Qwen3.8 Flash Next REAP 288 BF16 — Hardware Requirements & GPU Compatibility
Chat
Qwen3.8 Flash Next REAP 288 BF16 is a 124.5B-parameter open language model from sh0wie in the Qwen 3.8 family. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 75.09 GB of VRAM — see which GPUs and Macs can run it below.
867 downloads
2 likesSpecifications
- Publisher
- sh0wie
- Family
- Qwen 3.8
- Parameters
- 124.5B
- Architecture
- Qwen4ExpForConditionalGeneration
- Context Length
- 262,144 tokens
- Vocabulary Size
- 248,320
- Release Date
- 2026-08-29
- License
- Other
Get Started
HuggingFace
How Much VRAM Does Qwen3.8 Flash Next REAP 288 BF16 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 53.3 GB | 64.0 GB | 52.92 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 61.1 GB | 71.7 GB | 60.70 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 75.1 GB | 85.8 GB | 74.71 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 89.1 GB | 99.8 GB | 88.72 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 103.1 GB | 113.8 GB | 102.73 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 124.9 GB | 135.6 GB | 124.52 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 249.4 GB | 260.1 GB | 249.03 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 REAP 288 BF16?
Q4_K_M · 75.1 GBQwen3.8 Flash Next REAP 288 BF16 (Q4_K_M) requires 75.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 98+ GB is recommended. Using the full 262K context window can add up to 10.7 GB, bringing total usage to 85.8 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Qwen3.8 Flash Next REAP 288 BF16?
Q4_K_M · 75.1 GB18 devices with unified memory can run Qwen3.8 Flash Next REAP 288 BF16, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, NVIDIA Jetson AGX Thor Developer Kit.
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Qwen3.8 Flash Next REAP 288 BF16 need?
Qwen3.8 Flash Next REAP 288 BF16 requires 75.1 GB of VRAM at Q4_K_M, or 249.4 GB at BF16. Full 262K context adds up to 10.7 GB (85.8 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 124.5B × 4.8 bits ÷ 8 = 74.7 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_M75.1 GBQ4_K_M + full context85.8 GB- Can NVIDIA GeForce RTX 5090 run Qwen3.8 Flash Next REAP 288 BF16?
No — Qwen3.8 Flash Next REAP 288 BF16 requires at least 53.3 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 REAP 288 BF16?
For Qwen3.8 Flash Next REAP 288 BF16, Q4_K_M (75.1 GB) offers the best balance of quality and VRAM usage. Q5_K_M (89.1 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 53.3 GB.
VRAM requirement by quantization
Q2_K53.3 GBQ4_K_M ★75.1 GBQ5_K_M89.1 GBQ6_K103.1 GBQ8_0124.9 GBBF16249.4 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Qwen3.8 Flash Next REAP 288 BF16 on a Mac?
Qwen3.8 Flash Next REAP 288 BF16 requires at least 53.3 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 REAP 288 BF16 locally?
Yes — Qwen3.8 Flash Next REAP 288 BF16 can run locally on consumer hardware. At Q4_K_M quantization it needs 75.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen3.8 Flash Next REAP 288 BF16?
At Q4_K_M, Qwen3.8 Flash Next REAP 288 BF16 can reach ~64 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 ÷ 75.1 × 0.65 = ~69 tok/s
Estimated speed at Q4_K_M (75.1 GB)
~69 tok/s~69 tok/s~64 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 REAP 288 BF16?
At Q4_K_M, the download is about 74.71 GB. The full-precision BF16 version is 249.03 GB. The smallest option (Q2_K) is 52.92 GB.
- Which GPUs can run Qwen3.8 Flash Next REAP 288 BF16?
No single consumer GPU has enough VRAM to run Qwen3.8 Flash Next REAP 288 BF16 at Q4_K_M (75.1 GB). Multi-GPU or professional hardware is required.
- Which devices can run Qwen3.8 Flash Next REAP 288 BF16?
19 devices with unified memory can run Qwen3.8 Flash Next REAP 288 BF16 at Q4_K_M (75.1 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.