Cdx1 Pro 30B Q4 K M GGUF — Hardware Requirements & GPU Compatibility
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19 downloads
1 likesSpecifications
- Publisher
- CycloneDX
- Parameters
- 30B
- Architecture
- Qwen3MoeForCausalLM
- Context Length
- 262,144 tokens
- Vocabulary Size
- 151,936
- Release Date
- 2025-08-10
- License
- Apache 2.0
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HuggingFace
How Much VRAM Does Cdx1 Pro 30B Q4 K M GGUF Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q4_K_M | 4.80 | 18.4 GB | 31.2 GB | 18.00 GB | 4-bit medium quantization — most popular sweet spot |
Which GPUs Can Run Cdx1 Pro 30B Q4 K M GGUF?
Q4_K_M · 18.4 GBCdx1 Pro 30B Q4 K M GGUF (Q4_K_M) requires 18.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 24+ GB is recommended. Using the full 262K context window can add up to 12.8 GB, bringing total usage to 31.2 GB. 6 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroom
Which Devices Can Run Cdx1 Pro 30B Q4 K M GGUF?
Q4_K_M · 18.4 GB21 devices with unified memory can run Cdx1 Pro 30B Q4 K M GGUF, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Cdx1 Pro 30B Q4 K M GGUF need?
Cdx1 Pro 30B Q4 K M GGUF requires 18.4 GB of VRAM at Q4_K_M. Full 262K context adds up to 12.8 GB (31.2 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 30B × 4.8 bits ÷ 8 = 18 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 13.2 GB (at full 262K context)
VRAM usage by quantization
Q4_K_M18.4 GBQ4_K_M + full context31.2 GB- Can I run Cdx1 Pro 30B Q4 K M GGUF on a Mac?
Cdx1 Pro 30B Q4 K M GGUF requires at least 18.4 GB at Q4_K_M, 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 Cdx1 Pro 30B Q4 K M GGUF locally?
Yes — Cdx1 Pro 30B Q4 K M GGUF can run locally on consumer hardware. At Q4_K_M quantization it needs 18.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Cdx1 Pro 30B Q4 K M GGUF?
At Q4_K_M, Cdx1 Pro 30B Q4 K M GGUF can reach ~158 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~36 tok/s. 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 ÷ 18.4 × 0.55 = ~158 tok/s
Estimated speed at Q4_K_M (18.4 GB)
AMD Instinct MI300X~158 tok/sNVIDIA GeForce RTX 4090~36 tok/sNVIDIA H100 SXM~118 tok/sAMD Instinct MI250X~98 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Cdx1 Pro 30B Q4 K M GGUF?
At Q4_K_M, the download is about 18.00 GB.
- Which GPUs can run Cdx1 Pro 30B Q4 K M GGUF?
6 consumer GPUs can run Cdx1 Pro 30B Q4 K M GGUF at Q4_K_M (18.4 GB). Top options include NVIDIA GeForce RTX 5090, AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XTX. 1 GPU have plenty of headroom for comfortable inference.
- Which devices can run Cdx1 Pro 30B Q4 K M GGUF?
21 devices with unified memory can run Cdx1 Pro 30B Q4 K M GGUF at Q4_K_M (18.4 GB), including Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.