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Lyzr integrates with OpenAI’s most powerful models, offering a spectrum of capabilities from real-time multimodal interaction to complex, deep-thinking reasoning. These models are available to use without any additional configuration.
OpenAI’s latest frontier model featuring a “Unified Thinking” system that automatically routes queries between fast responses and deep reasoning.Use Cases:
  • High-stakes enterprise orchestration
  • Complex multi-step planning and autonomous agents
  • Advanced research and data synthesis
Highlights:
  • Native multimodality (text, vision, and audio trained together)
  • 400K context window with high reliability
  • Adjustable “Reasoning Effort” (Minimal to High)
A refined version of the GPT-5 baseline, optimized for improved conversational tone and enhanced personalization.Use Cases:
  • Personalized AI assistants
  • Dynamic customer experience agents
  • Content creation with specific brand-voice requirements
Highlights:
  • Warmer, more human-like interaction style
  • Improved instruction-following consistency
  • Better performance in creative writing and brainstorming
Scalable variants of the GPT-5 architecture designed for efficiency and edge deployment.Use Cases:
  • Mini: Real-time API calls, lightweight agents, and summarization.
  • Nano: On-device processing, privacy-preserving mobile apps, and instant classification.
Highlights:
  • Maintains the “Unified Thinking” logic at a lower cost
  • Ideal for high-volume, low-latency production environments
  • Minimal token usage for equivalent GPT-5 quality tasks
The flagship of the “o-series,” specifically engineered for tasks requiring intense logic and sequential reasoning.Use Cases:
  • Advanced coding and technical debugging
  • Complex mathematical proofs and scientific analysis
  • Strategic decision-making and policy evaluation
Highlights:
  • Direct “Chain-of-Thought” processing visible to the user
  • High-tier performance on STEM benchmarks (AIME, ARC-AGI)
  • First reasoning model with autonomous tool-use (Search, Python)
A breakthrough small-scale reasoning model that delivers deep analytical capabilities at a fraction of the cost.Use Cases:
  • High-volume reasoning tasks (e.g., analyzing thousands of legal docs)
  • STEM-focused educational tools
  • Cost-effective structured data extraction
Highlights:
  • 20% better performance than o3-mini with 10x lower cost
  • 200K context window for long-context reasoning
  • Native multimodal support within the reasoning chain
An enterprise-optimized flagship model focused on high-throughput, reliability, and precision in instruction following.Use Cases:
  • Real-world software engineering (Excel at code diffs)
  • Extracting insights from 1M+ token documents
  • Predictable, low-latency business workflows
Highlights:
  • Massively expanded 1M token context window
  • Significantly better at “Format Following” (JSON, XML, YAML)
  • Half the latency of GPT-4o for complex tasks
A versatile, multimodal model designed for natural, real-time human-computer interaction.Use Cases:
  • Real-time voice translation and customer support
  • Interactive video analysis and vision-based troubleshooting
  • Multimodal RAG applications
Highlights:
  • Sub-320ms latency for audio/visual inputs
  • “Omni” architecture (handles text, audio, and images natively)
  • Balanced performance across 50+ languages
The most cost-efficient and fastest small model in the GPT-4o family.Use Cases:
  • Lightweight chatbots and simple Q&A
  • Basic sentiment analysis and text classification
  • Rapid prototyping of AI-powered features
Highlights:
  • Over 60% cheaper than GPT-3.5 Turbo
  • Faster than its larger counterpart for text-only tasks
  • Supports the same 128K context window as the flagship
💡 Recommendation: Use GPT-5 for complex autonomous agents, o3/o4-mini for heavy logic or math, and GPT-4.1 for long-document analysis and coding tasks.