01What it can do
- Massive context up to ~1M tokens
- Focused on code and agentic reasoning
- Permissive MIT license
- Official release (supersedes the preview)
- —Very large model: ~176 GB VRAM in Q4, beyond the reach of consumers
- —Modest local throughput (~5 tok/s in Q4)
- —No Ollama tag — install via HuggingFace
04Install
Install Ollama for your OS. Check the model and its quantization before downloading. Start with 4096 tokens of context, then check placement with ollama ps. A command below is not proof that a test was run on your machine.
02Required memory
Approximate GPU VRAM required to run this model, including 4k tokens of context overhead. For a longer context, add ~1 GB per 8k-token increment.
What hardware do you need for DeepSeek V4 Flash 0731 304B?
To run DeepSeek V4 Flash 0731 304B locally with Q4 quantization, you need about 176 GB of VRAM. An option to compare: BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395) — this model exceeds this mini-PC's GPU capacity: choose a smaller model or suitable infrastructure.
Why this choice? Our complete guide on BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395) →
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03Expected speed
Tokens generated per second in Q4_K_M, 4k context. Beyond 20 t/s, reading is comfortable. Below 10 t/s, that's just for testing.