# Reinforcement Learning with Self-Feedback

DeepSeek released DeepSeek-V4.1-Flash-1017, which it says delivers stronger benchmark performance, faster task completion and shorter outputs than the previous version, a Pareto improvement in performance and cost, now live on its website, app and API. The model uses reinforcement learning with self-feedback to improve end-to-end project development, with demos spanning 3D modeling, a web racing game and a Godot-engine recreation. The Search and Fetch APIs also opened to everyone at $0.75 per 1,000 calls per endpoint.

DeepSeek released DeepSeek-V4.1-Flash-1017, which it says delivers stronger benchmark performance, faster task completion and shorter outputs than the previous version, a Pareto improvement in performance and cost, now live on its website, app and API. The model uses reinforcement learning with self-feedback to improve end-to-end project development, with demos spanning 3D modeling, a web racing game and a Godot-engine recreation. The Search and Fetch APIs also opened to everyone at $0.75 per 1,000 calls per endpoint.