Qwopus3.6 27B v2 GPTQ Pro V1 — Hardware Requirements & GPU Compatibility
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Qwopus3.6 27B v2 GPTQ Pro V1 is a 27.4B-parameter open language model from XReyRobert. It supports a context window of up to 262,144 tokens. At BF16 it needs about 55.46 GB of VRAM — see which GPUs and Macs can run it below.
5.7K downloads
6 likesSpecifications
- Publisher
- XReyRobert
- Parameters
- 27.4B
- Architecture
- Qwen3_5ForConditionalGeneration
- Context Length
- 262,144 tokens
- Vocabulary Size
- 248,320
- Release Date
- 2026-06-01
- License
- Apache 2.0
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HuggingFace
How Much VRAM Does Qwopus3.6 27B v2 GPTQ Pro V1 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 55.5 GB | 112.3 GB | 54.71 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Qwopus3.6 27B v2 GPTQ Pro V1?
BF16 · 55.5 GBQwopus3.6 27B v2 GPTQ Pro V1 (BF16) requires 55.5 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 73+ GB is recommended. Using the full 262K context window can add up to 56.8 GB, bringing total usage to 112.3 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Qwopus3.6 27B v2 GPTQ Pro V1?
BF16 · 55.5 GB8 devices with unified memory can run Qwopus3.6 27B v2 GPTQ Pro V1, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 Max (64 GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Qwopus3.6 27B v2 GPTQ Pro V1 need?
Qwopus3.6 27B v2 GPTQ Pro V1 requires 55.5 GB of VRAM at BF16. Full 262K context adds up to 56.8 GB (112.3 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 27.4B × 16 bits ÷ 8 = 54.7 GB
KV Cache + Overhead ≈ 0.8 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 57.6 GB (at full 262K context)
VRAM usage by quantization
BF1655.5 GBBF16 + full context112.3 GB- Can NVIDIA GeForce RTX 5090 run Qwopus3.6 27B v2 GPTQ Pro V1?
No — Qwopus3.6 27B v2 GPTQ Pro V1 requires at least 55.5 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run Qwopus3.6 27B v2 GPTQ Pro V1 on a Mac?
Qwopus3.6 27B v2 GPTQ Pro V1 requires at least 55.5 GB at BF16, 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 Qwopus3.6 27B v2 GPTQ Pro V1 locally?
Yes — Qwopus3.6 27B v2 GPTQ Pro V1 can run locally on consumer hardware. At BF16 quantization it needs 55.5 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwopus3.6 27B v2 GPTQ Pro V1?
At BF16, Qwopus3.6 27B v2 GPTQ Pro V1 can reach ~53 tok/s on AMD Instinct MI300X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 55.5 × 0.55 = ~53 tok/s
Estimated speed at BF16 (55.5 GB)
~53 tok/s~39 tok/s~33 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Qwopus3.6 27B v2 GPTQ Pro V1?
At BF16, the download is about 54.71 GB.
- Which GPUs can run Qwopus3.6 27B v2 GPTQ Pro V1?
No single consumer GPU has enough VRAM to run Qwopus3.6 27B v2 GPTQ Pro V1 at BF16 (55.5 GB). Multi-GPU or professional hardware is required.
- Which devices can run Qwopus3.6 27B v2 GPTQ Pro V1?
8 devices with unified memory can run Qwopus3.6 27B v2 GPTQ Pro V1 at BF16 (55.5 GB), including Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB), Mac Studio M4 Max (128 GB), Mac Studio M4 Max (64 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.