Qwen3.8 Flash Next — Hardware Requirements & GPU Compatibility
Vision
Qwen3.8 Flash Next is a 180.0B-parameter open language model from Alibaba in the Qwen 3.8 family. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 108.38 GB of VRAM — see which GPUs and Macs can run it below.
401.3K downloads
4.9K likesSpecifications
- Publisher
- Alibaba
- Family
- Qwen 3.8
- Parameters
- 180.0B
- Architecture
- Qwen4ExpForConditionalGeneration
- Context Length
- 262,144 tokens
- Vocabulary Size
- 248,320
- Release Date
- 2026-08-24
- License
- Other
Get Started
HuggingFace
How Much VRAM Does Qwen3.8 Flash Next Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 76.9 GB | 87.5 GB | 76.50 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 88.1 GB | 98.8 GB | 87.75 GB | 3-bit medium quantization |
| IQ4_XS | 4.30 | 97.1 GB | 107.8 GB | 96.75 GB | Importance-weighted 4-bit, compact |
| Q4_K_M | 4.80 | 108.4 GB | 119.0 GB | 108.00 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 128.6 GB | 139.3 GB | 128.25 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 148.9 GB | 159.5 GB | 148.50 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 180.4 GB | 191.0 GB | 180.00 GB | 8-bit quantization, near-lossless |
| BF16 | 16.00 | 360.4 GB | 371.0 GB | 360.00 GB | Brain floating point 16 — preferred for training |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run Qwen3.8 Flash Next?
Q4_K_M · 108.4 GBQwen3.8 Flash Next (Q4_K_M) requires 108.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 141+ GB is recommended. Using the full 262K context window can add up to 10.7 GB, bringing total usage to 119.0 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Qwen3.8 Flash Next?
Q4_K_M · 108.4 GB11 devices with unified memory can run Qwen3.8 Flash Next, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Pro 16" M5 Max (128 GB).
Runs great
— Plenty of headroom
Where to Download Qwen3.8 Flash Next
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Benchmarks
Benchmark details →Related Models
Frequently Asked Questions
- How much VRAM does Qwen3.8 Flash Next need?
Qwen3.8 Flash Next requires 108.4 GB of VRAM at Q4_K_M, or 360.4 GB at BF16. Full 262K context adds up to 10.7 GB (119.0 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 180.0B × 4.8 bits ÷ 8 = 108 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 11 GB (at full 262K context)
VRAM usage by quantization
Q4_K_M108.4 GBQ4_K_M + full context119.0 GB- Can NVIDIA GeForce RTX 5090 run Qwen3.8 Flash Next?
No — Qwen3.8 Flash Next requires at least 76.9 GB at Q2_K, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for Qwen3.8 Flash Next?
For Qwen3.8 Flash Next, Q4_K_M (108.4 GB) offers the best balance of quality and VRAM usage. Q5_K_M (128.6 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 76.9 GB.
VRAM requirement by quantization
Q2_K76.9 GBIQ4_XS97.1 GBQ4_K_M ★108.4 GBQ5_K_M128.6 GBQ6_K148.9 GBBF16360.4 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Qwen3.8 Flash Next on a Mac?
Qwen3.8 Flash Next requires at least 76.9 GB at Q2_K, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Qwen3.8 Flash Next locally?
Yes — Qwen3.8 Flash Next can run locally on consumer hardware. At Q4_K_M quantization it needs 108.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen3.8 Flash Next?
At Q4_K_M, Qwen3.8 Flash Next can reach ~44 tok/s on AMD Instinct MI350X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 108.4 × 0.65 = ~48 tok/s
Estimated speed at Q4_K_M (108.4 GB)
~48 tok/s~48 tok/s~44 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Qwen3.8 Flash Next?
At Q4_K_M, the download is about 108.00 GB. The full-precision BF16 version is 360.00 GB. The smallest option (Q2_K) is 76.50 GB.
- Which GPUs can run Qwen3.8 Flash Next?
No single consumer GPU has enough VRAM to run Qwen3.8 Flash Next at Q4_K_M (108.4 GB). Multi-GPU or professional hardware is required.
- Which devices can run Qwen3.8 Flash Next?
18 devices with unified memory can run Qwen3.8 Flash Next at Q4_K_M (108.4 GB), including ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.