Arcee Trinity Mini 26B on NVIDIA RTX 4080 Laptop (120-150W)
RTX 4080 Laptop (120-150W) cannot run Arcee Trinity Mini 26B. 12 GB VRAM is insufficient at any quantization level.
Model Size
26B
Device VRAM
12 GB
Bandwidth
384 GB/s
Quantization
Q3_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Arcee Trinity Mini 26B on NVIDIA RTX 4080 Laptop (120-150W) at Q3_K_M. This pairing has limitations — check the rating and notes below.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q3_K_M | 6 tok/s | 2000ms | ✗ Offload | Not viable | estimated |
Notes
Q3_K_M
26B MoE (3B active). Q3_K_M 13GB exceeds 12GB VRAM. Requires CPU offloading.
About Arcee Trinity Mini 26B
Arcee Trinity Mini 26B (26B) is a chat, coding, ai coding, reasoning, multi-purpose model. Arcee AI's mid-range Mixture-of-Experts reasoning model. 26B total parameters with only 3B active per token (128 experts, 8 selected + 1 shared). Trained on 10 trillion tokens via Datology partnership. Handles math, code, and agentic tasks well; fits at Q4_K_M on a 24 GB GPU. The most practical Trinity variant for consumer hardware. US-built, Apache 2.0 licensed.
View all Arcee Trinity Mini 26B hardware options →About NVIDIA RTX 4080 Laptop (120-150W)
NVIDIA RTX 4080 Laptop (120-150W) has 12 GB at 384 GB/s. Street price: $0.
See all models NVIDIA RTX 4080 Laptop (120-150W) 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.