# Gemini 3.5 Flash

> Google's fast Flash model that beats Gemini 3.1 Pro on agentic and coding tasks at ~4x the speed.

- Maker: Google
- Line: Gemini Flash
- Canonical page: https://ai-tldr.dev/models/gemini-3-5-flash/
- Updated: 2026-10-16

## In short

Gemini 3.5 Flash is Google's fast, cost-efficient model in the Gemini Flash line, announced at Google I/O 2026 and made generally available on May 19, 2026 as the API model gemini-3.5-flash. It has a 1M-token context window and costs $1.50 per million input tokens and $9.00 per million output tokens. You can use it through Google Gemini API, Google Vertex AI and OpenRouter.

## Facts

| Fact | Value | Source |
| --- | --- | --- |
| Context window | 1M (max output 64K) | [1] |
| Input price | $1.50 / 1M tokens (cached $0.15 / 1M tokens) | [2] |
| Output price | $9.00 / 1M tokens | [2] |
| Licence | Proprietary · API only | [1] |
| Released | 19 May 2026 | [3] |
| Parameters | Not disclosed | [1] |
| Knowledge cutoff | January 2025 | [1] |

## Sources

1. [Gemini 3.5 Flash model card](https://deepmind.google/models/model-cards/gemini-3-5-flash/)
2. [Gemini API pricing](https://ai.google.dev/gemini-api/docs/pricing)
3. [Gemini 3.5: frontier intelligence with action — Google blog](https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-5/)

## Overview

Gemini 3.5 Flash is Google's fast, cost-efficient model in the Gemini Flash line, announced at Google I/O 2026 and made generally available on May 19, 2026 as the API model gemini-3.5-flash. At launch it was positioned as the Flash tier's flagship for sustained agentic and coding work, and it was the first Flash-tier model to outperform a previous Pro tier (Gemini 3.1 Pro) on Google's published coding and agentic benchmarks. It was superseded by Gemini 3.6 Flash on July 21, 2026.

Gemini 3.5 Flash accepts text, images, audio, video, and PDFs/documents as input and returns text, with a 1 million-token context window and up to roughly 64K output tokens. Reasoning depth is adjustable through a thinking_level setting (minimal, low, medium, high), and Google reports the model delivers output around four times faster than other frontier models, making it well suited to high-throughput agent and tool-use loops.

The model is available through the Gemini API, Google AI Studio, Vertex AI, the Gemini app, Google Search AI Mode, and Google's Antigravity agentic IDE, and it is selectable in third-party tools such as Cursor. Its knowledge cutoff is January 2025; for newer information Google recommends the built-in search grounding tool.

## Benchmarks

- Terminal-Bench 2.1 (agentic coding): 76.2% ([source](https://deepmind.google/models/model-cards/gemini-3-5-flash/))
- SWE-Bench Pro: 55.1% ([source](https://deepmind.google/models/model-cards/gemini-3-5-flash/))
- MCP Atlas (multi-step workflows): 83.6% ([source](https://deepmind.google/models/model-cards/gemini-3-5-flash/))
- MMMU-Pro (multimodal reasoning): 83.6% ([source](https://deepmind.google/models/model-cards/gemini-3-5-flash/))
- ARC-AGI-2: 72.1% ([source](https://deepmind.google/models/model-cards/gemini-3-5-flash/))
- CharXiv Reasoning (chart understanding): 84.2% ([source](https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-5/))
- Artificial Analysis Intelligence Index: 55% ([source](https://artificialanalysis.ai/articles/gemini-3-5-flash-everything-you-need-to-know))

## Pricing

- Input: $1.50 / 1M tokens per 1M tokens
- Cached input: $0.15 / 1M tokens per 1M tokens
- Output: $9.00 / 1M tokens per 1M tokens

Paid tier; output price includes thinking tokens. Context caching also incurs $1.00 per 1M tokens per hour of storage. A free tier is available with usage limits.

Source: https://ai.google.dev/gemini-api/docs/pricing

## Strengths

- Frontier agentic and coding performance that surpasses Gemini 3.1 Pro on Terminal-Bench 2.1, MCP Atlas, and Finance Agent v2
- Very high output speed (Artificial Analysis measured ~280+ tokens/sec, roughly 70% faster than Gemini 3 Flash)
- 1 million-token context window for long-document and multi-file reasoning
- Native multimodal input across text, image, audio, video, and PDF
- Controllable reasoning via thinking_level plus dynamic compute allocation
- Built-in tool use: function calling, structured output, code execution, and search grounding

## Best for

- Coding agents and autonomous multi-step software tasks (e.g. terminal and SWE-style workflows)
- Tool-using and MCP-driven agents that need fast, cheap iterations
- Long-context document analysis and summarization across up to 1M tokens
- Multimodal understanding of charts, images, audio, and video
- High-volume production workloads where latency and cost matter
- Structured data extraction and function-calling pipelines

## How to access

- [Google Gemini API](https://ai.google.dev/gemini-api/docs/models/gemini-3.5-flash) — model id `gemini-3.5-flash`
- [Google Vertex AI](https://cloud.google.com/vertex-ai) — model id `gemini-3.5-flash`
- [OpenRouter](https://openrouter.ai/google/gemini-3.5-flash) — model id `google/gemini-3.5-flash`

## Gemini Flash versions

- [Gemini 3.6 Flash](https://ai-tldr.dev/models/gemini-3-6-flash/) (21 July 2026)
- Gemini 3.5 Flash (19 May 2026) — this page
- [Gemini 3 Flash](https://ai-tldr.dev/models/gemini-3-flash/) (17 December 2025)
- [Gemini 2.5 Flash](https://ai-tldr.dev/models/gemini-2-5-flash/) (17 April 2025)
- [Gemini 2.0 Flash](https://ai-tldr.dev/models/gemini-2-0-flash/) (30 January 2025)
- [Gemini 1.5 Flash](https://ai-tldr.dev/models/gemini-1-5-flash/) (14 May 2024)

## FAQ

### When was Gemini 3.5 Flash released?

Google announced Gemini 3.5 Flash at Google I/O 2026 and made it generally available on May 19, 2026, as the API model gemini-3.5-flash.

### What is the context window and output limit of Gemini 3.5 Flash?

It has a 1 million-token input context window and can produce up to about 64K output tokens. It accepts text, images, audio, video, and PDFs as input and returns text.

### How much does Gemini 3.5 Flash cost?

On the paid tier it is $1.50 per 1M input tokens and $9.00 per 1M output tokens (output includes thinking tokens), with cached input at $0.15 per 1M tokens. A free tier with usage limits is also available.

### How does Gemini 3.5 Flash compare to Gemini 3.1 Pro?

It is the first Flash-tier model to beat a previous Pro tier on Google's published benchmarks, outperforming Gemini 3.1 Pro on Terminal-Bench 2.1, MCP Atlas, and Finance Agent v2 while running roughly four times faster.

## Links

- [Gemini 3.5 Flash — Google DeepMind](https://deepmind.google/models/gemini/flash/)
- [Gemini 3.5 Flash model card](https://deepmind.google/models/model-cards/gemini-3-5-flash/)
- [Gemini API docs — models](https://ai.google.dev/gemini-api/docs/models)
- [Gemini API pricing](https://ai.google.dev/gemini-api/docs/pricing)
- [Gemini API release notes (GA changelog)](https://ai.google.dev/gemini-api/docs/changelog)
- [Gemini 3.5: frontier intelligence with action — Google blog](https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-5/)
- [What's new in Gemini 3.5 Flash — Gemini API docs](https://ai.google.dev/gemini-api/docs/interactions/whats-new-gemini-3.5)
- [Artificial Analysis — Gemini 3.5 Flash analysis](https://artificialanalysis.ai/articles/gemini-3-5-flash-everything-you-need-to-know)
- [Google AI Studio (playground)](https://aistudio.google.com/)

Source: AI/TLDR LLM registry, https://ai-tldr.dev/models/gemini-3-5-flash/