How much faster is the M5 chip than M1 for AI?

According to LLMCheck benchmarks, the M5 Max generates approximately 3x more tokens per second than the M1 Max on the same model. The base M5 is roughly 2x faster than the base M1. The primary driver is memory bandwidth: M5 Max delivers ~600 GB/s versus M1 Max's ~400 GB/s, plus architectural improvements in GPU compute and Neural Engine.

Is the M4 Pro good enough for local AI on Mac?

Yes. According to LLMCheck testing, the M4 Pro with 48 GB Unified Memory runs 9B models at ~50 tok/s (comfortable conversational speed) and fits models up to 30B parameters. It represents the best value for most users who want capable local AI without paying for Max or Ultra chips. LLMCheck rates it the sweet spot for developers and power users.

Is the M2 Ultra still worth buying for AI in 2026?

According to LLMCheck benchmarks, the M2 Ultra with 192 GB remains the only consumer Mac capable of running 120B+ parameter models locally. Its ~800 GB/s memory bandwidth delivers ~110 tok/s on 9B models and ~25 tok/s on 70B models. However, it is only available in the now-discontinued Mac Studio/Mac Pro form factor. For new purchases, the M5 Max 128 GB offers better value for most AI workloads.

Hardware Updated March 24, 2026 · 10 min read

Apple Silicon for AI: M1 vs M2 vs M3 vs M4 vs M5 Compared

Q: Which Apple Silicon chip is best for running local AI?

According to LLMCheck benchmarks, the M5 Max with 128 GB Unified Memory is the fastest consumer chip for AI, generating ~100 tok/s on 9B models and ~20 tok/s on 70B models. For best value, the M4 Pro with 48 GB offers ~50 tok/s on 9B models at roughly half the price. The M2 Ultra remains the most capable for very large models (120B+) with its 192 GB max RAM.

Q: Why does memory bandwidth matter more than GPU cores for AI?

During LLM inference, the model's full weights must be read from memory for every single token generated. Memory bandwidth (GB/s) determines how fast this read happens. According to LLMCheck benchmarks, a chip with 600 GB/s bandwidth generates roughly 3x more tok/s than one with 200 GB/s — regardless of GPU core count. This is why the M5 Max (40 GPU cores, 600 GB/s) vastly outperforms the base M3 (10 GPU cores, 200 GB/s).

Q: Can I run 70B parameter models on a MacBook Air?

No. A 70B model at Q4 quantization requires approximately 40 GB of free memory. MacBook Air models max out at 24 GB (M3/M4 Air), which is only enough for models up to about 14B parameters. According to LLMCheck, the minimum hardware for 70B models is a 64 GB Mac — typically an M4 Max MacBook Pro or M4 Mac Mini with max RAM.

Q: What is the best budget Mac for AI in 2026?

According to LLMCheck, the best budget Mac for AI is the Mac Mini with M4 chip and 16 GB RAM (starting at $599). It runs 9B models like Qwen 3.5 9B at ~35 tok/s — fast enough for comfortable AI conversations. For slightly more capability, the M4 Pro Mac Mini with 24 GB ($1,399) runs models up to 14B parameters and delivers ~50 tok/s on 9B models.

According to LLMCheck benchmarks, the M5 Max with 128 GB is the fastest consumer chip for local AI at ~100 tok/s on 9B models. The best value is the M4 Pro 48 GB at ~50 tok/s. Memory bandwidth is the #1 predictor of AI speed — the M5 Max (~600 GB/s) delivers 3x the tok/s of a base M3 (~200 GB/s). Every generation brings 15-30% improvement.

The Complete Apple Silicon AI Benchmark Table

According to LLMCheck testing, this table shows estimated inference speed across every major Apple Silicon variant. All speeds measured with Qwen 3.5 9B at Q4_K_M quantization unless noted.

Chip	GPU Cores	Bandwidth	Max RAM	9B tok/s	30B tok/s	70B tok/s
M5 Generation (2025-2026)
M5 Max	40	~600 GB/s	128 GB	~100	~35	~20
M5 Pro	20	~300 GB/s	48 GB	~55	~20	N/A
M5	10	~150 GB/s	32 GB	~30	N/A	N/A
M4 Generation (2024-2025)
M4 Max	40	~546 GB/s	128 GB	~80	~28	~15
M4 Pro	20	~273 GB/s	48 GB	~50	~18	N/A
M4	10	~120 GB/s	32 GB	~25	N/A	N/A
M3 Generation (2023-2024)
M3 Max	40	~400 GB/s	128 GB	~65	~22	~12
M3 Pro	18	~200 GB/s	36 GB	~35	~12	N/A
M3	10	~100 GB/s	24 GB	~18	N/A	N/A
M2 Generation (2022-2023)
M2 Ultra	76	~800 GB/s	192 GB	~110	~38	~25
M2 Max	38	~400 GB/s	96 GB	~60	~20	~10
M2 Pro	19	~200 GB/s	32 GB	~32	N/A	N/A
M2	10	~100 GB/s	24 GB	~16	N/A	N/A
M1 Generation (2020-2022)
M1 Ultra	64	~800 GB/s	128 GB	~90	~30	~18
M1 Max	32	~400 GB/s	64 GB	~50	~16	~8
M1 Pro	16	~200 GB/s	32 GB	~28	N/A	N/A
M1	8	~68 GB/s	16 GB	~12	N/A	N/A

N/A = model requires more RAM than the chip supports. According to LLMCheck, a model needs approximately 1.2-1.5x its file size in available Unified Memory (after macOS overhead of ~4-6 GB).

The Key Insight: Memory Bandwidth Determines Speed

According to LLMCheck benchmarks, memory bandwidth has the strongest correlation with AI inference speed — stronger than GPU core count, Neural Engine TOPS, or chip generation. Here's why:

During token generation, the entire model is read from memory for every single token. A 9B model at Q4 = ~5.5 GB read per token. At 100 tok/s, that's 550 GB/s of sustained memory reads — nearly saturating the M5 Max's ~600 GB/s bandwidth. This is why bandwidth is the bottleneck, not compute.

LLMCheck testing shows this relationship holds across all Apple Silicon chips: double the bandwidth, roughly double the tok/s.

Best Value Recommendations by Budget

Budget	Best Mac	Chip / RAM	9B tok/s	Max Model Size
$599	Mac Mini	M4 / 16 GB	~25	9B (Q4)
$1,399	Mac Mini	M4 Pro / 24 GB	~50	14B (Q4)
$2,499	MacBook Pro 16"	M5 Pro / 48 GB	~55	30B MoE
$3,499+	MacBook Pro 16"	M5 Max / 64 GB	~100	35B MoE
$4,999+	MacBook Pro 16"	M5 Max / 128 GB	~100	70B (Q4)

LLMCheck's top pick for most users: M4 Pro Mac Mini with 24 GB ($1,399). Runs Qwen 3.5 9B at ~50 tok/s — fast, smooth conversational AI for under $1,500. Upgrade to 48 GB if you want to run 30B MoE models.

Generation-Over-Generation Improvement

According to LLMCheck benchmarks, each Apple Silicon generation brings meaningful AI performance gains:

Upgrade Path	Bandwidth Gain	tok/s Gain	Worth It?
M1 Max → M2 Max	0% (same)	~20%	No (arch gains only)
M2 Max → M3 Max	0% (same)	~8%	No
M3 Max → M4 Max	+37%	+23%	Yes
M4 Max → M5 Max	+10%	+25%	Yes (Neural Accel.)
M1 → M5 (base)	+120%	+150%	Absolutely
M1 Max → M5 Max	+50%	+100%	Yes

LLMCheck recommends upgrading if you're gaining 30%+ bandwidth or jumping 2+ generations. Skipping one generation (e.g., M3 to M5) typically delivers the best value.

Which Models Run on Which Chips?

According to LLMCheck's leaderboard data, here's what your Mac can handle:

Your RAM	Best Models (Q4)	Max Params	Experience
8 GB	Phi-4 Mini, Llama 3.2 3B	~4B	Fast chat, basic tasks
16 GB	Qwen 3.5 9B, DeepSeek R1 8B	~9B	Strong general-purpose AI
24 GB	Qwen 3 30B-A3B (MoE)	~14B dense / 30B MoE	Advanced reasoning
32 GB	Qwen 3.5 35B (MoE)	~20B dense / 35B MoE	Near-frontier capability
48 GB	Llama 3.3 70B (partial offload)	~35B dense	High-end reasoning
64 GB	Llama 4 Scout, DeepSeek R1 70B	~70B	Deep reasoning, research
128 GB	Qwen 3.5 122B, Llama 3.1 405B (Q2)	~122B	Frontier-class
192 GB (Ultra)	Full Llama 3.1 405B (Q4)	~400B+	Server-class on desktop

LLMCheck Research Team

We benchmark local AI models on real Apple Silicon hardware. Our database covers 42+ models across 12+ chip variants with standardized tok/s measurements using Ollama, LM Studio, and MLX.

Frequently Asked Questions

Which Apple Silicon chip is best for running local AI?

According to LLMCheck benchmarks, the M5 Max with 128 GB is the fastest at ~100 tok/s on 9B models. For best value, the M4 Pro 48 GB offers ~50 tok/s at roughly half the price. The M2 Ultra remains best for very large models (120B+) with its 192 GB max RAM.

How much faster is the M5 than M1 for AI?

According to LLMCheck benchmarks, the M5 Max generates approximately 3x more tok/s than the M1 Max on the same model. The base M5 is roughly 2x faster than the base M1, driven primarily by higher memory bandwidth and architectural improvements.

Is the M4 Pro good enough for local AI?

Yes. According to LLMCheck testing, the M4 Pro with 48 GB runs 9B models at ~50 tok/s and fits models up to 30B parameters. LLMCheck rates it the best value chip for developers and power users who want capable local AI.

Why does memory bandwidth matter more than GPU cores?

During LLM inference, the full model weights must be read from memory for every token generated. Memory bandwidth (GB/s) determines how fast this happens. According to LLMCheck benchmarks, a chip with 600 GB/s bandwidth generates roughly 3x more tok/s than one with 200 GB/s.

Can I run 70B parameter models on a MacBook Air?

No. A 70B model at Q4 needs ~40 GB free. MacBook Air maxes at 24 GB. According to LLMCheck, the minimum for 70B models is 64 GB — typically M4/M5 Max MacBook Pro or Mac Mini with max RAM.

What is the best budget Mac for AI in 2026?

According to LLMCheck, the Mac Mini M4 16 GB at $599 is the best budget option. It runs Qwen 3.5 9B at ~25 tok/s. The M4 Pro Mac Mini at $1,399 doubles the speed to ~50 tok/s with room for larger models.

Is the M2 Ultra still worth it for AI in 2026?

According to LLMCheck, the M2 Ultra 192 GB remains the only consumer Mac for 120B+ models. Its ~800 GB/s bandwidth delivers ~110 tok/s on 9B. However, for new purchases, M5 Max 128 GB offers better value for most workloads.

Find the Right Model for Your Chip

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