Arcee Trinity Nano 6B on NVIDIA RTX 4070 Laptop (80-115W)
Yes — RTX 4070 Laptop (80-115W) runs Arcee Trinity Nano 6B excellently at Q8_0 — 45 tok/s. 8 GB VRAM with plenty of headroom.
Model Size
6B
Device VRAM
8 GB
Bandwidth
256 GB/s
Quantization
Q8_0
Performance by Quantization
OwnRig currently has one published compatibility entry for Arcee Trinity Nano 6B on NVIDIA RTX 4070 Laptop (80-115W) at Q8_0. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q8_0 | 45 tok/s | 200ms | ✓ Yes | Excellent | estimated |
Notes
Q8_0
6B MoE (1B active). Q8_0 7.5GB on 8GB discrete gpu.
About Arcee Trinity Nano 6B
Arcee Trinity Nano 6B (6B) is a chat, coding, multi-purpose model. Arcee AI's smallest Mixture-of-Experts model. 6B total parameters with only 1B active per token (128 experts, 8 selected + 1 shared). Runs on consumer GPUs, edge devices, and mobile; fits at full Q8_0 precision on any GPU with 8 GB of VRAM. Still a preview release, so expect rough edges in some workflows. US-built, Apache 2.0 licensed.
View all Arcee Trinity Nano 6B hardware options →About NVIDIA RTX 4070 Laptop (80-115W)
NVIDIA RTX 4070 Laptop (80-115W) has 8 GB at 256 GB/s. Street price: $0.
See all models NVIDIA RTX 4070 Laptop (80-115W) can run →Estimate method: Estimated from MoE architecture (active params per token), quantization size, and device bandwidth. Reference hardware source: huggingface.co (2026-03-14)
Performance varies by driver version, inference engine, quantization method, context length, and system configuration. Figures shown are estimates based on community benchmarks and may not reflect your exact setup. Product names are trademarks of their respective owners. OwnRig is independent and not affiliated with any hardware or AI model provider.