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

2026-05-19 · Source: Simon Willison's Weblog · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Emerging Technologies & Innovation · Depth: Intermediate, quick

Summary

Google launched Gemini 3.5 Flash on May 19, 2026, making it generally available without a preview phase. This model, identified as "gemini-3.5-flash", is being integrated across numerous Google products, including the Gemini app, Google Search, Google Antigravity, and Gemini Enterprise. It features a January 2025 knowledge cut-off and supports 1,048,576 input tokens and 65,536 maximum output tokens. A new Interactions API, currently in beta, also accompanies the release, offering server-side history management. Notably, Gemini 3.5 Flash comes with a significant price increase, costing \$1.50 per million input tokens and \$9 per million output tokens, which is 3x the price of Gemini 3 Flash Preview and 6x that of Gemini 3.1 Flash-Lite. This pricing positions it close to Gemini 3.1 Pro and reflects a broader industry trend of rising LLM costs, as evidenced by benchmark costs like \$1,551.60 for Gemini 3.5 Flash (high) compared to \$892.28 for Gemini 3.1 Pro Preview.

Key takeaway

For AI Engineers and Directors of AI/ML evaluating LLM deployments, be aware that Gemini 3.5 Flash represents a significant price increase over previous Flash models, costing \$1.50/million input and \$9/million output tokens. This trend, mirrored by other vendors, suggests a new pricing floor for advanced models. You should re-evaluate your cost models and consider benchmark data, like Artificial Analysis's \$1,551.60 for 3.5 Flash, to accurately forecast operational expenses and optimize your LLM strategy.

Key insights

Gemini 3.5 Flash signals a new phase of higher LLM pricing and broad internal deployment across Google's ecosystem.

Principles

• LLM API costs are increasing across major providers.
• Internal product integration often precedes wider API rollout.
• Benchmark costs reveal true operational expense.

In practice

• Use benchmark data for LLM cost comparisons.
• Assess new LLM versions for price-performance.
• Track API pricing trends for budget planning.

Topics

• Gemini 3.5 Flash
• LLM Pricing
• Google AI
• API Costs
• Benchmark Data
• Interactions API

Best for: CTO, VP of Engineering/Data, Entrepreneur, AI Engineer, Director of AI/ML, AI Product Manager

Related on AIssential

• Google’s cheapest AI model just got 3x more expensive — AI inference costs are rising for high-volume, economical models, challenging prior industry expectations.
• Google's Gemini 3.5 Flash follows Anthropic and OpenAI in making newer AI models significantly pricier — Newer, more capable AI models like Gemini 3.5 Flash are significantly pricier due to increased token consumption for complex agentic tasks.
• Gemini 3.5 FLASH: BAD to OUTSTANDING — Gemini 3.5 Flash offers significant cost savings but exhibits high solution variance and requires iterative prompting for complex tasks.
• Gemini 3.1 Flash-Lite: Built for intelligence at scale — Gemini 3.1 Flashlight offers high-quality AI at significantly reduced cost and increased speed for high-volume workloads.
• How Much Does It Actually Cost to Run a Local LLM? (€ per Million Tokens, Measured) — Local LLM energy costs vary significantly by model size and architecture, with larger models potentially exceeding cloud API costs.
• llm-gemini 0.32 — The llm-gemini 0.32 plugin now supports Google's gemini-3.5-flash model for faster LLM access.

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Editorial summary, takeaway, and curation by AIssential. Original article published by Simon Willison's Weblog.