.3%58.6%
MCP Atlas (Multi-step Agentic)83.6%62.0%78.2%69.5%79.1%75.3%
OSWorld-Verified (Computer Use)78.4%65.1%76.2%72.5%78.0%78.7%
GDPval-AA (Value Knowledge Work)165612041314167617531769
CharXiv Reasoning (Multimodal)84.2%80.3%83.3%72.4%82.1%84.1%
Humanity's Last Exam (Reasoning)40.2%33.7%44.4%33.2%46.9%41.4%
ARC-AGI-2 (Abstract Puzzle)72.1%33.6%77.1%58.3%75.8%84.6%

Reduced Operation Costs by Over 50%

When executing deep, multi-agent workflows, the highly optimized Gemini Flash 3.5 model cuts computational costs in half compared to conventional frontier networks.

Gemini 3.5 Pro Private Preview

The flagship Gemini 3.5 Pro is currently in private preview with select enterprise partners, delivering unparalleled reasoning depth for extremely high-complexity logical pipelines.

FAQ SHEET

Frequently Asked Questions

Get technical insights about agent workflows, Antigravity integration setups, and API limits.

What is an Agentic Workflow, and how does it differ from standard chat interactions?
Standard chat models operate on a simple 'question-and-answer' single-stage pattern, which struggles with complex software development or financial analysis. An Agentic Workflow allows the AI model to break down a main objective into multiple sub-goals and dispatch concurrent subagents. For instance, one subagent writes code, while another executes it and inspects errors, forming an autonomous self-correction loop. Gemini 3.5 is built from the ground up to support this coordination natively.
How does Gemini 3.5 Flash achieve a 4x output throughput speed multiplier?
Gemini 3.5 Flash introduces fundamental optimizations in model routing, tensor compilation, and hardware utilization. By leveraging highly efficient attention mechanisms customized for multi-stage tasks, it delivers four times faster token generation speeds than standard frontier models. This eliminates latency bottlenecks during continuous self-reflection and multi-turn subagent runs.
How can developers access the Gemini 3.5 series and Antigravity parallel agent toolkit?
Developers can sign up for the Google Antigravity developer platform or access Gemini API keys directly via Google AI Studio. Within the Antigravity console, Gemini 3.5 Flash comes with native subagent orchestration harnesses, allowing you to define agent roles, endpoints, and recursive steps in just a few lines of code. It is currently available in Google AI Studio, Antigravity, and Android Studio.
What are the primary upgrades in Gemini 3.5 Flash compared to Gemini 3.1 Pro or Gemini 2.5?
Compared to Gemini 3.1 Pro, the new 3.5 Flash scores an outstanding 76.2% on the Terminal-Bench 2.1 coding dataset and reaches 84.2% on CharXiv visual reasoning. More importantly, it slashes compute overhead by over 50% for complex workflows, solving cost constraints for large-scale code refactoring or multi-page invoice indexing, while incorporating Gemini 2.5's advanced real-time voice and vision capabilities.
How does Google ensure data privacy and security for enterprise multi-agent workflows?
Gemini 3.5 is developed under Google's strict Frontier Safety Framework, which filters cybersecurity and CBRN (Chemical, Biological, Radiological, and Nuclear) risks in real-time. For corporate systems, Google Enterprise and the Gemini Enterprise Agent Platform guarantee that none of your uploaded invoices, contracts, or source code files will ever be used for training public models.
What is Gemini Spark, and how does it leverage Gemini 3.5 Flash?
Gemini Spark is Google's new autonomous personal agent, powered by Gemini 3.5 Flash. Running 24/7 in the background, it autonomously manages digital routines, organizes calendars, matches invoices, and compiles action logs based on secure permissions. Gemini Spark is currently rolling out in private beta, with wider access coming next week for US Google One AI Premium subscribers.
What is the API pricing model, and is there a free tier for developers?
Gemini 3.5 Flash offers a highly generous free tier via Google AI Studio, providing up to 15 requests per minute at no cost. For high-scale production systems, pay-as-you-go pricing delivers flagship-level inference at less than half the per-token cost of comparable industry models, making it the most cost-effective solution for running heavy multi-agent loops.