GPT-5.3-Codex vs Hy4 preview: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of GPT-5.3-Codex and Hy4 preview — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
GPT-5.3-Codex
OpenAI
Agentic coding model combining Codex and GPT‑5 training for faster, reasoning-rich code generation and interactive developer collaboration.
Key features
- Agentic Workflow: Acts as a steerable coding agent that performs multi-step tasks, provides frequent progress updates, and accepts real-time guidance while executing long-horizon engineering workflows.
- Frontier Code & Reasoning: Combines Codex and GPT‑5 training stacks to deliver best-in-class code generation with stronger general reasoning and professional knowledge for complex problem solving.
- Faster Generation for Codex Users: Optimized runtime that is ~25% faster for users of Codex surfaces, reducing iteration time for code authoring and interactive sessions.
- Cross-Surface Availability: Available across Codex app, CLI, IDE extensions, and web (for paid ChatGPT subscribers) enabling consistent workflows in editors, terminals, and the browser.
- Collaboration & Steering: Improved collaboration behaviors that let users steer the agent while it works—supporting conversational correction, test-driven workflows, and iterative design.
- Enhanced Cybersecurity Capabilities: Demonstrates elevated cyber capabilities in internal evaluations (first model to meet multiple high-level thresholds), enabling advanced vulnerability discovery and red-team style assessments under controlled conditions.
- Transition/Access Support: Integrates with existing Codex tools and workflows; API access is planned to roll out after initial ChatGPT-integrated availability, with CLI and app updates to select the model.
- Agentic coding behavior with interactive steering and frequent progress updates
- Frontier code generation and stronger general reasoning (combines Codex + GPT-5 training stacks)
- ~25% faster inference for Codex users compared to GPT-5.2-Codex
- Available across Codex surfaces: Codex app, CLI, IDE extensions, and Codex Cloud/web
- Real-time variant (GPT-5.3-Codex-Spark) offering much faster generation (15x) and up to 128k context (research preview)
- Designed for long-horizon, multi-file development, large-scale code transformations, and collaborative workflows
- Higher assessed cybersecurity capabilities (documented in model/system card; marked as High under Preparedness Framework)
- API access rolling out separately; initial availability requires ChatGPT sign-in (OAuth) on Codex surfaces
Best for
- Long-Horizon Feature Development: Orchestrate multi-file feature builds, writing tests, implementing functionality, and iterating on fixes with the agent autonomously while a developer supervises and guides progress.
- Interactive Pair-Programming: Use the model in IDE extensions or the Codex app as a collaborative partner to draft code, refactor modules, and respond to inline developer feedback in real time.
- Large-Scale Code Transformations: Automate broad codebase changes—migration of APIs, bulk refactors, and modernization tasks—by instructing the agent to propose, test, and apply transformations.
- Test-Driven Development Assist: Drive red/green TDD workflows where the agent prefers creating failing tests first, then implementing and refining code until tests pass, accelerating reliable feature delivery.
- Automated Code Review & QA: Generate detailed code reviews, identify potential bugs, and suggest fixes or security hardenings across repositories to streamline review cycles.
- Security Assessment (Controlled): Run cyber-range style scenarios and vulnerability discovery assessments for defensive research and hardening within responsible use constraints and governance.
- End-to-end software development and multi-file code transforms
- Pair-programming and interactive coding assistants inside IDEs
- Automated code review and refactoring at scale
- Building and steering long-horizon engineering workflows and agents
- Security auditing, vulnerability discovery assistance, and cybersecurity exercises
- CI/tooling automation where an agent maintains and updates codebases
Hy4 preview
Tencent
Tencent's open-weight Hy4 preview, a 770B-parameter Mixture-of-Experts model with 49B active parameters and a 1M-token context window.
Key features
- 770B Mixture-of-Experts Architecture: Holds 770 billion total parameters while activating only 49 billion per token, so capacity scales without proportional inference cost.
- 1M-Token Context Window: Accepts inputs exceeding one million tokens, allowing whole codebases, long document sets or extended agent traces in a single prompt.
- Apache 2.0 Open Weights: Released under a permissive licence that allows commercial use, modification and redistribution with no separate agreement.
- Productivity Task Focus: Tuned for real-world coding, office work and scientific research rather than narrow benchmark optimisation.
- Multi-Product Availability: Accessible globally through Tencent's WorkBuddy, CodeBuddy, Yuanbao and ima applications in addition to the raw weights.
- API Access via TokenHub and OpenRouter: Can be called through Tencent Cloud TokenHub or OpenRouter for teams that prefer hosted inference over self-hosting.
Best for
- Whole-Repository Code Work: Load an entire codebase into the million-token context to reason about refactors and cross-file dependencies at once.
- Long-Horizon Agent Tasks: Drive multi-step agent workflows where the full history of tool calls and intermediate results must stay in context.
- Self-Hosted Deployment: Run a frontier-scale open-weight model on private infrastructure where data cannot leave the organisation.
- Scientific Literature Analysis: Ingest large collections of papers or experimental logs and synthesise findings without chunking the input.
- Office Document Processing: Summarise, draft and restructure long reports, contracts and spreadsheets in enterprise workflows.
- Commercial Fine-Tuning: Adapt the weights for a proprietary product under the Apache 2.0 licence without negotiating a model licence.