NaNovel 27B — Hardware Requirements & GPU Compatibility
ChatReasoning
93 downloads
4 likesSpecifications
- Publisher
- Dxniz
- Parameters
- 27.8B
- Architecture
- Qwen3_5ForConditionalGeneration
- Context Length
- 262,144 tokens
- Vocabulary Size
- 248,320
- Release Date
- 2026-03-13
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does NaNovel 27B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 56.3 GB | 113.1 GB | 55.56 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run NaNovel 27B?
BF16 · 56.3 GBNaNovel 27B (BF16) requires 56.3 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 74+ GB is recommended. Using the full 262K context window can add up to 56.8 GB, bringing total usage to 113.1 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run NaNovel 27B?
BF16 · 56.3 GB8 devices with unified memory can run NaNovel 27B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 Max (64 GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does NaNovel 27B need?
NaNovel 27B requires 56.3 GB of VRAM at BF16. Full 262K context adds up to 56.8 GB (113.1 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 27.8B × 16 bits ÷ 8 = 55.6 GB
KV Cache + Overhead ≈ 0.7 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 57.5 GB (at full 262K context)
VRAM usage by quantization
BF1656.3 GBBF16 + full context113.1 GB- Can NVIDIA GeForce RTX 5090 run NaNovel 27B?
No — NaNovel 27B requires at least 56.3 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run NaNovel 27B on a Mac?
NaNovel 27B requires at least 56.3 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 NaNovel 27B locally?
Yes — NaNovel 27B can run locally on consumer hardware. At BF16 quantization it needs 56.3 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is NaNovel 27B?
At BF16, NaNovel 27B can reach ~52 tok/s on AMD Instinct MI300X. 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 ÷ 56.3 × 0.55 = ~52 tok/s
Estimated speed at BF16 (56.3 GB)
AMD Instinct MI300X~52 tok/sNVIDIA H100 SXM~39 tok/sAMD Instinct MI250X~32 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of NaNovel 27B?
At BF16, the download is about 55.56 GB.
- Which GPUs can run NaNovel 27B?
No single consumer GPU has enough VRAM to run NaNovel 27B at BF16 (56.3 GB). Multi-GPU or professional hardware is required.
- Which devices can run NaNovel 27B?
8 devices with unified memory can run NaNovel 27B at BF16 (56.3 GB), including Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB), Mac Studio M4 Max (128 GB), Mac Studio M4 Max (64 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.