Chrome ExtensionGemini Prompt Generator
Updated for Gemini 4 Argon (GA October 2026), Google's most powerful model, and Gemini 3.8 Flash, the fast everyday workhorse. Generate prompts built the way current Gemini models actually want them: concise and direct, structured with Markdown or XML, constraints first, output format explicit — and free of the forced chain-of-thought and self-critique scaffolding that a reasoning model now over-analyses.
Be specific about what you want the AI to do
Generated Prompt
Fill in the form and click "Generate" to create an optimized Gemini 4 Argon & 3.8 Flash prompt.
Tip: The more specific your task description and context, the better the generated prompt will perform.
Gemini 4 Argon & 3.8 Flash Tips
- • Be CONCISE — Gemini 3.x is a reasoning model and over-analyses verbose, over-engineered prompts
- • Skip persuasive filler ("please", "if you don't mind", "this is very important") and redundant restatement
- • Don't write "think step by step" to force reasoning — raise the thinking level and simplify the prompt instead
- • Skip the self-critique ritual too: the model already deliberates internally, so it mostly adds tokens and hedging
- • Use Markdown headings (## Role, ## Task, ## Output Format) OR XML tags — pick one and stay consistent
- • Place role and constraints at the TOP; with long pasted material, put it first and bridge with "Based on the material above…"
- • Gemini defaults to terse output — state the format and the length as a number if you want more
- • Google recommends few-shot examples: two or three with identical formatting beat a long description of the format
- • For time-sensitive or search-grounded questions, put today's date in the prompt so Gemini searches for the current year
- • For Workspace tasks, reference files by name (Gmail thread, @Drive doc, Docs file) so Gemini binds to the right source
Gemini Prompt Templates
Copy-ready starting points for the most common jobs people bring to this model. Swap the [BRACKETED] parts for your own details, or use them as a shape to imitate when you write your own.
Concise Technical Answer
EngineeringShort and direct — the shape current Gemini models reward most.
## Role [ROLE, e.g. Senior platform engineer] ## Task [THE SPECIFIC QUESTION OR TASK] ## Context Stack: [STACK AND VERSIONS]. Scale: [SCALE]. Constraint: [HARD CONSTRAINT]. ## Output Format [FORMAT, e.g. numbered steps with a code block per step]. Maximum [NUMBER] steps.
Long Document Q&A
AnalysisUses the 1M window: material first, question after.
[PASTE THE FULL DOCUMENT, TRANSCRIPT OR CODEBASE HERE] --- Based on the material above, answer: [QUESTION] ## Constraints - Cite the section or line each answer comes from. - If the material does not cover something, say so plainly. ## Output Format [FORMAT, e.g. a table with Question / Answer / Source columns]
Workspace Synthesis
ProductivityBinds Gemini to named files so it synthesises the right sources.
## Task Using the @Drive document "[DOC NAME]" and the Gmail thread with [PERSON/SUBJECT], produce [DELIVERABLE]. ## Context This is for [AUDIENCE] ahead of [EVENT/DEADLINE]. ## Constraints - Pull facts only from the named sources; flag anything you cannot find in them. - Keep names and figures exactly as written in the sources. ## Output Format [FORMAT, e.g. a one-page brief with three H2 sections], under [WORD COUNT] words.
Design Mock to Code
EngineeringPlays to Gemini 3.8 Flash's web-development and spatial reasoning strengths.
## Role Front-end engineer ## Task Build the attached design as a [FRAMEWORK, e.g. React + Tailwind] component. ## Constraints - Match spacing, type scale and colour to the mock; do not improvise a different layout. - Responsive down to [BREAKPOINT]. - Semantic HTML, keyboard accessible, no external UI libraries. - [LIGHT/DARK/BOTH] theme. ## Output Format One self-contained component file in a fenced code block, followed by a short list of any judgement calls you made where the mock was ambiguous.
Multimodal Review
AnalysisNames the uploaded artefacts explicitly so the model binds to them.
## Task Review the [IMAGES / SCREENSHOTS / PDF] I uploaded and identify [WHAT TO FIND]. ## Context These are [WHAT THEY ARE]. The audience is [AUDIENCE] and the purpose is [PURPOSE]. ## Constraints - Reference each finding to the specific file and region it came from. - Rank findings by impact. ## Output Format Numbered list. For each: what you saw, why it matters, what to change.
Structured Data Extraction
DataTerse instruction plus an explicit schema — no scaffolding needed.
## Task
Extract [WHAT] from the content below into JSON.
## Schema
{"[field1]": "string", "[field2]": "number|null", "[field3]": "string[]"}
## Constraints
- JSON only, no commentary.
- null where the source is genuinely silent. Never infer.
## Content
[PASTE CONTENT]Gemini Model & Prompting Update Log
November check-in
● LatestNovember 8, 2026- Gemini 4 Argon and Gemini 3.8 Flash are still Google's newest text models. Argon's introductory API price ($2 / $10 per million tokens) ends November 30; from December 1 it is $4 / $20.
- Argon's 1M-token window is shared by input and output. Output defaults to 64K tokens, and API long decode can stretch one response toward 1M tokens for book-length or whole-codebase outputs. Google recommends the default medium thinking level for most tasks.
- Google's prompting guide now recommends few-shot examples in most prompts (a few, consistently formatted), so the generator has a Few-Shot Examples switch. It also suggests stating today's date for search-grounded questions.
- Gemini 2.5 Pro requests will route to Gemini 3.8 Flash on December 1, 2026, and Gemini 2.5 Flash to 3.5 Flash-Lite. Since November 5 the API also accepts PPT, ODP and ODS files as input.
Gemini 4 Argon GA
October 13, 2026- Gemini 4 Argon (gemini-4-argon) became generally available in the Gemini API and for Google AI Pro and Ultra subscribers in the Gemini app, two weeks after its September 30 announcement.
- It has a 1M-token context window, 64K output by default, low, medium and high thinking levels, and takes text, image, video, audio and PDF input. API pricing is $2 / $10 per million tokens until November 30, then $4 / $20.
- The generator now has a Model switch. Gemini 3.8 Flash stays the default for everyday work, and the same concise, direct prompting rules apply to both.
- Google deprecated gemini-3.7-flash and gemini-3.5-flash on October 8; requests now route to newer Flash models.
October check-in
October 8, 2026- Gemini 3.8 Flash was still Google's newest generally available text model on this date.
- Nano Banana 2.1 (gemini-nano-banana-2.1) went GA on October 6, 2026, replacing Nano Banana 2 for image generation and editing in the Gemini app and API. For image prompts, use our Nano Banana 2.1 Prompt Generator.
- Since September 18, 2026, Gemini 2.5 models are only available to projects that used them recently. Google points new projects to Gemini 3.8 Flash or 3.5 Flash-Lite.
- Gemini 3.8 Flash TTS and 3.8 Flash-Lite TTS reached GA on September 22 with voice design and voice replication.
Gemini 3.8 Flash
September 2, 2026- Generally available as gemini-3.8-flash, three weeks after Gemini 3.7 Flash. Google calls it its most intelligent workhorse model.
- Aimed at long-horizon software engineering, autonomous agents and complex enterprise workflows, with gains over 3.7 Flash in coding, agentic tasks and multi-step reasoning.
- Same 1M-token context window and 64K-token output limit.
- Same introductory price: $0.75 per million input tokens and $3.75 per million output through December 31, 2026, then $1.50 and $7.50 from January 1, 2027.
- Thinking level is low, medium (default) or high. Requesting minimal returns an error. Remove temperature, top_p, top_k and candidate_count; thinking_level replaces thinking_budget.
- Also released in September: Gemini 3.8 Live for real-time voice (September 15) and Gemini 3.8 Flash TTS (September 22).
- Gemini 4 is not out yet. On September 24 Google DeepMind said it is in post-training and an early version will ship as soon as possible.
Gemini 3.7 Flash
August 13, 2026- Google's workhorse model for coding and agentic work at the time, released less than a month after Gemini 3.6 Flash.
- Keeps the 1,048,576-token context window and a 64K-token output limit.
- Substantial gains on software engineering and automation — Google-reported DeepSWE v1.1 rose from 49.0% to 65.3% over Gemini 3.6 Flash, with AutomationBench at 30.4%.
- Positioned for software engineering, web development from design mocks, multi-step agentic workflows, and spatial and multimodal reasoning.
- Introductory pricing of $0.75 per million input tokens and $3.75 per million output runs through December 31, 2026, then doubles to $1.50 and $7.50 on January 1, 2027.
How prompting Gemini changed
Gemini 3.x guidance- Gemini 3.x models are REASONING models, and Google's guidance is to be concise and direct — they over-analyse the verbose prompt-engineering scaffolding that helped on older models.
- Reasoning depth moved to a thinking level (low, medium, high) set outside the prompt. Low suits latency-critical work like real-time chat and fast drafts; medium is the default and best for most tasks including complex code and agents; high is for hard maths, difficult coding and the toughest agent runs.
- If you previously used chain-of-thought prompt engineering to force reasoning, note that Google now calls outlining the reasoning in the response generally unnecessary. Use a higher thinking level and keep the prompt simple instead.
- On the API side, temperature, top_p, top_k and candidate_count were dropped, thinking_budget was replaced by the thinking_level enum, and prefilled model turns are no longer supported.
Earlier 2026 releases
June–July 2026- Gemini 3.6 Flash reached GA on July 21, 2026 with improved token efficiency for code and agentic planning, alongside Gemini 3.5 Flash-Lite as a low-latency, high-volume subagent option.
- Gemini Omni Flash entered public preview on June 30, 2026 for video generation and editing.
- Gemini 3.5 Pro, the flagship promised at I/O, remained in limited preview on Vertex AI rather than launching publicly.
How to Use the Prompt Generator
Define Your Task
Select a category and describe what you want Gemini to do. Assign a role, set reasoning depth, and pick your structure format (Markdown or XML). Be direct and precise — Gemini rewards clarity over flowery filler.
Set Structure & Constraints
Add context, choose tone and output format, and set constraints. The generator will use Markdown headings and structured formatting that Gemini interprets best.
Generate & Use
Click "Generate" to get a structured Gemini-optimized prompt. Copy and paste it directly into the Gemini app, AI Studio, or your Workspace tools for dramatically better results.
Frequently Asked Questions
What is a Gemini prompt generator?
A Gemini prompt generator helps you create optimized prompts specifically designed for Google's Gemini models. It structures your inputs following Gemini-specific best practices — concise, direct instructions, structured formatting with Markdown or XML tags, constraint-first placement, and explicit output format — which matters more than ever now that Gemini 3.x models reason internally and penalise padded prompts.
How is prompting Gemini different from ChatGPT?
Gemini favours directness over verbosity and produces terse output by default, so you often have to ask explicitly for detail. It responds best to structured prompts using Markdown headings or XML tags, with constraints at the very top. The bigger difference on Gemini 3.x is that it is a reasoning model that actively over-analyses elaborate prompt scaffolding — the techniques people learned on older models (forced chain-of-thought, self-critique steps, heavy role-play framing) now work against it. Gemini is also unusually strong on multimodal inputs and Google Workspace integration.
When should I split into multiple prompts?
When you have several genuinely distinct deliverables. Gemini works best conversationally with one focused deliverable per turn, so producing them in sequence beats cramming them into a single request. Use this generator for each focused deliverable, then chain them in conversation. Note this is about splitting TASKS, not about fragmenting the context — with a 1M-token window you should paste long source material in full, then ask your question after it.
What is the thinking level and which one should I pick?
Gemini 3.8 Flash and Gemini 4 Argon both let you trade latency against depth with three thinking levels. Low reduces time-to-answer for latency-critical work — real-time chat, incident response, quick drafts, fast data analysis. Medium is the default and gives the best quality for most tasks, including complex code and agentic use, with higher first-pass accuracy. High maximises reasoning and tool use, and is worth it for hard maths, difficult coding and the toughest agent runs. Because depth is set here rather than in the prompt, the prompt itself should stay short and specific. There is no minimal level on 3.8 Flash; the API returns an error if you request it.
What is the current Gemini model?
Google's most powerful model is Gemini 4 Argon (gemini-4-argon), generally available since October 13, 2026 in the Gemini API and for Google AI Pro and Ultra subscribers in the Gemini app. It has a 1M-token context window shared by input and output, 64K output by default (long decode in the API stretches a single response toward 1M tokens), low, medium (default) and high thinking levels, and takes text, image, video, audio and PDF input. API pricing is $2 per million input tokens and $10 per million output until November 30, 2026, then $4 and $20 from December 1. The everyday workhorse is still Gemini 3.8 Flash (GA September 2, 2026), which is faster and cheaper and the right pick for most prompts.
Should I use Gemini 4 Argon or Gemini 3.8 Flash?
Start with 3.8 Flash for everyday writing, coding and agent work: it is fast and well under half of Argon's price (about a fifth once Argon's introductory pricing ends on November 30). Switch to Argon for the hardest reasoning, long multi-file code changes and analysis across long video, audio or PDF inputs. Pick the model in the generator and the prompt is tuned for it, but it stays short and direct either way, because both models over-analyse padded prompts.
What's new in Gemini 3.8 Flash?
It arrived three weeks after Gemini 3.7 Flash and keeps the same context window, output limit and introductory price. Google reports gains over 3.7 Flash in software engineering, agentic tasks and multi-step reasoning in specialised domains, including multi-file refactoring and more deterministic tool execution. On the API side, the thinking level is low, medium (default) or high, minimal is not supported, temperature, top_p and top_k should be removed, and thinking_level replaces thinking_budget. The same month Google also shipped Gemini 3.8 Live for real-time voice (September 15) and Gemini 3.8 Flash TTS (September 22). For prompting, the advice stays the same: short, direct prompts with an explicit output format.
Is this tool free to use?
Yes. You get 1 free prompt generation per day with no signup required. For unlimited access, sign up for a Promptslove membership which includes all AI tools and 29,000+ premium prompts.
Can I use these prompts with other AI tools?
While optimized for Gemini, the structured prompting approach works well with Claude, ChatGPT, Grok, MiniMax, Qwen, and most modern LLMs. The Markdown/XML structure and constraint-first pattern are model-agnostic.
What is structured prompting?
Structured prompting uses Markdown headings or XML-style tags to organize different sections of your prompt (identity, constraints, context, output format). This provides unambiguous boundaries that help Gemini distinguish between instructions and data, leading to more accurate and consistent results.
Should I use self-critique directives?
No — this is advice that has aged badly. It helped on older Gemini models, but the current 3.x generation already deliberates internally before answering, so "review your output against the constraints and revise" mostly adds tokens and makes the response more hedged. The same applies to "think step by step" added purely to force reasoning. If a task needs more thought, raise the thinking level and keep the prompt simple. Google says spelling out reasoning in the response is generally unnecessary; for a genuinely heavy problem, one short "think carefully" line is enough.
How many prompts can I generate for free?
You get 1 free prompt generation every 24 hours. This resets automatically. For unlimited generations, consider signing up for a Promptslove membership.
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