Gemini 3.6 Flash Announced: Key Points for Individual Developers
## Gemini 3.6 Flash has been announced
As someone who develops and publishes AI and PC-related tools and apps on my own, this was news I couldn't ignore.
So, I decided to organize the key points for myself.
This time, three new models have been added to the Flash series.
## Three models added to the Flash series
First, the centerpiece is "Gemini 3.6 Flash".
It is a balanced model offering high speed, low cost, and high accuracy, with a major highlight being a 65% reduction in output token costs.
It is also said that accuracy in coding, search, and multimodal tasks has been enhanced.
For individual developers who use APIs daily, I think the impact on costs is the most significant point of interest.
Next, "Gemini 3.5 Flash-Lite" is a model that pursues being lightweight, fast, and cheap above all else.
It features high-speed generation of 350 tokens per second and is designed to be easily integrated into smartphone apps and search-related features.
The final one, "Gemini 3.5 Flash Cyber," is a security-specialized model.
It is intended for tasks like vulnerability detection and appears to be positioned for governments and specific enterprises.
It seems unlikely that a solo developer like myself would use this on a regular basis.
Even so, the fact that Google has released a security-focused model feels like proof that the use cases for AI are expanding.
## Context up to 1 million tokens
The ability to process long texts and massive amounts of data at once is Gemini's strength.
This scale of context is becoming important for building AI agents.
I think this is a particularly compelling point for those considering ways to have the AI read and process large volumes of logs or documents in their entirety.
Furthermore, Google has declared that they have 'begun their most ambitious pre-training,' announcing that development of Gemini 4 has officially started.
It feels like the AI race has entered its next phase.
## Organizing the differences between Claude, Codex, and Gemini
From here, as someone who usually uses AI in a Windows environment, I will organize the 'personality differences' of these three models (lineages).
First, Claude (Anthropic) is the ethical and intelligent advisor type.
It excels at long texts, reasoning, and analysis, produces high-quality writing, and is top-class in terms of safety and ethics.
Another feature is that the conversation is natural and human-like.
It is strong at coding, but it is built to be somewhat cautious.
It is well-suited for text generation, research and analysis, brainstorming, and summarizing or structuring long documents.
I usually use Claude (Claude Code) as my main tool, and this "cautiousness" is something I actually feel when using it.
Because it carefully confirms instructions, my impression is that it is not the type to just charge ahead with pure momentum.
Next, Codex (OpenAI) is a craftsman type specialized for programmers.
It serves as the foundation for GitHub Copilot and has a stronger focus on code comprehension than natural language understanding.
Currently, it is in the process of being integrated into the GPT-4 series Code Interpreter.
It is suitable for coding, understanding API specifications, program debugging, and generating automation scripts.
And Gemini (Google) is a multimodal, all-purpose engine.
Its strength lies in its ability to handle images, video, audio, code, and text simultaneously.
The distinction is that Flash is light, fast, and cheap, while Pro is high-performance.
It also has a wealth of features for building agents, such as a large context window, integration with Google Search, and Computer Use.
It is well-suited for multimodal processing, large-scale data analysis, AI agent construction, low-cost high-speed generation, and integration with Google services.
In a nutshell, Claude is the "pro of thinking and writing," Codex is the "code craftsman," and Gemini is the "multimodal all-rounder."
## Choosing by Purpose
If you are wondering "which one should I use," I think choosing based on your purpose is the simplest approach.
- Want to improve the quality of writing and thinking → Claude
- Want to write code extensively → Codex series
- Want to build AI agents or automation → Gemini Flash
- Want to handle images, video, and audio as well → Gemini
I personally use Claude (Claude Code) as my main tool, while trying out other models as needed.
Using different models depending on the use case seems to be the fundamental stance for AI utilization moving forward.
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I plan to share details about Gemini 3.6 Flash and the differences between the three model families on X as I discover things while developing. I will be sharing my impressions from actually trying it out, as well as potential pitfalls when implementing the API, so please take a look if you are interested. https://x.com/aishiroto