Can You Run Qwen3.8-Flash-Next (180B MoE)? VRAM Requirements
Qwen3.8-Flash-Next (180B MoE) has 180B total parameters (MoE, 6B active per token). Running it at Q4_K_M (GGUF) with 16K context takes roughly 111 GB of memory (102 GB weights + 0.4 GB KV cache + runtime overhead). The minimum viable hardware is about Mac 128GB unified. All numbers are planning estimates, verified 2026-09-05.
⚠ Some architecture details of this model are estimated — treat results as ballpark figures.
VRAM by quantization (16K context)
| Quantization | Weights | Total needed | Minimum hardware |
|---|---|---|---|
| FP16 / BF16 | 335 GB | 362 GB | Mac M3 Ultra 512GB |
| FP8 | 168 GB | 181 GB | Mac M3 Ultra 512GB |
| Q8_0 (GGUF) | 178 GB | 192 GB | Mac M3 Ultra 512GB |
| Q6_K (GGUF) | 137 GB | 149 GB | AMD MI300X 192GB |
| Q5_K_M (GGUF) | 119 GB | 129 GB | H200 141GB |
| MXFP4 | 88.8 GB | 96.3 GB | Mac 128GB unified |
| NVFP4 | 88.8 GB | 96.3 GB | Mac 128GB unified |
| Q4_K_M (GGUF)recommended | 102 GB | 111 GB | Mac 128GB unified |
| Q3_K_M (GGUF) | 78.8 GB | 85.5 GB | Mac 128GB unified |
| Q2_K (GGUF) | 58.7 GB | 63.7 GB | A100 / H100 80GB |
How context length changes memory (Q4_K_M (GGUF))
| Context | KV cache | Total needed |
|---|---|---|
| 4K | 0.1 GB | 111 GB |
| 16K | 0.4 GB | 111 GB |
| 64K | 1.5 GB | 112 GB |
| 128K | 3.0 GB | 113 GB |
| 256K | 6.0 GB | 116 GB |
KV cache grows linearly with context; FP8 KV cache halves it again (try it in the calculator below).
Customize the estimate
LLM VRAM Calculator — Can I Run It?
Estimate how much GPU memory (VRAM) you need to run open-weight LLMs like Kimi K3, DeepSeek R1, Qwen3, or Llama locally. Pick a model, quantization, and context length — the calculator adds up weights, KV cache, and runtime overhead, then shows which GPUs or Macs can fit it. Runs entirely in your browser: no upload, no signup.
180B total params · 6B active (MoE) · max 256K context · specs partially estimated
Recommended balance · ~0.61 bytes/param
Estimated memory needed
113 GB
Architecture details for this model are estimated — treat results as a ballpark.
Will it fit?
Assumes ~92% of device memory is usable. Multi-GPU counts are for tensor/pipeline parallel serving (vLLM, SGLang); Apple Silicon uses unified memory via llama.cpp or MLX.
FAQ
How much VRAM does Qwen3.8-Flash-Next (180B MoE) need?
About 111 GB at the recommended Q4_K_M (GGUF) quantization with 16K context: 102 GB for weights, 0.4 GB for KV cache, plus runtime overhead. Longer context grows the KV cache.
What is the minimum hardware for Qwen3.8-Flash-Next (180B MoE)?
Roughly Mac 128GB unified, assuming 92% of device memory is usable. Lower-end setups can try more aggressive quantization (Q3/Q2) at a noticeable quality cost.
Can I run Qwen3.8-Flash-Next (180B MoE) on a Mac?
Yes. At Q4_K_M (GGUF) with 16K context it needs about 111 GB, which fits the unified memory of a Mac M3 Ultra 512GB via llama.cpp or MLX.
Which quantization should I use for Qwen3.8-Flash-Next (180B MoE)?
Q4_K_M is the recommended balance of size and quality; with headroom, Q6_K or Q8_0 reduce quality loss further.