Aurora Code 1 — Hardware Requirements & GPU Compatibility
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Aurora Code 1 is a 34.7B-parameter open language model from Perciqa. It supports a context window of up to 262,144 tokens. At BF16 it needs about 69.71 GB of VRAM — see which GPUs and Macs can run it below.
350 downloads
4 likesSpecifications
- Publisher
- Perciqa
- Parameters
- 34.7B
- Architecture
- Qwen3_5MoeForCausalLM
- Context Length
- 262,144 tokens
- Vocabulary Size
- 248,320
- Release Date
- 2026-07-17
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Aurora Code 1 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16est. | 16.00 | 69.7 GB | 80.4 GB | 69.32 GB | Brain floating point 16 — preferred for training |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run Aurora Code 1?
BF16 · 69.7 GBAurora Code 1 (BF16) requires 69.7 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 91+ GB is recommended. Using the full 262K context window can add up to 10.7 GB, bringing total usage to 80.4 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Aurora Code 1?
BF16 · 69.7 GB19 devices with unified memory can run Aurora Code 1, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio (M3 Ultra, 96GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Aurora Code 1 need?
Aurora Code 1 requires 69.7 GB of VRAM at BF16. Full 262K context adds up to 10.7 GB (80.4 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 34.7B × 16 bits ÷ 8 = 69.3 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 11.1 GB (at full 262K context)
VRAM usage by quantization
BF1669.7 GBBF16 + full context80.4 GB- Can NVIDIA GeForce RTX 5090 run Aurora Code 1?
No — Aurora Code 1 requires at least 69.7 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run Aurora Code 1 on a Mac?
Aurora Code 1 requires at least 69.7 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 Aurora Code 1 locally?
Yes — Aurora Code 1 can run locally on consumer hardware. At BF16 quantization it needs 69.7 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Aurora Code 1?
At BF16, Aurora Code 1 can reach ~63 tok/s on AMD Instinct MI350X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 69.7 × 0.65 = ~75 tok/s
Estimated speed at BF16 (69.7 GB)
~75 tok/s~75 tok/s~63 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Aurora Code 1?
At BF16, the download is about 69.32 GB.
- Which GPUs can run Aurora Code 1?
No single consumer GPU has enough VRAM to run Aurora Code 1 at BF16 (69.7 GB). Multi-GPU or professional hardware is required.
- Which devices can run Aurora Code 1?
19 devices with unified memory can run Aurora Code 1 at BF16 (69.7 GB), including ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.