Claude 4.5 vs Hy4 preview: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Claude 4.5 and Hy4 preview — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Claude 4.5
Anthropic
Hybrid reasoning model optimized for coding, building complex agents, and interacting with computers, with a 200K token context window.
Key features
- Large Context Window: Supports a 200K token context window enabling long-form reasoning, multi-file codebases, and extended agent histories for complex workflows.
- Best-in-Class Coding: Verified state-of-the-art performance on coding benchmarks (SWE-bench) with improvements across planning, system design, code organization, and secure coding practices.
- Agent SDK and Agentic Capabilities: Provides a Claude Agent SDK and infrastructure to build complex, multi-step autonomous agents that coordinate tools and workflows reliably.
- Robust Tool & Computer Use: Enhanced tool-call reliability including a bug fix that preserves trailing newlines in string parameters and defenses against prompt injection attacks when interacting with external tools and systems.
- Safety and Alignment Improvements: Extensive safety training to reduce concerning behaviors (sycophancy, deception, power-seeking) and improved adherence to instructions and policy constraints.
- Multi-Platform Availability: Available through Claude.ai, Claude Code, Anthropic API, Amazon Bedrock, Google Cloud Vertex AI, and partner integrations such as GitHub Copilot for developer tooling.
- 200K-token context window for long-form reasoning and multi-step workflows
- State-of-the-art coding performance (SWE-bench verified)
- Optimized for building complex agents and orchestration
- Improved planning, system design, and instruction following
- Enhanced security engineering and vulnerability detection capabilities
- Defenses against prompt injection attacks and improved alignment
- Preserves trailing newlines in tool call string parameters (bug fix)
- Available via Anthropic API, Claude.ai, Claude Code, Amazon Bedrock, and Google Cloud Vertex AI
- Claude Agent SDK: developer tooling and building blocks for agent infrastructure
- Integration/availability in GitHub Copilot (select plans)
Best for
- End-to-End Software Development: Generate, refactor, and architect multi-file projects, leveraging 200K context for design documents, large codebases, and long-running code edits.
- Agent-Driven Automation: Build autonomous agents that orchestrate tools, APIs, and human-in-the-loop steps for tasks like automated incident response, orchestration, or workflow automation using the Claude Agent SDK.
- Security Engineering and Red Teaming: Automate vulnerability discovery, triage, and exploit scenario generation; demonstrated high success rates on benchmarks like Cybench and CyberGym for security tasks.
- Code Modernization and Migration: Translate legacy systems to modern languages, reorganize projects, and propose architectural improvements with detailed planning and system-design outputs.
- Developer Tooling Integration: Power interactive coding assistants in IDEs and services (e.g., GitHub Copilot, Claude Code) for chat, edit, and agent modes with faster, accurate responses.
- Regulated Enterprise Solutions: Deploy in regulated industries (through partnerships and enterprise plans) for customer support, financial services, and government use cases with compliance and safety controls.
- End-to-end software development: code generation, refactoring, code reviews, and architectural planning
- Building and orchestrating complex autonomous agents and agentic workflows
- Security: vulnerability discovery, red teaming, and automated security engineering assistance
- Tool use and automation: driving external tools, editors, and system operations with precise parameter handling
- Customer support and knowledge-base automation requiring long context retention
- Education and tutoring for complex multi-step problems and programming instruction
- Enterprise deployments in regulated industries via cloud marketplace integrations
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.