Qwen3 235B A22B GGUF — Hardware Requirements & GPU Compatibility
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6.8K downloads
73 likesSpecifications
- Publisher
- Unsloth
- Family
- Qwen
- Parameters
- 235B
- Architecture
- Qwen3MoeForCausalLM
- Context Length
- 40,960 tokens
- Vocabulary Size
- 151,936
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Qwen3 235B A22B GGUF Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 470.5 GB | 474.2 GB | 470.00 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Qwen3 235B A22B GGUF?
BF16 · 470.5 GBQwen3 235B A22B GGUF (BF16) requires 470.5 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 612+ GB is recommended. Using the full 41K context window can add up to 3.7 GB, bringing total usage to 474.2 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Qwen3 235B A22B GGUF?
BF16 · 470.5 GB2 devices with unified memory can run Qwen3 235B A22B GGUF, including NVIDIA DGX H100.
Decent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Qwen3 235B A22B GGUF need?
Qwen3 235B A22B GGUF requires 470.5 GB of VRAM at BF16. Full 41K context adds up to 3.7 GB (474.2 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 235B × 16 bits ÷ 8 = 470 GB
KV Cache + Overhead ≈ 0.5 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 4.2 GB (at full 41K context)
VRAM usage by quantization
BF16470.5 GBBF16 + full context474.2 GB- Can NVIDIA GeForce RTX 5090 run Qwen3 235B A22B GGUF?
No — Qwen3 235B A22B GGUF requires at least 470.5 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run Qwen3 235B A22B GGUF on a Mac?
Qwen3 235B A22B GGUF requires at least 470.5 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 Qwen3 235B A22B GGUF locally?
Yes — Qwen3 235B A22B GGUF can run locally on consumer hardware. At BF16 quantization it needs 470.5 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- What's the download size of Qwen3 235B A22B GGUF?
At BF16, the download is about 470.00 GB.
- Which GPUs can run Qwen3 235B A22B GGUF?
No single consumer GPU has enough VRAM to run Qwen3 235B A22B GGUF at BF16 (470.5 GB). Multi-GPU or professional hardware is required.
- Which devices can run Qwen3 235B A22B GGUF?
2 devices with unified memory can run Qwen3 235B A22B GGUF at BF16 (470.5 GB), including NVIDIA DGX A100 640GB, NVIDIA DGX H100. Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.