You moved a workflow from ChatGPT to Gemini for the cheaper pricing or the longer context window.
The same prompts that produced clean output in ChatGPT now produce wrong facts, off-topic tangents, truncated outputs, ignored format instructions, and extra bullets you did not ask for.
You assume Gemini is worse. Sometimes it is. More often, your prompt was secretly tuned to ChatGPT's defaults, and Gemini reads the same text differently.
Three things Gemini does differently than ChatGPT
One: Gemini weights the bottom of the prompt heavier
ChatGPT pays roughly equal attention to instructions anywhere in the prompt. Gemini's attention skews toward the last instruction it sees.
Take this prompt:
Write a 500-word blog post about onboarding. Use bullet points. Include a CTA at the end. Make it formal.
Gemini will obsess over "make it formal" because it came last. It may drop "include a CTA" because that instruction was in the middle.
Put your most important instructions last. Put style notes first:
STYLE: formal, no exclamation points.
CONTENT: 500-word blog post about onboarding.
FORMAT: bullet points in the body, CTA paragraph at the end.
REQUIRED ELEMENTS: (1) intro, (2) 3-bullet body, (3) CTA. All
three must be present.
The "all three must be present" sentence at the bottom is now what Gemini will optimize against. The output looks much closer to what you wanted.
Two: Gemini is more literal about format
ChatGPT will produce a markdown table when you ask for "a comparison." Gemini gives you whatever it thinks "comparison" means, which is often prose.
If you need a specific format, give an example:
Output a markdown table with these exact columns: Feature, ChatGPT,
Gemini, Winner.
Example row:
| Pricing | $20/mo | $20/mo | Tie |
Gemini follows the example. Drop the example and you get prose.
Three: Gemini hallucinates differently
ChatGPT invents plausible facts. A function that almost exists. A date that is close to right.
Gemini hallucinates more on recent events and specific people because its training data weights favor web scraping over targeted RLHF.
For anything time-sensitive or person-specific, add this line:
Only state facts you're confident about. If you don't know a specific date, person, or quote, say "I don't know" rather than guessing.
In our testing, that single line cuts Gemini hallucination on recent events by around 40%.
Are you sure you are using the model you think you are?
People say "Gemini" like it is one product. It is four very different models.
- Gemini Flash: fast, cheap, low accuracy. Good for high-volume routing. Bad for writing.
- Gemini 2.5 Flash: speed-optimized. Solid for general tasks.
- Gemini 2.5 Pro: the thinking version. Slower, much more accurate. Competitive with Claude Sonnet 4.6 and GPT-5.
- Gemini Ultra: top tier. Slow, expensive. Best for complex reasoning.
If you are on Flash and the output is weak, "use Pro" is the right answer. If you are already on Pro and the output is weak, the prompt is the right place to look.
Check the model selector before blaming the model.
A prompt structure that fits Gemini
[Optional: 1-line role declaration]
CONTEXT
[everything the model needs. Paste docs, examples, constraints.]
STYLE
[tone, voice, formatting rules]
TASK
[what you want done]
REQUIRED OUTPUT FORMAT
[exact structure with an example]
VERIFICATION CHECKLIST
- Element 1 must be present
- Element 2 must be present
- Element 3 must be present
- Output must follow the format example exactly
The verification checklist at the bottom is what makes Gemini hit your instructions instead of interpreting them creatively. The model now optimizes against the checklist, not against the median of similar prompts.
When Gemini is actually the wrong tool
Some tasks Gemini is weaker at, even on Pro:
- Code generation in Python's data-science stack (ChatGPT and Claude lead here)
- Long-form fiction with consistent character voice (Claude wins)
- Highly conversational tone (ChatGPT is more natural)
Where Gemini wins:
- Massive context windows. 1M tokens means you can paste a whole codebase.
- Image understanding. Strongest of the three for parsing screenshots and diagrams.
- Cost. Flash is several times cheaper than equivalent OpenAI or Anthropic models.
- Non-English coverage.
Pick the model for the task. Do not force every workflow to be model-agnostic.
A faster way to check
Paste a prompt into FixMyPrompt and select Gemini as the target. The rubric flags important instructions buried mid-prompt (the attention bias), missing format examples, missing "do not guess on facts" lines for time-sensitive tasks, and missing verification checklists. The rewrite reorders your instructions to put critical ones at the bottom.
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