AREX-2 27B
AREX-2 27B loads in 17.2 GB at Q4_K_M, comfortably from 32 GB of memory, Macs included, starting at the MacBook Pro M5 Pro 48GB. Below is the memory math we ran for it, the smallest card that fits, and the fastest machine we track.
- Parameters
- 27.4B
- Format
- Q4_K_M
- Min memory
- 32 GB
- Best for
- Agents, Deep research, Coding
How much memory does AREX-2 27B need?
AREX-2 27B is a 27.4B dense model built for agents, deep research, coding. The weights alone take 17.2 GB at Q4_K_M; add context and the OS, and it belongs in the 32 GB memory class. Every number below comes from the ModelFit engine: speeds are estimates, labeled est., because we do not benchmark hardware ourselves.
KV = fp16 estimate (q8_0 cache roughly halves it). "Comfortable" = weights + KV within the engine's tiered budget (~70-85% of memory).
Which machines run AREX-2 27B?
- Smallest GPU
- AMD Radeon RX 7900 XTest. 36 tok/s · 20 GB VRAMtypical error 50%
- Fastest
- NVIDIA GeForce RTX 5090est. 87 tok/stypical error 5%
- Runs on a Mac?
- MacBook Pro M5 Pro 48GBest. 16 tok/stypical error 10%
Verdicts come from the same engine that powers our fit checker: memory capacity first, bandwidth for speed. How we compute these numbers · What typical error means · Hugging Face model card
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Frequently asked questions
How much memory does AREX-2 27B need?
17.2 GB for the Q4_K_M weights, plus ~1.0 GB of KV-cache at 16k context, about 18.2 GB total. Comfortable from 32 GB of VRAM or unified memory.
Does AREX-2 27B run on a Mac?
Yes, from the MacBook Pro M5 Pro 48GB (est. 16 tok/s, typical error 10%). Unified memory means the RAM budget is the only limit.
What is the smallest GPU for AREX-2 27B?
The AMD Radeon RX 7900 XT (20 GB VRAM) is the smallest tracked card that runs AREX-2 27B comfortably, est. 36 tok/s, typical error 50%.
Cite this page
ModelFit: AREX-2 27B, specs, memory math and hardware verdicts. https://modelfit.io/models/arex-2-27b/ (dataset updated 2026-10-24, CC BY 4.0).