Compare Gemini 3.1 Pro vs. GPT‑5.3‑Codex‑Spark

GPT‑5.3‑Codex‑Spark

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What is Gemini 3.1 Pro?

Gemini 3.1 Pro is Google’s most powerful multimodal AI model to date, engineered to help developers transform ambitious ideas into intelligent, real-world applications. It sets a new benchmark in reasoning, code generation, and multimodal comprehension, outperforming earlier iterations in both speed and depth of capability. Built with advanced long-context processing, the model maintains awareness across extensive codebases and documents, making it highly effective for complex development tasks. Its agentic workflow capabilities allow it to autonomously write, debug, optimize, and refactor code across entire projects with minimal supervision. Beyond text-based intelligence, Gemini 3.1 Pro excels in interpreting images, video, and spatial data, unlocking innovative possibilities in robotics, XR environments, and interactive computing. The model can analyze documents, generate structured outputs, and connect insights across multiple input formats seamlessly. Developers can integrate Gemini 3.1 Pro through the Gemini API, Google AI Studio, or Vertex AI, ensuring compatibility with enterprise-grade infrastructure. Its flexible deployment options make it suitable for startups, research teams, and large-scale production systems alike. By combining coding expertise with visual and contextual understanding, the model supports truly multimodal application development. From building autonomous agents to creating immersive interactive apps from a single prompt, it accelerates innovation across industries. The architecture is optimized for precision, efficiency, and scalable performance in demanding workflows. As a next-generation AI foundation, Gemini 3.1 Pro represents a significant leap toward intelligent systems capable of reasoning, creating, and operating across diverse digital environments.

What is GPT‑5.3‑Codex‑Spark?

GPT-5.3-Codex-Spark is a specialized, ultra-fast coding model designed to enable real-time collaboration within the Codex platform. As a streamlined variant of GPT-5.3-Codex, it prioritizes latency-sensitive workflows where immediate responsiveness is critical. When deployed on Cerebras’ Wafer Scale Engine 3 hardware, Codex-Spark delivers more than 1000 tokens per second, dramatically accelerating interactive development sessions. The model supports a 128k context window, allowing developers to maintain broad project awareness while iterating quickly. It is optimized for making minimal, precise edits and refining logic or interfaces without automatically executing additional steps unless instructed. OpenAI implemented extensive infrastructure upgrades—including persistent WebSocket connections and inference stack rewrites—to reduce time-to-first-token by 50% and cut client-server overhead by up to 80%. On software engineering benchmarks such as SWE-Bench Pro and Terminal-Bench 2.0, Codex-Spark demonstrates strong capability while completing tasks in a fraction of the time required by larger models. During the research preview, usage is governed by separate rate limits and may be queued during peak demand. Codex-Spark is available to ChatGPT Pro users through the Codex app, CLI, and VS Code extension, with API access for select design partners. The model incorporates the same safety and preparedness evaluations as OpenAI’s mainline systems. This release signals a shift toward dual-mode coding systems that combine rapid interactive loops with delegated long-running tasks. By tightening the iteration cycle between idea and execution, GPT-5.3-Codex-Spark expands what developers can build in real time.