Chinese AI company DeepSeek has released DeepSeek-V4.1-Flash-1017, an updated version of its Flash model with improvements in coding, agentic tasks, speed, and output efficiency.
The model is available through DeepSeek’s website, app, and API. The company has also published its weights on Hugging Face and ModelScope.
DeepSeek says the update delivers better benchmark performance than its predecessor while completing tasks faster and generating shorter responses. The company describes this as a Pareto improvement in the balance between performance and cost.
For end-to-end software development, DeepSeek uses a post-training method called reinforcement learning with self-feedback, or RLSF.
The technique allows the model to use its own confidence scores or generated critiques as reward signals rather than relying on human evaluators or external reward models.