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Build with GPT-5.5 freeGPT-5.5 vs Gemini 3.1 Pro for Image Generation
Which AI model is better for image generation? We compare GPT-5.5 and Gemini 3.1 Pro on the criteria that matter most - with a clear verdict.
Why your image generation LLM choice matters
Image generation models are evaluated on fundamentally different criteria from text LLMs - prompt adherence, compositional accuracy, visual quality, and style range matter more than reasoning or context window. The best image models produce assets that look like intentional creative work, not AI artifacts, and handle complex multi-element compositions without breaking down.
Key evaluation criteria for image generation
Side-by-Side Comparison
| Feature | GPT-5.5 | Gemini 3.1 Pro |
|---|---|---|
| Provider | OpenAI | |
| Model Type | text | text |
| Context Window | 1,000,000 tokens | 1,048,576 tokens |
| Input Cost | $5.00/ 1M tokens | $4.00/ 1M tokens |
| Output Cost | $30.00/ 1M tokens | $18.00/ 1M tokens |
| Top pick for Image Generation | Tied | Tied |
Strengths for Image Generation
GPT-5.5
OpenAI1. Strongest Agentic Coding Model
- State-of-the-art on Terminal-Bench 2.0 (82.7%), Expert-SWE (73.1%), and SWE-Bench Pro (58.6%), outperforming GPT-5.4 on complex coding tasks.
- Holds context across large systems, reasons through ambiguous failures, and carries changes through surrounding codebases with fewer tokens.
2. Higher Intelligence at GPT-5.4 Latency
- Co-designed, trained, and served on NVIDIA GB200/GB300 NVL72 systems to match GPT-5.4 per-token latency while performing at a significantly higher level.
- Uses fewer tokens to complete the same tasks, making it more efficient as well as more capable.
3. Powerful for Knowledge Work & Computer Use
- Scores 84.9% on GDPval (44 occupations) and 78.7% on OSWorld-Verified for autonomous computer operation.
- Excels at generating documents, spreadsheets, and reports; naturally moves across finding information, using tools, and checking output.
4. Scientific Research Co-Scientist
- Leading performance on GeneBench, BixBench, and FrontierMath; helped discover a new proof about Ramsey numbers verified in Lean.
- Strong enough to meaningfully accelerate progress at the frontiers of biomedical and mathematical research.
Gemini 3.1 Pro
Google1. Google's most advanced reasoning Gemini model
- Designed to solve complex problems across multimodal inputs, including text, audio, images, video, PDFs, and full code repositories.
- Google highlights improved software engineering behavior, better agentic performance, and stronger usability in domains like finance and spreadsheets.
2. Large multimodal context with substantial output room
- Supports a 1,048,576 token input context window for large repositories, long documents, and multi-source workflows.
- Allows up to 65,536 output tokens for longer answers, plans, and code generations.
3. More efficient thinking with expanded controls
- Improves token efficiency and reasoning performance across use cases.
- Adds the
MEDIUMthinking_leveloption to better balance cost, speed, and quality.
4. Strong support for production agents
- Supports grounding with Google Search, code execution, function calling, structured outputs, context caching, RAG, and chat completions.
- Also offers a custom-tools endpoint tuned for agentic workflows that mix bash-like tools with custom code tools.
Stop comparing. Start building your image generation tool.
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Build a image generation app - freeFrequently asked questions
Is GPT-5.5 or Gemini 3.1 Pro better for image generation?
Both GPT-5.5 and Gemini 3.1 Pro are capable of image generation tasks. The best choice depends on your specific priorities: prompt adherence and compositional accuracy and visual quality and aesthetic consistency.
What are the key differences between GPT-5.5 and Gemini 3.1 Pro for image generation?
The main differences are in prompt adherence and compositional accuracy, visual quality and aesthetic consistency, style range - photorealistic to illustrated. GPT-5.5 is developed by OpenAI and comes from a different provider than Gemini 3.1 Pro. Context window, pricing, and speed all differ - check the comparison table above for a side-by-side breakdown.
How much does it cost to use GPT-5.5 vs Gemini 3.1 Pro?
Gemini 3.1 Pro is cheaper at $4.00/million input tokens, versus $5.00/million for GPT-5.5. For image generation workloads, the total cost difference depends on your average prompt length and volume.
Can I build a image generation app with GPT-5.5 or Gemini 3.1 Pro?
Yes. Both models can power image generation applications. With Appaca, you can build a image generation app using either GPT-5.5 or Gemini 3.1 Pro - and switch between them at any time to find the model that performs best for your specific workflow, without rebuilding your product.
Which model should I choose if I care most about prompt adherence and compositional accuracy?
Both models handle prompt adherence and compositional accuracy competently. Test both with your actual content and compare outputs directly - benchmark results don't always translate to your specific workflow.