Arcee Trinity Nano 6B on Apple M2 (8GB Unified)
Yes — M2 (8GB Unified) handles Arcee Trinity Nano 6B well at Q5_K_M — 18 tok/s. Solid daily-driver performance on 8 GB VRAM.
Model Size
6B
Device VRAM
8 GB
Bandwidth
100 GB/s
Quantization
Q5_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Arcee Trinity Nano 6B on Apple M2 (8GB Unified) at Q5_K_M. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q5_K_M | 18 tok/s | – | ✓ Yes | Good | estimated |
Notes
Q5_K_M
Conservative estimate. Uses Q5_K_M (5.4GB), the highest-quality format that fits within ~5.5GB usable memory.
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 Apple M2 (8GB Unified)
Apple M2 (8GB Unified) has 8 GB at 100 GB/s. Available in MacBook Air 13" (2022), MacBook Air 15" (2023), MacBook Pro 13" (2022).
See all models Apple M2 (8GB Unified) can run →Estimate method: Conservative estimate anchored to m4-16gb with bandwidth scaling, quantization-size adjustment, and generation damping. Reference hardware source: github.com (2026-04-18)
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.