Gemini 3.5 Flash: more expensive, but Google plan to use it for everything

19th May 2026
Today at Google I/O, Google released Gemini 3.5 Flash. This one skipped the -preview
modifier and went straight to general availability, and Google appear to be using it for a whole lot of their key products:
3.5 Flash is available today to billions of people globally:
- For everyone via the Gemini app and AI Mode in Google Search
- For developers in our agent-first development platform Google Antigravity and Gemini API in Google AI Studio and Android Studio
- For enterprises in Gemini Enterprise Agent Platform and Gemini Enterprise.
As usual with Gemini, the most interesting details are tucked away in the What’s new in Gemini 3.5 Flash developer documentation. It mostly has the same set of platform features as the previous Gemini 3.x series, albeit with no computer use. The model ID is gemini-3.5-flash
. The knowledge cut-off is January 2025, and it supports 1,048,576 input tokens and 65,536 maximum output tokens.
Google are also pushing a new Interactions API, currently in beta, which looks to me like their version of the patterns introduced by OpenAI Responses—in particular server-side history management.
The price has gone up
Gemini 3.5 Flash is accompanied by a notable price bump. The previous models in the “Flash” family were Gemini 3 Flash Preview and Gemini 3.1 Flash-Lite. The new 3.5 Flash is 3x the price of 3 Flash Preview and 6x the price of 3.1 Flash-Lite (see price comparison here).
At $1.50/million input and $9/million output it’s getting close in price to Google’s Gemini 3.1 Pro, which is $2 and $12.
The Gemini team promise that 3.5 Pro will roll out “next month”—presumably at an even higher price.
This fits a trend: OpenAI’s GPT-5.5 was 2x the price of GPT-5.4, and Claude Opus 4.7 is around 1.46x the price of 4.6 when you take the new tokenizer into account.
Given the price increase it’s interesting to see Google roll it out for so many of their own free-to-consumer products. It feels like all three of the major AI labs are starting to probe the price tolerance of their API customers.
Artificial Analysis publish the cost to run their proprietary benchmark against models, which is a useful way to take things like tokenization and increased volume of reasoning tokens into account. Some numbers worth comparing:
- Gemini 3.5 Flash (high): $1,551.60
- Gemini 3.1 Pro Preview: $892.28
- Gemini 3 Flash Preview (Reasoning): $278.26
- Gemini 3.1 Flash-Lite Preview: $93.60
Running the benchmark for 3.5 Flash (high) cost significantly more than 3.1 Pro Preview!
Here are some numbers from other vendors:
- Claude Opus 4.7 (Adaptive Reasoning, Max Effort): $5,117.14
- Claude Opus 4.7 (Non-reasoning, High Effort): $1,217.23
- GPT-5.5 (xhigh): $3,357.00
- GPT-5.5 (medium): $1,199.14
A pelican on a bicycle
I ran “Generate an SVG of a pelican riding a bicycle” against the Gemini API and got back this pelican, which is a lot:
From the code comments:
That pelican looks like it’s in Miami for a crypto conference.
That one cost me 11 input tokens and 14,403 output tokens, for a total cost of just under 13 cents.
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Facts Only

Gemini 3.5 Flash is generally available today.
It is accessible via the Gemini app and AI Mode in Google Search.
Developers can access it via Google Antigravity and the Gemini API in Google AI Studio and Android Studio.
Enterprises can use it through the Gemini Enterprise Agent Platform and Gemini Enterprise.
The model ID is gemini-3.5-flash.
The knowledge cut-off is January 2025.
It supports 1,048,576 input tokens and 65,536 maximum output tokens.
The price is $1.50/million input and $9/million output.
Gemini 3.5 Flash is 3x the price of Gemini 3 Flash Preview and 6x the price of Gemini 3.1 Flash-Lite.
Benchmarking costs for Gemini 3.5 Flash (high) are $1,551.60.
Claude Opus 4.7 (Adaptive Reasoning, Max Effort) cost is $5,117.14.
GPT-5.5 (xhigh) cost is $3,357.00.

Executive Summary

Google released Gemini 3.5 Flash, making it generally available to billions globally through various products including the Gemini app and Google Search. The model supports 1,048,576 input tokens and 65,536 maximum output tokens, with a knowledge cut-off of January 2025. The model is integrated across Google platforms, including developer tools like Google Antigravity and the Gemini API. A new Interactions API is also being pushed in beta, focusing on server-side history management. The model introduced a significant price increase compared to previous "Flash" models, costing $1.50 per million input and $9 per million output. This pricing places it near the cost of Gemini 3.1 Pro, and the pricing trend aligns with recent increases observed among competitors like OpenAI and Claude.

Full Take

The narrative centers on a price hike for a widely deployed, free-to-consumer product, which serves as a signal in the competitive AI market. The increase positions Gemini 3.5 Flash competitively against higher-tier models like Gemini 3.1 Pro and directly against rivals such as GPT-5.5 and Claude Opus 4.7. This pattern suggests that the cost of advanced reasoning capabilities is being rapidly commoditized and monetized across the industry, rather than remaining siloed within proprietary systems. The benchmarking data indicates that running high-capability models carries substantial computational costs, and the move to triple the price for Flash models suggests a strategy to capture value from mass-market usage while maintaining premium pricing for enterprise offerings. The implication is that cost tolerance for API customers is being heavily tested, pushing major AI labs toward a more aggressive monetization strategy for their foundational models. The observation that all major labs are simultaneously probing price tolerance suggests a systemic shift where competitive advantage is increasingly defined not just by model capability, but by the cost-efficiency of deployment and the perceived value proposition of tiered access.

Sentinel — Human

Confidence

The text exhibits the flow and idiosyncratic voice of human commentary, blending hard data with subjective observations about market trends.

Signals Detected

Sentence length variance is erratic; voice shifts between descriptive reporting and casual observation.

Presence of idiosyncratic emphasis and conversational interjections ('looks to me like their version'), suggesting a human author's voice.

The flow smoothly transitions from product announcement to pricing comparison to market trend, demonstrating a logical narrative construction.

The inclusion of a highly specific, contextual anecdote (the SVG generation cost) that breaks the purely technical tone and adds an element of personal experience.

Human Indicators

The integration of casual, subjective phrasing and the inclusion of a non-essential, illustrative anecdote suggest a human writer shaping the core information.

The narrative structure focuses on synthesizing market trends (pricing, competition) rather than merely reciting press releases.