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GPT-5.4 vs Gemini 3.1 Pro

Compare GPT-5.4 and Gemini 3.1 Pro. Build AI products powered by either model on Appaca.

Model Comparison

Feature	GPT-5.4	Gemini 3.1 Pro
Provider	OpenAI	Google
Model Type	text	text
Context Window	1,050,000 tokens	1,048,576 tokens
Input Cost	$2.50/ 1M tokens	$4.00/ 1M tokens
Output Cost	$15.00/ 1M tokens	$18.00/ 1M tokens

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Strengths & Best Use Cases

GPT-5.4

OpenAI

1. Best Intelligence at Scale

OpenAI positions GPT-5.4 as its frontier model for agentic, coding, and professional workflows.
Built for complex professional work where stronger reasoning and higher answer quality matter.

2. Configurable Reasoning + Multimodal Input

Supports configurable reasoning effort from none to xhigh, letting teams balance speed and depth.
Accepts both text and image inputs while producing text output.

3. Massive Context for Long-Running Work

1.05M token context window supports very large codebases, documents, and multi-step workflows.
Allows up to 128 k output tokens for long-form answers and larger generations.

4. Updated Knowledge & Broad Tool Support

Knowledge cut-off of Aug 31 2025 keeps it current for newer frameworks and business context.
Supports tools like web search, file search, code interpreter, hosted shell, computer use, and MCP in the Responses API.

Gemini 3.1 Pro

Google

1. 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 MEDIUM thinking_level option 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.