Hardware · Motorola

What AI models can the Motorola razr ultra 2025 / razr 60 ultra / razr 70 ultra run?

RAM: 16.0 GB
Storage: 512 GB – 1 TB
One app can use: 9.9 GB
Memory bandwidth: 77 GB/s
FP16 compute: 3.4 TFLOPS
Released: 2025

342 / 622 LLMs run Best: Mellum2.1 Thinking (12B-A2.5B) 0 / 61 Image models run No Android app 0 / 43 Video models run No Android app 0 / 70 Decision models run No Android app

Every Motorola razr ultra 2025 / razr 60 ultra / razr 70 ultra has 16 GB of RAM, whatever its storage (512 GB or 1 TB). A model runs in RAM (the 16.0 GB here), not in storage. Storage (512 GB or 1 TB on this version) only keeps the downloaded files, and even the smallest size has room for several. Android lets one app hold only part of the RAM before it closes the app, so we plan around 9.9 GB; a model bigger than that won’t run. Phone apps such as PocketPal AI download a model once, then run it with no connection.

More about this hardware

Maker	Motorola
Type	Mobile device (system on a chip)
App share of memory	62% (what one app can typically hold before the system closes it)
Chip	Snapdragon 8 Elite
RAM type	16 GB LPDDR5X 9600 Mbps (Motorola)
Versions sold	razr ultra 2025 / razr 60 ultra: 16 GB RAM with 512 GB or 1 TB razr 70 ultra: 16 GB RAM with 512 GB
Bandwidth figure	76.8 GB/s, as the maker states it
Note	Snapdragon 8 Elite (Adreno 830); LPDDR5X at 9600 Mbps (76.8 GB/s), as Motorola states. 1 TB from motorola.com only. The 2026 razr 70 ultra keeps the chip and 16 GB.
Maker’s specifications	www.motorola.com

Apps that run models well on the Motorola razr ultra 2025 / razr 60 ultra / razr 70 ultra

Android

For a typical model that fits in memory. Each model page picks the best app for that model on this hardware. All apps

Best LLMs for the Motorola razr ultra 2025 / razr 60 ultra / razr 70 ultra

Quality	Model	Quant	Memory	Speed	Runs
66Good quality (B) · 66 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking.	Mellum2.1 Thinking (12B-A2.5B)JetBrains	`Q4_K_M`	8.1 GB	25.4 tok/s	Runs well
58Good quality (B) · 58 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking.	Ling 3.0 Tiny (8B-A1.3B)Ant Group (inclusionAI)	`Q5_K_M`	6.4 GB	38.2 tok/s	Runs great
80Great quality (A) · 80 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking.	Gemma 4 12BGoogle	`Q5_K_M`	9.8 GB	4.8 tok/s	Slowtight fit
66Good quality (B) · 66 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking.	Nemotron 3.5 Bolt E4BNVIDIA	`Q4_K_M`	5.6 GB	15.4 tok/s	Runs well
64Good quality (B) · 64 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.	Gemma 4 E4BGoogle	`Q4_K_M`	5.6 GB	15.4 tok/s	Runs well
49Fair quality (C) · 49 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.	Maple Preview (20B-A1B)DeepGrove	`Q2_K`	8.8 GB	61.7 tok/s	Runs welltight fit
49Fair quality (C) · 49 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking.	LFM2.5 8B-A1BLiquid AI	`Q4_K_M`	5.9 GB	40.0 tok/s	Runs great
49Fair quality (C) · 49 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking.	ERNIE 4.5 21B-A3B ThinkingBaidu	`Q2_K`	9.8 GB	34.0 tok/s	Runs welltight fit
64Good quality (B) · 64 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking.	Nanbeige4.2 3BBOSS Zhipin (Nanbeige)	`Q4_K_M`	4.6 GB	16.6 tok/s	Runs well
43Fair quality (C) · 43 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking.	Granite 4.0 H Tiny (7B-A1B)IBM	`Q6_K`	6.4 GB	41.0 tok/s	Runs great
50Fair quality (C) · 50 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking.	Kimi-VL A3B Thinking 2506Moonshot AI	`Q3_K_M`	8.9 GB	27.3 tok/s	Runs welltight fit
43Fair quality (C) · 43 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking.	Ling Mini 2.0 (16B-A1.4B)Ant Group (inclusionAI)	`Q3_K_M`	8.9 GB	53.1 tok/s	Runs welltight fit

Best Image models for the Motorola razr ultra 2025 / razr 60 ultra / razr 70 ultra

None of the image models in our catalog fit in this much memory.

Best Video models for the Motorola razr ultra 2025 / razr 60 ultra / razr 70 ultra

None of the video models in our catalog fit in this much memory.

Best Decision models for the Motorola razr ultra 2025 / razr 60 ultra / razr 70 ultra

None of the decision models in our catalog fit in this much memory.

Best LLMs by task on this hardware Open in Model Finder

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.