aicanrun

AI Models for ROG Phone 9 Pro — What runs on 24GB

37 great · 28 slow · 44 won't fit
Chip
Snapdragon 8 Elite
Memory bandwidth
76.8 GB/s
NPU
45 TOPS
RAM options
16 / 24 GB
Usable for models
~20 GB
Year
2024

Specs checked against manufacturer and public documentation on .

What runs on the ROG Phone 9 Pro

All 109 models at their recommended quant, on the 24GB configuration. Select any row for the full report.

ModelParamsQuantNeedsSpeedVerdict
Qwen3 0.6B0.6BQ8_01.3 GB~57.6 tokens/s✓ Runs great
Qwen3 1.7B1.7BQ8_02.6 GB~19.2 tokens/s✓ Runs great
Llama 3.2 1B1.2BQ4_K_M1.5 GB~43.2 tokens/s✓ Runs great
Llama 3.2 3B3.2BQ4_K_M2.9 GB~17.3 tokens/s✓ Runs great
Gemma 3 1B1BQ4_K_M1.5 GB~43.2 tokens/s✓ Runs great
DeepSeek R1 Distill 1.5B1.8BQ4_K_M1.9 GB~31.4 tokens/s✓ Runs great
SmolLM2 1.7B1.7BQ4_K_M1.9 GB~31.4 tokens/s✓ Runs great
SmolLM3 3B3.1BQ4_K_M2.8 GB~18.2 tokens/s✓ Runs great
Qwen 3.5 2B2BQ4_K_M2.1 GB~26.6 tokens/s✓ Runs great
Gemma 4 26B-A4B26BQ4_017.5 GB~15.6 tokens/s✓ Runs great
Ternary Bonsai 8B8BQ2_03.5 GB~15.7 tokens/s✓ Runs great
Ternary Bonsai 4B4BQ2_02 GB~31.4 tokens/s✓ Runs great
Ternary Bonsai 1.7B1.7BQ2_01.2 GB~69.1 tokens/s✓ Runs great
Ministral 3 3B3BQ4_K_M3 GB~16.5 tokens/s✓ Runs great
LFM2.5 2.6B2.7BQ4_K_M2.6 GB~20.3 tokens/s✓ Runs great
LFM2.5 8B-A1B8BQ4_K_M6.6 GB~53.2 tokens/s✓ Runs great
LFM2.5-VL 3B3.1BQ4_K_M2.6 GB~20.3 tokens/s✓ Runs great
MiniCPM5-2B2.52BQ4_K_M2.5 GB~21.6 tokens/s✓ Runs great
GPT-OSS 20B21BMXFP414.8 GB~16.7 tokens/s✓ Runs great
OvisOCR2 0.8B0.8BQ4_K_M1.3 GB~57.6 tokens/s✓ Runs great
G9v3 3B3BQ4_K_M2.8 GB~18.2 tokens/s✓ Runs great
OneJev 0.8B0.8BQ4_K_M1.4 GB~49.4 tokens/s✓ Runs great
Tini Cybersec 8B-A1B8.5BQ4_K_M6.7 GB~56.5 tokens/s✓ Runs great
Ling 3.0 Tiny7.9BQ4_K_M6.3 GB~39.8 tokens/s✓ Runs great
Granite 4.2 3B3BQ4_K_M3.1 GB~15.7 tokens/s✓ Runs great
Qwen3 4B4BQ4_K_M3.5 GB~13.8 tokens/s✓ Runs great
Gemma 3 4B4.3BQ4_K_M3.5 GB~13.8 tokens/s✓ Runs great
Phi-4 Mini 3.8B3.8BQ4_K_M3.5 GB~13.8 tokens/s✓ Runs great
Qwen 3.5 4B4BQ4_K_M3.7 GB~12.8 tokens/s✓ Runs great
Agents-A1 4B4BQ4_K_M3.7 GB~12.8 tokens/s✓ Runs great
Nanbeige 4.2 3B4.2BQ4_K_M3.7 GB~12.8 tokens/s✓ Runs great
Nemotron 3 Nano 4B4BQ4_K_M3.8 GB~12.3 tokens/s✓ Runs great
AREX Turbo 4B4.5BQ4_K_M4 GB~11.9 tokens/s✓ Runs great
Fara 1.5 4B4.5BQ4_K_M4 GB~11.9 tokens/s✓ Runs great
Gemma 4 E2B2BQ4_K_M4 GB~11.1 tokens/s✓ Runs great
OneJev 4B4BQ4_K_M4.1 GB~11.1 tokens/s✓ Runs great
Bonsai 27B (1-bit)27BQ1_04.8 GB~9.1 tokens/s✓ Runs great
Mistral 7B v0.37.2BQ4_K_M5.7 GB~7.9 tokens/s! Runs, barely
DeepSeek R1 Distill 7B7.6BQ4_K_M6.1 GB~7.4 tokens/s! Runs, barely
Llama 3.1 8B8BQ4_K_M6.3 GB~7.1 tokens/s! Runs, barely
Ministral 8B8BQ4_K_M6.3 GB~7.1 tokens/s! Runs, barely
Qwen3 8B8.2BQ4_K_M6.4 GB~6.9 tokens/s! Runs, barely
Gemma 4 E4B4BQ4_K_M6.1 GB~6.9 tokens/s! Runs, barely
Ministral 3 8B8BQ4_K_M6.6 GB~6.6 tokens/s! Runs, barely
Ornith 1.0 9B9BQ4_K_M7.1 GB~6.2 tokens/s! Runs, barely
OneJev 9B9BQ4_K_M7.1 GB~6.2 tokens/s! Runs, barely
Granite 4.2 8B8BQ4_K_M6.7 GB~6.5 tokens/s! Runs, barely
Qwen 3.5 9B9BQ4_K_M7.2 GB~6.1 tokens/s! Runs, barely
GRM 3.2 Cliff 9B9.4BQ4_K_M7.5 GB~5.9 tokens/s! Runs, barely
Qwythos 9B v29BQ4_K_M7.2 GB~6.1 tokens/s! Runs, barely
grug 9B (ProCreations)9.4BQ4_K_M7.5 GB~5.9 tokens/s! Runs, barely
Fara 1.5 9B9.4BQ4_K_M7.5 GB~5.9 tokens/s! Runs, barely
UI-Mate 9B9BQ4_K_M7.4 GB~5.9 tokens/s! Runs, barely
LensVLM 9B9.4BQ4_K_M7.3 GB~6 tokens/s! Runs, barely
Gemma 3 12B12.2BQ4_K_M9.1 GB~4.7 tokens/s! Runs, barely
Gemma 4 12B12BQ4_08.8 GB~4.9 tokens/s! Runs, barely
Ternary Bonsai 27B27BQ2_08.4 GB~4.8 tokens/s! Runs, barely
Grug 12B12BQ4_K_M9.5 GB~4.5 tokens/s! Runs, barely
Ministral 3 14B14BQ4_K_M10.2 GB~4.2 tokens/s! Runs, barely
Qwen3 14B14.8BQ4_K_M11.1 GB~3.8 tokens/s! Runs, barely
Phi-4 14B14.7BQ4_K_M11.2 GB~3.8 tokens/s! Runs, barely
MiMo V2.6 Distill Qwen 9B9.4BQ8_011.2 GB~3.6 tokens/s! Runs, barely
Qwen 3.6 27B27BQ4_K_M18.5 GB~2.1 tokens/s! Runs, barely
OneJev 27B27BQ4_K_M19.8 GB~2.1 tokens/s! Runs, barely
Qwen3.8-27B-pi27.8BQ4_K_M19.9 GB~2.1 tokens/s! Runs, barely
Qwen 3.5 27B27BQ4_K_M20 GB—✕ Won't fit
Muse Glimmer 30B29.6BK_QUANT_17GB20.3 GB—✕ Won't fit
AREX-2 27B27BQ4_K_M20.6 GB—✕ Won't fit
Fara 1.5 27B27BQ4_K_M20.9 GB—✕ Won't fit
Qwen3.8 27B27BQ4_K_M20.8 GB—✕ Won't fit
UI-Mate 27B27BQ4_K_M20.9 GB—✕ Won't fit
Swift 1.5 Qwen3.8 27B27.8BQ4_K_M20.8 GB—✕ Won't fit
Granite 4.2 30B30BQ4_K_M21.3 GB—✕ Won't fit
Qwen3 30B A3B30.5BQ4_K_M22.3 GB—✕ Won't fit
Gemma 4 31B31BQ4_K_M22 GB—✕ Won't fit
Salience 1.5 Flash30BQ4_K_M22.3 GB—✕ Won't fit
Qwen 3.6 35B-A3B35BQ4_K_M23.9 GB—✕ Won't fit
Qwen3 32B32.8BQ4_K_M23.7 GB—✕ Won't fit
Laguna XS 2.133BQ4_K_M24.2 GB—✕ Won't fit
Ornith 1.0 35B-A3B35BQ4_K_M25.3 GB—✕ Won't fit
XYZ-Aquila mini 35B-A3B35BQ4_K_M25.5 GB—✕ Won't fit
Holo4 35B-A3B35BQ4_K_M25.4 GB—✕ Won't fit
KAT-Coder V2.5 Dev35BQ4_K_M25.5 GB—✕ Won't fit
Qwen 3.5 35B-A3B35BQ4_K_M26.2 GB—✕ Won't fit
Nemotron 3 Nano Omni 30B-A3B31BQ4_K_M26.3 GB—✕ Won't fit
BigBang V1 36B-A3B36BQ4_K_M26.1 GB—✕ Won't fit
Apodex 1.1 Mini35BQ4_K_M26 GB—✕ Won't fit
Nemotron 3 Nano 30B-A3B30BQ4_K_M28.5 GB—✕ Won't fit
Nemotron 3.5 Lightning 30B-A3B30BQ8_035.9 GB—✕ Won't fit
MiMo V2.6 Flash MOPD309BQ2_K154.7 GB—✕ Won't fit
Qwen3.8 2.4T-A95B2400BIQ4_XS1377.4 GB—✕ Won't fit
GLM-4.5V106BQ4_K_M74.8 GB—✕ Won't fit
GLM-4.5-Air106BQ4_K_M74.8 GB—✕ Won't fit
Ling 3.0 Flash124BQ4_K_M82.3 GB—✕ Won't fit
Ling 3.0 Flash Fin124BQ4_K_M91 GB—✕ Won't fit
Ling 3.0 Flash VL124.85BQ4_K_M92 GB—✕ Won't fit
Swift 1.5 Qwen3.8 Flash Next125BQ2_079.2 GB—✕ Won't fit
Qwen3.8-Flash-Next125BIQ4_XS107.7 GB—✕ Won't fit
GLM-5.3744BQ4_K_XL543.3 GB—✕ Won't fit
GLM-5.3-Flash320BQ4_K_XL232.7 GB—✕ Won't fit
Llama 3.3 70B70BQ4_K_M50.1 GB—✕ Won't fit
Ornith 1.0 397B397BQ4_K_M285.6 GB—✕ Won't fit
Hunyuan 3 (Hy3)298.8BQ4_K_M212.8 GB—✕ Won't fit
DeepSeek V4 Flash 0731284BQ4_K_XL163.6 GB—✕ Won't fit
DeepSeek V4 Flash Vision Exp284BQ4_K_XL183.3 GB—✕ Won't fit
Inkling952.4BQ8_0966.9 GB—✕ Won't fit
Inkling Small276BQ4_K_M190.5 GB—✕ Won't fit
LongCat Flash Chat561.9BIQ1_S159.6 GB—✕ Won't fit
Laguna S 2.1118BQ4_K_M109.7 GB—✕ Won't fit

~ = bandwidth-based estimate · ✓ = measured on real hardware

Best model by use case

Best for Chat
Qwen3 0.6B

Top everyday assistant & writing pick here — ~57.6 tokens/s at Q8_0, using 1.3 of ~20GB.

Best for Coding
MiniCPM5-2B

Top code completion & explain-this pick here — ~21.6 tokens/s at Q4_K_M, using 2.5 of ~20GB.

Best for Reasoning
DeepSeek R1 Distill 1.5B

Top math & step-by-step thinking pick here — ~31.4 tokens/s at Q4_K_M, using 1.9 of ~20GB.

FAQ

What is the biggest AI model the ROG Phone 9 Pro can run?

Qwen3.8-27B-pi (27.8B parameters) at Q4_K_M — it needs 19.9GB of the ~20GB usable on the 24GB ROG Phone 9 Pro, at ~2.1 tokens/s.

How much of the ROG Phone 9 Pro's 24GB RAM can AI models actually use?

About 20GB. Android keeps roughly 2–4GB for the system and resident apps, so of the 24GB about 20GB is actually available to a model.

Can the ROG Phone 9 Pro run Llama 3.1 8B?

Yes — at Q4_K_M it needs 6.3GB of the ~20GB usable and runs at ~7.1 tokens/s.

How fast is local AI on the ROG Phone 9 Pro?

The Snapdragon 8 Elite has 76.8GB/s of memory bandwidth, which is what decode speed scales with. Small models like Ternary Bonsai 1.7B reach ~69.1 tokens/s; larger 7–14B models land in the single digits. Anything above ~8 tokens/s feels smooth for chat.

Which quantization should I use on the ROG Phone 9 Pro?

Q4_K_M is the size/quality sweet spot for most models. For example, Qwen3 0.6B at Q8_0 takes 1.3GB of memory here. Only drop to Q3 or IQ4 if a model just misses fitting; Q8 rarely pays off on 24GB of RAM.

Is 24GB of RAM enough for local AI?

65 of the 109 models we track fit on the ROG Phone 9 Pro — 37 run great and 28 run with compromises. 44 models (mostly 12B+) don't fit at their recommended quant.