Qwen3 235B A22B 128K GGUF — Hardware Requirements & GPU Compatibility
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1.6K downloads
36 likesSpecifications
- Publisher
- Unsloth
- Family
- Qwen
- Parameters
- 235B
- Architecture
- Qwen3MoeForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 151,936
- License
- Apache 2.0
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HuggingFace
How Much VRAM Does Qwen3 235B A22B 128K GGUF Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 470.5 GB | 482.9 GB | 470.00 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Qwen3 235B A22B 128K GGUF?
BF16 · 470.5 GBQwen3 235B A22B 128K 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 131K context window can add up to 12.4 GB, bringing total usage to 482.9 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Qwen3 235B A22B 128K GGUF?
BF16 · 470.5 GB2 devices with unified memory can run Qwen3 235B A22B 128K GGUF, including NVIDIA DGX H100.
Decent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Qwen3 235B A22B 128K GGUF need?
Qwen3 235B A22B 128K GGUF requires 470.5 GB of VRAM at BF16. Full 131K context adds up to 12.4 GB (482.9 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 ≈ 12.9 GB (at full 131K context)
VRAM usage by quantization
BF16470.5 GBBF16 + full context482.9 GB- Can NVIDIA GeForce RTX 5090 run Qwen3 235B A22B 128K GGUF?
No — Qwen3 235B A22B 128K 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 128K GGUF on a Mac?
Qwen3 235B A22B 128K 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 128K GGUF locally?
Yes — Qwen3 235B A22B 128K 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 128K GGUF?
At BF16, the download is about 470.00 GB.
- Which GPUs can run Qwen3 235B A22B 128K GGUF?
No single consumer GPU has enough VRAM to run Qwen3 235B A22B 128K GGUF at BF16 (470.5 GB). Multi-GPU or professional hardware is required.
- Which devices can run Qwen3 235B A22B 128K GGUF?
2 devices with unified memory can run Qwen3 235B A22B 128K 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.