NuExtract 1.5 — Hardware Requirements & GPU Compatibility
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7.1K downloads
244 likesSpecifications
- Publisher
- numind
- Parameters
- 3.8B
- Architecture
- Phi3ForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 32,064
- Release Date
- 2025-07-17
- License
- MIT
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HuggingFace
How Much VRAM Does NuExtract 1.5 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 8.8 GB | 59.5 GB | 7.64 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run NuExtract 1.5?
BF16 · 8.8 GBNuExtract 1.5 (BF16) requires 8.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 12+ GB is recommended. Using the full 131K context window can add up to 50.7 GB, bringing total usage to 59.5 GB. 28 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3080 Ti.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run NuExtract 1.5?
BF16 · 8.8 GB27 devices with unified memory can run NuExtract 1.5, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does NuExtract 1.5 need?
NuExtract 1.5 requires 8.8 GB of VRAM at BF16. Full 131K context adds up to 50.7 GB (59.5 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 3.8B × 16 bits ÷ 8 = 7.6 GB
KV Cache + Overhead ≈ 1.2 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 51.9 GB (at full 131K context)
VRAM usage by quantization
BF168.8 GBBF16 + full context59.5 GB- Can I run NuExtract 1.5 on a Mac?
NuExtract 1.5 requires at least 8.8 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 NuExtract 1.5 locally?
Yes — NuExtract 1.5 can run locally on consumer hardware. At BF16 quantization it needs 8.8 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is NuExtract 1.5?
At BF16, NuExtract 1.5 can reach ~333 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~75 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 ÷ 8.8 × 0.55 = ~333 tok/s
Estimated speed at BF16 (8.8 GB)
AMD Instinct MI300X~333 tok/sNVIDIA GeForce RTX 4090~75 tok/sNVIDIA H100 SXM~249 tok/sAMD Instinct MI250X~206 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of NuExtract 1.5?
At BF16, the download is about 7.64 GB.
- Which GPUs can run NuExtract 1.5?
28 consumer GPUs can run NuExtract 1.5 at BF16 (8.8 GB). Top options include AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 6900 XT, AMD Radeon RX 6700 XT. 17 GPUs have plenty of headroom for comfortable inference.
- Which devices can run NuExtract 1.5?
27 devices with unified memory can run NuExtract 1.5 at BF16 (8.8 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.