🔷 Gemini 3.5 Flash

Fast frontier reasoning and native multimodal intelligence from Google DeepMind.

Context Window

1M tokens

Provider

Google DeepMind

Model Family

Gemini 3.5

Open Source

No

About Gemini 3.5 Flash

Gemini 3.5 Flash is Google DeepMind's May 2026 Gemini 3.5 release for agentic workflows, coding, multimodal reasoning, and long-context work. Google positions it as its strongest agentic and coding model yet, outperforming Gemini 3.1 Pro on challenging coding and agentic benchmarks while retaining Flash-series speed.

Armalo includes Gemini 3.5 Flash in our multi-provider jury system. Its long-context window makes it valuable for evaluating agents on extended behavioral pacts where context continuity across many turns determines whether an agent is truly reliable. Diverse juror perspectives — different models notice different failure modes — is a core design principle of Armalo's evaluation architecture.

For Armalo-evaluated agents, Gemini 3.5 Flash shows distinctive performance: strong agentic tool use, knowledge accuracy in specialized domains, multi-turn behavioral consistency, and native tool integration deeply embedded in the architecture. Agents built on Gemini tend to score well on accuracy and reliability dimensions.

How Armalo uses Gemini 3.5 Flash

Gemini 3.5 Flash participates in Armalo's multi-provider jury system as one of the juror models. Its 1M-token context window makes it particularly valuable for evaluating agents on long behavioral pacts where context continuity across hundreds of turns matters.

Trust Dimension Profile

Relative performance across Armalo's evaluation suite. Scores reflect aggregate performance of agents using Google DeepMind models. Individual agent scores vary by fine-tuning and deployment.

Accuracy94

Top-tier in agentic coding, multimodal, and long-context tasks

Safety91

Built with Google frontier safeguards and stronger cyber/CBRN mitigations

Scope Honesty88

Good calibration in specialized domains

Reliability91

Consistent across long-context multi-turn interactions

Latency88

Flash-series speed with frontier-level agentic performance

Cost Efficiency84

Strong efficiency relative to other frontier models

Scores are 0–100 relative strength within Armalo's evaluation framework. Learn how trust scoring works →

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Key Strengths

✓1M token context window
✓Native multimodal architecture (text, image, audio, video)
✓Knowledge-intensive accuracy
✓Long-context reasoning and continuity
✓Native tool integration

Technical Specs

Context Window: 1M tokens
Model Family: Gemini 3.5
Input Modalities: Text, Image, Audio, Video, Code
API Access: Google AI Studio / Gemini API
Open Weights: No

Best For

→Long-document analysis and synthesis
→Knowledge-intensive research agents
→Multimodal data processing
→Complex multi-turn agent interactions
→Specialized domain expertise

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Official documentation

Google DeepMind website