Apple M3 Pro (36GB) vs Apple M4 Pro (24GB)
Side-by-side local AI comparison: VRAM, memory bandwidth, model compatibility, and estimated tokens per second across 110 open-weight models.
Quick verdict
Apple M3 Pro (36GB) wins for local AI inference. It has 12 GB more VRAM and -45.1% more memory bandwidth, runs 60 models natively (vs 50), and exclusively fits 10 models the other cannot.
Specs comparison
| Spec | Apple M3 Pro (36GB) | Apple M4 Pro (24GB) |
|---|---|---|
| VRAM | 36 GB unified | 24 GB unified |
| Memory type | LPDDR5 | LPDDR5X |
| Bandwidth | 150 GB/s | 273 GB/s(+82%) |
| CPU cores | 12 (6P + 6E) | 12 (8P + 4E) |
| Architecture | Apple M3 Pro | Apple M4 Pro |
| Backend | METAL | METAL |
| Tier | Laptop | Laptop |
| Released | 2023 | 2024 |
| Models (native) | 60 | 50 |
Estimated tokens per second
Computed from memory bandwidth and model active-parameter weight. Assumes model fits natively in VRAM.
| Model | Apple M3 Pro (36GB) | Apple M4 Pro (24GB) | Delta |
|---|---|---|---|
| Llama 3.3 70B Instruct(70B) | N/A | N/A | N/A |
| Qwen 3.6 27B(27B) | 5.3 t/s(Q6_K) | 16.1 t/s(Q3_K_M) | -45%at Q3_K_M |
| Llama 3.1 8B Instruct(8B) | 7 t/s(BF16) | 22.8 t/s(Q8_0) | -45%at Q8_0 |
| Qwen 2.5 7B Instruct(7.6B) | 7.7 t/s(BF16) | 25.5 t/s(Q8_0) | -45%at Q8_0 |
Delta is Apple M3 Pro (36GB) relative to Apple M4 Pro (24GB), compared at the highest quantization that fits natively on both cards.
Only Apple M3 Pro (36GB) can run(10)
Only Apple M4 Pro (24GB) can run(0)
No exclusive models: Apple M3 Pro (36GB) can run everything Apple M4 Pro (24GB) can.
Both run natively(50)
These models fit in VRAM on both GPUs. Bandwidth determines which runs them faster.
- Qwen 3.5 35B-A3B (MoE)39.3 t/svs67.6 t/s
- Qwen 3.6 35B-A3B (MoE)39.3 t/svs67.6 t/s
- Ornith 1.5 35B-A3B (MoE)39.3 t/svs67.6 t/s
- Qwen3 32B4.9 t/svs15.8 t/s
- Gemma 4 31B5.1 t/svs16.5 t/s
- Qwen3 30B-A3B (MoE)28.5 t/svs51.3 t/s
- Muse Glimmer 30B5.2 t/svs16.1 t/s
- Gemma 2 27B Instruct5.3 t/svs16.2 t/s
- Gemma 3 27B Instruct5.1 t/svs18.5 t/s
- Qwen 3.6 27B5.3 t/svs16.1 t/s
- UI-Mate 27B5.3 t/svs16.1 t/s
- Bonsai 27B15.5 t/svs28.2 t/s
- Bonsai 2 27B18.6 t/svs33.9 t/s
- Qwen 3.8 27B5.3 t/svs16.1 t/s
- Gemma 4 26B (MoE)28 t/svs59.9 t/s
- Mistral Small 3.1 24B Instruct5.7 t/svs16.9 t/s
- +34 more on both
Which should you choose?
Choose Apple M3 Pro (36GB) if:
- • You need to run larger models (>24 GB VRAM)
Choose Apple M4 Pro (24GB) if:
- • Faster token generation is the priority
- • You want the newer architecture and longer driver support lifecycle
Frequently asked questions
- Which is better for local AI, the Apple M3 Pro (36GB) or Apple M4 Pro (24GB)?
- For local AI inference, the Apple M3 Pro (36GB) has the edge. It offers 36 GB VRAM (vs 24 GB) and 150 GB/s bandwidth (vs 273 GB/s), letting it run 60 models natively in VRAM vs 50 for its rival.
- How much VRAM does the Apple M3 Pro (36GB) have vs the Apple M4 Pro (24GB)?
- The Apple M3 Pro (36GB) has 36 GB of LPDDR5 at 150 GB/s. The Apple M4 Pro (24GB) has 24 GB of LPDDR5X at 273 GB/s. The Apple M3 Pro (36GB) has 12 GB more VRAM, allowing it to run 10 models the Apple M4 Pro (24GB) cannot fit natively.
- Can the Apple M3 Pro (36GB) run Llama 3.3 70B?
- The Apple M3 Pro (36GB) does not have enough VRAM to run Llama 3.3 70B.
- Can the Apple M4 Pro (24GB) run Llama 3.3 70B?
- The Apple M4 Pro (24GB) does not have enough VRAM to run Llama 3.3 70B.
- What is the difference between the Apple M3 Pro (36GB) and Apple M4 Pro (24GB) for AI?
- The key difference for AI inference is VRAM and memory bandwidth. The Apple M3 Pro (36GB) has 36 GB VRAM at 150 GB/s (METAL backend). The Apple M4 Pro (24GB) has 24 GB VRAM at 273 GB/s (METAL backend). VRAM determines which models fit; bandwidth determines tokens per second. The Apple M3 Pro (36GB) runs 60 models natively vs 50 for the Apple M4 Pro (24GB).