Running the New DeepSeek V4.1 Flash Release on Local Hardware: Setup, Quantizations, and Benchmark Results

This video introduces the newly released DeepSeek V4.1 Flash model and walks through how to set it up and run it locally. Since the update only changes model weights rather than architecture, the existing setup can be reused without modification. The presenter also shares benchmark observations and performance measurements from running the model on local hardware.

■ Model Update and Quantizations
- What changed in the new V4.1 Flash release and how it compares to the previous version
- Custom quantizations (including a low-bit version) available for download, and where to get them

■ Setup and Operation
- How to download the model weights via the AI Toolbox Cockpit interface
- Server mode configuration, context length options, and SWA-limited responses
- Enabling speculative decoding and vision features
- Running the model standalone on one device or in a coordinator/worker setup across two devices

■ Performance and Benchmarks
- Prefill and token generation speeds measured on one and two connected devices
- Early Terminal Bench Mini results comparing token usage and completion time with the previous version
- Where full benchmark results will be published

This video is aimed at users interested in running large language models locally, particularly those with compatible local hardware or an existing setup. Viewers can learn what the new release changes, how to get it running quickly, and what kinds of performance differences to expect in real-world tasks.