01What it can do
- 125B/6B active MoE: high throughput for its size
- Native 256k context
- Multimodal (vision, code, chat)
- Fits on an 80 GB GPU in Q4 (~72 GB)
- —One server-class option remains (~72 GB VRAM Q4)
- —“other” license — check the terms of use
- —Recent weights: the quantized ecosystem is still young
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 Qwen3.8 Flash Next 125B-A6B?
To run Qwen3.8 Flash Next 125B-A6B locally with Q4 quantization, you need about 72 GB of VRAM. An option to compare: BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395) — leave some headroom for the system and context; check engine compatibility with the GPU.
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.