DeepSeek's DS V4-Flash runs locally on 3x AMD MI50 GPUs
Local benchmark shows DS V4-Flash-0731 delivering 15 tokens/sec with 90.9GB model size...
DeepSeek's DS V4-Flash-0731 has become the latest quantized model to break local deployment barriers, achieving stable performance on consumer-adjacent hardware. A user on Reddit reported running the full 90.9GB model entirely in VRAM across three AMD MI50 GPUs (96GB total VRAM), delivering 15-16 tokens/second during text generation and 105-110 tokens/second during prompt processing. The benchmark maintained consistent speeds even when generating a 30K token response, demonstrating the model's efficiency in a quantized format.
The same user validated the model's coding capabilities by successfully completing a complex Rubik's Cube animation task that required creating a single HTML file with 3D rendering using only canvas APIs. The generated animation perfectly executed the specified 20-move sequence (10 scrambles + 10 solves) with proper sticker tracking and smooth transitions. This local deployment capability eliminates API dependency for users who previously relied on DeepSeek's cloud service.
- DS V4-Flash-0731 runs fully in VRAM on 3x AMD MI50 GPUs (90.9GB model, 96GB VRAM total)
- Achieves 15-16 tokens/sec generation and 105-110 tokens/sec prompt processing with stable performance
- Successfully completes complex coding task (3D Rubik's Cube animation) locally without API dependency
Why It Matters
Brings DeepSeek's advanced models to local environments, reducing cloud costs and API latency while enabling complete data privacy.