Qwen3 235B A22B Thinking 2507 GGUF — Hardware Requirements & GPU Compatibility
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2.6K downloads
81 likesSpecifications
- Publisher
- Unsloth
- Family
- Qwen
- Parameters
- 235B
- License
- Apache 2.0
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HuggingFace
How Much VRAM Does Qwen3 235B A22B Thinking 2507 GGUF Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 517 GB | — | 470.00 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Qwen3 235B A22B Thinking 2507 GGUF?
BF16 · 517 GBQwen3 235B A22B Thinking 2507 GGUF (BF16) requires 517 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 673+ GB is recommended. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Qwen3 235B A22B Thinking 2507 GGUF?
BF16 · 517 GB2 devices with unified memory can run Qwen3 235B A22B Thinking 2507 GGUF, including NVIDIA DGX H100.
Decent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Qwen3 235B A22B Thinking 2507 GGUF need?
Qwen3 235B A22B Thinking 2507 GGUF requires 517 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 235B × 16 bits ÷ 8 = 470 GB
KV Cache + Overhead ≈ 47 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF16517.0 GB- Can NVIDIA GeForce RTX 5090 run Qwen3 235B A22B Thinking 2507 GGUF?
No — Qwen3 235B A22B Thinking 2507 GGUF requires at least 517 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run Qwen3 235B A22B Thinking 2507 GGUF on a Mac?
Qwen3 235B A22B Thinking 2507 GGUF requires at least 517 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 Thinking 2507 GGUF locally?
Yes — Qwen3 235B A22B Thinking 2507 GGUF can run locally on consumer hardware. At BF16 quantization it needs 517 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- What's the download size of Qwen3 235B A22B Thinking 2507 GGUF?
At BF16, the download is about 470.00 GB.
- Which GPUs can run Qwen3 235B A22B Thinking 2507 GGUF?
No single consumer GPU has enough VRAM to run Qwen3 235B A22B Thinking 2507 GGUF at BF16 (517 GB). Multi-GPU or professional hardware is required.
- Which devices can run Qwen3 235B A22B Thinking 2507 GGUF?
2 devices with unified memory can run Qwen3 235B A22B Thinking 2507 GGUF at BF16 (517 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.