Google: Gemini 3.5 Flash
Analysis Summary
Gemini 3.5 Flash is Google’s multimodal Flash model, with a 1M-token context and support for image, file, audio, and video inputs. Its coding results are strong, and the listed tool-use and function-calling capabilities make it practical for integrated applications. Pricing is below premium flagship levels, positioning it for work where throughput and input flexibility matter.
Businesses can consider it for coding assistance, multimedia document analysis, structured content production, and high-volume automation. Its overall reasoning is good, though the agentic result is less strong than its coding result, so demanding autonomous workflows should be tested carefully. The broad input support is a useful advantage for client tasks that combine multiple media types.
Use Gemini 3.5 Flash as a versatile volume model, particularly when multimodal inputs or long context are central. Reserve a stronger reasoning model for high-stakes decisions that require deeper multi-step analysis.
Assessed September 23, 2026
Editorial notes
Gemini 3.5 Flash combines strong coding benchmarks with a 1M-token context, image, file, audio, and video input, plus tool support and moderate pricing; its agentic results are less prominent.
The DFO score ranks models on the Artificial Analysis Intelligence Index and is refreshed as new models launch. The write-up and verdict are our own. Feedback?
DFO Verdict
Gemini 3.5 Flash combines strong coding benchmarks with a 1M-token context, image, file, audio, and video input, plus tool support and moderate pricing; its agentic results are less prominent.
Benchmarks
Artificial Analysis data refreshed Oct 12, 2026. Arena ratings from the Oct 2, 2026 text leaderboard, with style control.
How Google: Gemini 3.5 Flash compares
Google: Gemini 3.5 Flash ranks #43 of 436 AI models we track for overall intelligence, #25 of 198 for coding, #53 of 181 for agentic tasks. Its 1M-token context window is larger than 95% of the models we list. At $1.50 per million input tokens it is cheaper than 18% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $1.50 | $0.001500 |
| Output | $9.00 | $0.009000 |
What would Google: Gemini 3.5 Flash cost your business?
Pick the job that looks most like yours, then fine-tune with the sliders. Estimates update live.
A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 698 models → Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save Google: Gemini 3.5 Flash for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout Google: Gemini 3.5 Flash
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..
Frequently asked questions about Google: Gemini 3.5 Flash
How much does Google: Gemini 3.5 Flash cost?
Google: Gemini 3.5 Flash costs $1.50 per million input tokens and $9.00 per million output tokens.
What is the context window of Google: Gemini 3.5 Flash?
Google: Gemini 3.5 Flash has a context window of 1,048,576 tokens (1M).
Is Google: Gemini 3.5 Flash good for coding?
On our coding benchmark index, Google: Gemini 3.5 Flash ranks #25 of 198 models, placing it in the top quartile of the field for code generation and debugging.
What can Google: Gemini 3.5 Flash do?
Google: Gemini 3.5 Flash supports image/vision input, tool use, and function calling.
Who created Google: Gemini 3.5 Flash?
Google: Gemini 3.5 Flash is developed by Google and was released on May 19, 2026.