Edge0 8B A1B Preview — Hardware Requirements & GPU Compatibility
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Edge0 8B A1B Preview is a 7.9B-parameter open language model from Edge0. It supports a context window of up to 131,072 tokens. At BF16 it needs about 16.45 GB of VRAM — see which GPUs and Macs can run it below.
5.1K downloads
79 likesSpecifications
- Publisher
- Edge0
- Parameters
- 7.9B
- Architecture
- BailingMoeV3ForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 157,184
- Release Date
- 2026-09-08
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Edge0 8B A1B Preview Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16est. | 16.00 | 16.4 GB | 35.5 GB | 15.85 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 Edge0 8B A1B Preview?
BF16 · 16.4 GBEdge0 8B A1B Preview (BF16) requires 16.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 22+ GB is recommended. Using the full 131K context window can add up to 19.0 GB, bringing total usage to 35.5 GB. 8 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroom
Which Devices Can Run Edge0 8B A1B Preview?
BF16 · 16.4 GB41 devices with unified memory can run Edge0 8B A1B Preview, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Edge0 8B A1B Preview need?
Edge0 8B A1B Preview requires 16.4 GB of VRAM at BF16. Full 131K context adds up to 19.0 GB (35.5 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 7.9B × 16 bits ÷ 8 = 15.8 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 19.7 GB (at full 131K context)
VRAM usage by quantization
BF1616.4 GBBF16 + full context35.5 GB- Can I run Edge0 8B A1B Preview on a Mac?
Edge0 8B A1B Preview requires at least 16.4 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 Edge0 8B A1B Preview locally?
Yes — Edge0 8B A1B Preview can run locally on consumer hardware. At BF16 quantization it needs 16.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Edge0 8B A1B Preview?
At BF16, Edge0 8B A1B Preview can reach ~185 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~173 tok/s. 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 ÷ 16.4 × 0.65 = ~531 tok/s
Estimated speed at BF16 (16.4 GB)
~531 tok/s~173 tok/s~531 tok/s~446 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Edge0 8B A1B Preview?
At BF16, the download is about 15.85 GB.
- Which GPUs can run Edge0 8B A1B Preview?
8 consumer GPUs can run Edge0 8B A1B Preview at BF16 (16.4 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 Edge0 8B A1B Preview?
41 devices with unified memory can run Edge0 8B A1B Preview at BF16 (16.4 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (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.