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We’ve added powerful models to Chat-O: Grok-Code-Fast-1, Kimi 2, DeepSeek v3.1, and more. What sets us apart isn’t any single model—it’s how multiple models work together in the same chat session. This reduces single-model bias and provides more creative, helpful responses. Since this launch, we’ve continued expanding with models like GPT-5, GPT-OSS-120B, and most recently the Kimi K3 and GLM-5.2.
xAI’s specialized coding model optimized for rapid code generation and debugging. It excels at:
Benchmarks show it competes favorably with dedicated coding models while maintaining xAI’s characteristic directness.
Moonshot AI’s second-generation model brings significant improvements over the original:
Kimi 2 was the foundation for later models like Kimi K2.6 and Kimi K2.7 Code, which pushed multi-agent and coding capabilities further.
The latest from DeepSeek, this 671B MoE model offers:
DeepSeek V3.1 remains a strong budget-friendly option in our lineup, complementing newer reasoning-focused models. In practice, users report it handles complex analytical tasks with surprising depth for its cost, making it a favorite for budget-conscious power users who need reliable reasoning without premium pricing.
We also added Mistral Large 2, a 123B-parameter model excelling at multilingual tasks and nuanced instruction following, and Llama 3.1 405B, Meta’s largest open-weight model with broad general knowledge.
| Model | Best For | Context | Strength |
|---|---|---|---|
| Grok-Code-Fast-1 | Real-time coding | 32K | Speed, directness |
| Kimi 2 | Long docs, bilingual | 128K | Chinese-English, file analysis |
| DeepSeek V3.1 | General reasoning | 64K | Cost efficiency |
| Mistral Large 2 | Multilingual, nuance | 128K | Instruction following |
| Llama 3.1 405B | Broad knowledge | 128K | Open-weight versatility |
Smart Model Selection: Our system suggests the best model for your task, or you can manually switch mid-conversation.
Cross-Model Context: Models can hand off complex problems to specialists better suited for specific tasks.
Quality Optimization: We continuously monitor performance and retire models that don’t meet standards, ensuring access to the best options.
As we add new models like GLM-5.1 and GLM-4.7, we retire older ones. We base decisions on usage analysis, user feedback, performance metrics, and comparative testing against industry benchmarks.
Since this launch, AI has advanced significantly. The Kimi K3 and GLM-5.2 represent the current frontier, offering multi-million-token contexts and 2.8T-parameter architectures. For a detailed breakdown, see our GLM-5.2 vs Kimi K3 comparison. While these newer models push boundaries, the models in this release remain excellent choices for their specific niches.
The future of AI isn’t picking winners—it’s orchestration. Chat-O gives you the tools to create the perfect AI ensemble.
Do I need to choose one model forever? Nope. Switch anytime, or let our system recommend the best model for your task.
What if my favorite model gets retired? We give plenty of notice and help find suitable alternatives. Quality comes first.
How do you decide which models to add? We test extensively for real-world performance, reliability, and user value. Only the best make the cut.
Can models share context? Yes. Our system maintains conversation context across model switches for seamless collaboration.