AREX 2
27.4B parameters · 256k context · Apache License 2.0 · released 2026-09-29
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In short
AREX 2 is an open model from BAAI with 27.4B parameters. At Q4_K_M, AREX 2 needs about 17 GB of memory at 8k context and 17 GB at 8k, counting the weights, the KV cache and runtime buffers. The cheapest hardware in Canada that runs AREX 2 fully in memory at 8k context is the AMD Radeon RX 7900 XTX, $1,455 at Amazon, at about 25 tok/s (estimated).
Updated . Speeds are estimates; how they are worked out.
Cheapest way to run it in Canada today
AMD Radeon RX 7900 XTX, new at Amazon
Runs AREX 2 at Q5_K_M fully in memory at 8k context, about 25 tok/sest.
$1,455
In stock, checked
What to run it on in Canada
Fully in memory at 8k context, priced at retailers today.
Cheapest
AMD Radeon RX 7900 XTX25tok/sest.Q5_K_M
$1,455
Best value
AMD Radeon RX 7900 XTX25tok/sest.Q5_K_M
$1,455
Fastest
NVIDIA GeForce RTX 509038tok/sest.Q8_0
$10,101
Mac
Mac Studio M3 Ultra 512GB18tok/sest.Q8_0
$28,000
All hardware that runs it
Everything we price, best value first. Two cards split the model by layers.
1 other card or machine we price cannot hold it at this context.
Memory needed
Weights, KV cache and runtime buffers at each context length (KV cache at fp16).
| Quant | File | @8k | @32k | @64k | @128k |
|---|---|---|---|---|---|
| Q4_K_Mgguf | 16.0 GB | 17.4 GB | 19.1 GB | 21.2 GB | 25.6 GB |
| Q5_K_Mgguf | 19.3 GB | 20.7 GB | 22.3 GB | 24.5 GB | 28.9 GB |
| Q6_Kgguf | 22.0 GB | 23.4 GB | 25.0 GB | 27.2 GB | 31.6 GB |
| Q8_0gguf | 26.7 GB | 28.1 GB | 29.7 GB | 31.9 GB | 36.3 GB |
Run it
Copy a command for the runtime you use.
- Q4_K_M
- Ollama
ollama run hf.co/bartowski/BAAI_AREX-2-GGUF:Q4_K_M - LM Studio
lms get bartowski/BAAI_AREX-2-GGUF@q4_k_m - llama.cpp
llama-server -hf bartowski/BAAI_AREX-2-GGUF:Q4_K_M
- Ollama
- Q5_K_M
- Ollama
ollama run hf.co/bartowski/BAAI_AREX-2-GGUF:Q5_K_M - LM Studio
lms get bartowski/BAAI_AREX-2-GGUF@q5_k_m - llama.cpp
llama-server -hf bartowski/BAAI_AREX-2-GGUF:Q5_K_M
- Ollama
- Q6_K
- Ollama
ollama run hf.co/bartowski/BAAI_AREX-2-GGUF:Q6_K - LM Studio
lms get bartowski/BAAI_AREX-2-GGUF@q6_k - llama.cpp
llama-server -hf bartowski/BAAI_AREX-2-GGUF:Q6_K
- Ollama
- Q8_0
- Ollama
ollama run hf.co/bartowski/BAAI_AREX-2-GGUF:Q8_0 - LM Studio
lms get bartowski/BAAI_AREX-2-GGUF@q8_0 - llama.cpp
llama-server -hf bartowski/BAAI_AREX-2-GGUF:Q8_0
- Ollama
Notes
Dense 27B multimodal model fine-tuned from Qwen3.8-27B; requires a recent Transformers release with Qwen3.8 support. The card says to follow the Qwen base model's terms and notices.
Questions
- How much VRAM does AREX 2 need?
- At Q4_K_M, AREX 2 needs about 17 GB of memory at 8k context and 17 GB at 8k, counting the weights, the KV cache and runtime buffers.
- What is the best GPU for running AREX 2 locally?
- The cheapest hardware in Canada that runs AREX 2 fully in memory at 8k context is the AMD Radeon RX 7900 XTX, $1,455 at Amazon, at about 25 tok/s (estimated). The fastest we price is the NVIDIA GeForce RTX 5090, at about 38 tok/s.
- What is the cheapest way to run AREX 2 in Canada today?
- The AMD Radeon RX 7900 XTX, $1,455 new at Amazon, in stock: it runs AREX 2 at Q5_K_M fully in memory at 8k context, at about 25 tok/s (estimated).
- Can I run AREX 2 on a 16 GB GPU?
- Only partly: at 8k context it does not fit in 16 GB, so part of it runs from system RAM and it slows to about 8 tok/s on the AMD Radeon RX 9060 XT 16GB (estimated).
- Can I run AREX 2 on a 24 GB GPU?
- Yes: at Q6_K it fits fully in 24 GB at 8k context. On the NVIDIA GeForce RTX 3090 Ti it runs at about 26 tok/s (estimated).
- How do I run AREX 2 locally?
- With Ollama: ollama run hf.co/bartowski/BAAI_AREX-2-GGUF:Q4_K_M (the Q4_K_M build). LM Studio and llama.cpp commands are on this page.
- What licence is AREX 2 released under?
- Apache License 2.0, which allows commercial use.