Hardware · Apple Silicon

What AI models can the Apple M1 (16 GB) run?

Unified memory: 16.0 GB
Usable for models: 10.7 GB
Memory bandwidth: 68 GB/s
FP16 compute: 2.6 TFLOPS
Released: 2020

379 / 621 LLMs run Best: Mellum2.1 Thinking (12B-A2.5B) 53 / 61 Image models run Best: FLUX.2 [klein] 4B 12 / 43 Video models run Best: LTX-Video 2B 64 / 70 Decision models run Best: GLiNER2.5 Decide

macOS lets the GPU use roughly two-thirds to three-quarters of unified memory by default, so we plan around that figure rather than the full 16.0 GB.

More about this hardware

Maker	Apple Silicon
Type	Apple silicon (system on a chip)
Chip	Apple M1

Apps that run models well on the Apple M1 (16 GB)

macOS

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

4 products with the Apple M1 (16 GB)

MacBook Air (M1, 2020)Apple · Laptop · 8 or 16 GB · $999–$1,449Product page (opens in a new tab)
MacBook Pro (13-inch, M1, 2020)Apple · Laptop · 8 or 16 GB · $1,299–$1,499Product page (opens in a new tab)
Mac mini (M1, 2020)Apple · Mini PC · 8 or 16 GB · $699–$899Product page (opens in a new tab)
iMac (24-inch, M1, 2021)Apple · Desktop · 8 or 16 GB · $1,299–$1,699Product page (opens in a new tab)

Best LLMs for the Apple M1 (16 GB)

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 82/100 (quality, fit, speed and memory use) sets the ranking.	Mellum2.1 Thinking (12B-A2.5B)JetBrains	`Q4_K_M`	9.0 GB	26.3 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 81/100 (quality, fit, speed and memory use) sets the ranking.	Ling 3.0 Tiny (8B-A1.3B)Ant Group (inclusionAI)	`Q5_K_M`	7.3 GB	39.5 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`	10.6 GB	5.0 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 78/100 (quality, fit, speed and memory use) sets the ranking.	Nemotron 3.5 Bolt E4BNVIDIA	`Q4_K_M`	6.5 GB	16.0 tok/s	Runs well
67Good quality (B) · 67 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking.	K2 Horizon 7BInstitute of Foundation Models	`Q3_K_M`	7.1 GB	10.4 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 77/100 (quality, fit, speed and memory use) sets the ranking.	Gemma 4 E4BGoogle	`Q4_K_M`	6.5 GB	16.0 tok/s	Runs well
49Fair quality (C) · 49 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.	LFM2.5 8B-A1BLiquid AI	`Q4_K_M`	6.7 GB	41.4 tok/s	Runs great
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`	9.7 GB	63.7 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 75/100 (quality, fit, speed and memory use) sets the ranking.	Nanbeige4.2 3BBOSS Zhipin (Nanbeige)	`Q4_K_M`	5.5 GB	17.3 tok/s	Runs well
49Fair quality (C) · 49 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking.	ERNIE 4.5 21B-A3B ThinkingBaidu	`Q2_K`	10.7 GB	35.2 tok/s	Runs welltight fit
58Good quality (B) · 58 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.	Gemma 4 E2BGoogle	`Q4_K_M`	4.6 GB	31.4 tok/s	Runs great
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`	7.2 GB	42.4 tok/s	Runs great

Best Image models for the Apple M1 (16 GB)

Quality	Model	Quant	Memory	Speed	Runs
76Great quality (A) · 76 of 100: how capable the model is at FP8, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking.	FLUX.2 [klein] 4BBlack Forest Labs	`FP8`	10.2 GB	23 s	Runs welltight fit
84Great quality (A) · 84 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking.	FLUX 3 Image KleinBlack Forest Labs	`Q4 GGUF`	10.2 GB	2.9 min	Very slowtight fit
78Great quality (A) · 78 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking.	Z-Image TurboAlibaba (Tongyi)	`Q4 GGUF`	10.1 GB	76 s	Slowtight fit
78Great quality (A) · 78 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.	FLUX.2 [klein] 9BBlack Forest Labs	`Q4 GGUF`	8.0 GB	58 s	Slowencoder unloaded after use
79Great quality (A) · 79 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking.	ERNIE-Image TurboBaidu	`Q4 GGUF`	7.4 GB	1.7 min	Slowencoder unloaded after use
76Great quality (A) · 76 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking.	Z-ImageAlibaba (Tongyi)	`Q4 GGUF`	10.1 GB	8.6 min	Very slowtight fit

Best Video models for the Apple M1 (16 GB)

Quality	Model	Quant	Memory	Speed	Runs
50Fair quality (C) · 50 of 100: how capable the model is at FP16, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking.	LTX-Video 2BLightricks	`FP16`	8.0 GB	11.1 min	Runs wellencoder unloaded after use
55Good quality (B) · 55 of 100: how capable the model is at FP16, whatever it runs on. Match score 62/100 (quality, fit, speed and memory use) sets the ranking.	Wan 2.1 T2V 1.3BAlibaba	`FP16`	8.4 GB	1.8 h	Very slowencoder unloaded after use
74Great quality (A) · 74 of 100: how capable the model is at FP8, whatever it runs on. Match score 62/100 (quality, fit, speed and memory use) sets the ranking.	HY-OmniWeaving (8.3B, unified video)Tencent	`FP8`	7.8 GB	4.4 h	Very slowCPU offload
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking.	Wan 2.1 VACE 1.3BAlibaba	`FP8`	8.0 GB	1.7 h	Very slowencoder unloaded after use
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking.	CogVideoX 5BZhipu AI	`FP8`	9.6 GB	72.1 min	Very slowtight fit · encoder unloaded after use

Best Decision models for the Apple M1 (16 GB)

Quality	Model	Quant	Memory	Speed	Runs
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking.	GLiNER2.5 DecideFastino	`Q8_0`	1.2 GB	89 ms	Runs great
76Great quality (A) · 76 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.	Llama Prompt Guard 2 86MMeta	`Q8_0`	1.0 GB	101 ms	Runs great
86Excellent quality (A+) · 86 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.	Jina Reranker v3.5Jina AI	`Q8_0`	2.3 GB	211 ms	Runs well
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking.	FRIDA-DecisionsSber AI	`Q8_0`	1.7 GB	146 ms	Runs well
74Great quality (A) · 74 of 100: how capable the model is at F16, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking.	GLiClass ModernBERT Large v3Knowledgator	`F16`	1.5 GB	83 ms	Runs great
84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking.	Jina Reranker v3Jina AI	`Q8_0`	2.3 GB	211 ms	Runs well
78Great quality (A) · 78 of 100: how capable the model is at F16, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking.	OpenAI Privacy FilterOpenAI	`F16`	3.8 GB	14 ms	Runs great
72Great quality (A) · 72 of 100: how capable the model is at F16, whatever it runs on. Match score 87/100 (quality, fit, speed and memory use) sets the ranking.	DeBERTa v3 Large Zero-shot v2.0Moritz Laurer	`F16`	1.6 GB	91 ms	Runs great

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.