DeepSeek's V4 Flash model has garnered significant developer attention due to its strong performance on leaderboards. However, real-world testing revealed it struggles with complex multi-step tasks involving various tools. Composio's tests showed V4 Flash completed only 53.8% of these tasks, highlighting the crucial role of orchestration over raw model capability. The model's performance varied significantly based on the harness and tool configurations used. DeepSeek is increasing prices for its V4 Flash and Pro models, a move that significantly alters its cost advantage. Despite the price hike, DeepSeek models remain considerably cheaper than those from major competitors. This shift forces a greater emphasis on performance and security over pure cost. Enterprises are considering DeepSeek for specific workloads like batch processing, where efficiency is key. Naman Ahuja's home automation project demonstrated the importance of reliability and structured outputs for agents that take actions. The future for DeepSeek in enterprise settings hinges on proving reliability, security, and demonstrable business cases beyond benchmark performance.