Arcee Trinity Large Thinking 400B on Apple M4 Ultra (192GB)
M4 Ultra (192GB) cannot run Arcee Trinity Large Thinking 400B. 192 GB VRAM is insufficient at any quantization level.
Model Size
399B
Device VRAM
192 GB
Bandwidth
819 GB/s
Quantization
Q3_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Arcee Trinity Large Thinking 400B on Apple M4 Ultra (192GB) 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 | 3 tok/s | 2000ms | ✗ Offload | Not viable | estimated |
Notes
Q3_K_M
398B MoE (13B active). Q3_K_M ~195GB exceeds 192GB unified memory. Requires partial CPU offloading — barely misses fitting. Performance severely degraded.
About Arcee Trinity Large Thinking 400B
Arcee Trinity Large Thinking 400B (399B) is a chat, coding, ai coding, reasoning, multi-purpose model. Arcee AI's largest Mixture-of-Experts reasoning model. 399B total parameters with only 13B active per token (256 experts, 4 selected; 1.56% routing, one of the sparsest MoE architectures in production). 512K native context. Trained on 17 trillion tokens across 2,048 B300 GPUs. Post-trained with extended chain-of-thought reasoning and agentic reinforcement learning. Ranks #2 on PinchBench behind Claude Opus-4.6. Requires a GB300 (288 GB) for full in-VRAM inference; even the M4 Ultra 192 GB cannot fit Q3_K_M. US-built, Apache 2.0 licensed.
View all Arcee Trinity Large Thinking 400B hardware options →About Apple M4 Ultra (192GB)
Apple M4 Ultra (192GB) has 192 GB at 819 GB/s. Available in Mac Studio, Mac Pro.
See all models Apple M4 Ultra (192GB) 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.