Mac mini M4 Pro 48GB vs NVIDIA GeForce RTX 4080 Super
For running models locally, priced in Germany. At 8k context the first runs 58 models fully in memory, the second 41.
In short
The Mac mini M4 Pro 48GB has more memory for models: 48 GB against 16 GB. At 8k context the Mac mini M4 Pro 48GB runs 58 of the models we track fully in memory and the NVIDIA GeForce RTX 4080 Super 41; only the Mac mini M4 Pro 48GB holds Qwen 3.8 27B. On the models both run fully in memory, the NVIDIA GeForce RTX 4080 Super is about 2.6× as fast as the Mac mini M4 Pro 48GB (estimated, median across models). In Germany the Mac mini M4 Pro 48GB costs 2.649 € at eBay (used) and the NVIDIA GeForce RTX 4080 Super 1.990 € at Amazon: the NVIDIA GeForce RTX 4080 Super is 659 € cheaper.
Updated . Speeds are estimates; how they are worked out.
Specifications
| Spec | Mac mini M4 Pro 48GB | NVIDIA GeForce RTX 4080 Super |
|---|---|---|
| Chip | Apple M4 Pro (20-core GPU) | – |
| Memory bus | 256-bit | 256-bit |
| Memory bandwidth | 273 GB/s | 736 GB/s |
| FP16 compute | 8.08 TFLOPS | 104 TFLOPS |
| Software | Metal | CUDA |
| Unified memory | 48 GB | – |
| GPU can use by default | 36 GB | – |
| GPU can use, tuned | 40 GB | – |
| Operating system | macos | – |
| Processor | M4 Pro 14-core | – |
| Storage | 512 GB | – |
| GPU | – | GeForce RTX 4080 Super |
| Memory | – | 16 GB GDDR6X |
| Board power | – | 320 W |
| PCIe generation | – | Gen 4 |
| PCIe lanes | – | x16 |
What each runs
Estimated decode speed with the most precise quant that fits each one est.
| Model | Mac mini M4 Pro 48GB | NVIDIA GeForce RTX 4080 Super |
|---|---|---|
| Qwen 3.8 27B | 6tok/sQ8_0 | offload |
| Qwen 3.6 27B | 6tok/sQ8_0 | offload |
| Gemma 4 31B | 5tok/sQ8_0 | offload |
| Qwen 3.6 35B-A3B | 32tok/sQ8_0 | offload |
| Qwen 3.5 27B | 6tok/sQ8_0 | offload |
| Gemma 4 26B-A4B | 23tok/sQ8_0 | offload |
| Qwen 3.5 35B-A3B | 32tok/sQ8_0 | offload |
| GLM 4.7 Flash | 19tok/sQ8_0 | offload |
| Devstral Small 2 24B | 7tok/sQ8_0 | 29tok/sQ4_K_M |
| Nemotron 3.5 Lightning 30B-A3B | 31tok/sUD-Q6_K_XL | offload |
| Kimi Linear 48B-A3B | 47tok/sQ5_K_M | offload |
| gpt-oss 20B | 40tok/sMXFP4 | 104tok/sMXFP4 |
| Qwen3 Coder 30B-A3B | 27tok/sQ8_0 | offload |
| Qwen3 32B | 5tok/sQ8_0 | offload |
| Gemma 4 12B | 14tok/sQ8_0 | 35tok/sQ8_0 |
| Qwen 3.5 9B | 18tok/sQ8_0 | 46tok/sQ8_0 |
| Mistral Small 3.2 24B | 7tok/sQ8_0 | 29tok/sQ4_K_M |
| Gemma 3 27B | 6tok/sQ8_0 | offload |
| DeepSeek R1 Distill Qwen 32B | 5tok/sQ8_0 | offload |
| Ministral 3 14B | 11tok/sQ8_0 | 29tok/sQ8_0 |
| Qwen3 14B | 10tok/sQ8_0 | 34tok/sQ6_K |
| DeepSeek R1 0528 Qwen3 8B | 18tok/sQ8_0 | 46tok/sQ8_0 |
| Qwen3 8B | 18tok/sQ8_0 | 46tok/sQ8_0 |
| Phi-4 14B | 10tok/sQ8_0 | 33tok/sQ6_K |
| Qwen 3.5 4B | 37tok/sQ8_0 | 95tok/sQ8_0 |
| Ministral 3 8B | 17tok/sQ8_0 | 45tok/sQ8_0 |
| Granite 4.2 8B | 17tok/sQ8_0 | 43tok/sQ8_0 |
| Gemma 4 E4B | 21tok/sQ8_0 | 54tok/sQ8_0 |
| LFM2.5 8B-A1B | 73tok/sQ8_0 | 187tok/sQ8_0 |
| Llama 3.1 8B | 23tok/sQ6_K | 60tok/sQ6_K |
| Qwen2.5 0.5B | 281tok/sQ8_0 | 722tok/sQ8_0 |
| Qwen3.5 0.8B | 191tok/sQ8_0 | 490tok/sQ8_0 |
| Qwen3.5 2B | 114tok/sQ5_K_M | 294tok/sQ5_K_M |
| DeepSeek R1 Distill Qwen 1.5B | 83tok/sQ8_0 | 214tok/sQ8_0 |
| MiniCPM5 2B | 59tok/sQ8_0 | 151tok/sQ8_0 |
| LFM2.5 2.6B | 53tok/sQ8_0 | 135tok/sQ8_0 |
| LFM2.5 VL 3B | 53tok/sQ8_0 | 135tok/sQ8_0 |
| Spark X2.5 4B | 52tok/smlx-4bit | 134tok/smlx-4bit |
| granite vision 4.1 4b | 41tok/sQ8_0 | 106tok/sQ8_0 |
| granite 4.2 3b | 39tok/sQ8_0 | 100tok/sQ8_0 |
| LFM2.5 24B A2B | 38tok/sQ8_0 | offload |
| Mellum2.1 12B A2.5B Thinking | 38tok/sQ8_0 | 97tok/sQ8_0 |
| FrogNano 4B 2609 | 36tok/sQ8_0 | 92tok/sQ8_0 |
| Kimi VL A3B Thinking 2506 | 32tok/sQ8_0 | 126tok/sQ4_K_M |
| Kimi VL A3B | 30tok/smlx-8bit | 98tok/smlx-6bit |
| DeepSeek R1 Distill Qwen 7B | 21tok/sQ8_0 | 53tok/sQ8_0 |
| GLM 4 9B 0414 | 21tok/smlx-5bit | 53tok/smlx-5bit |
| DeepSeek R1 Distill Llama 8B | 19tok/sQ8_0 | 48tok/sQ8_0 |
| Ministral 3 8B Reasoning 2512 | 17tok/sQ8_0 | 45tok/sQ8_0 |
| GLM 4.6V Flash | 17tok/sQ8_0 | 44tok/sQ8_0 |
| GLM 4.1V 9B Thinking | 15tok/smlx-8bit | 38tok/smlx-8bit |
| DeepSeek R1 Distill Qwen 14B | 10tok/sQ8_0 | 33tok/sQ6_K |
| Qwen3.8 27B OBLITERATED | 8tok/smlx-4bit | offload |
| Devstral Small 2507 | 7tok/sQ8_0 | 29tok/sQ4_K_M |
| Magistral Small 2506 | 7tok/sQ8_0 | 29tok/sQ4_K_M |
| Magistral Small 2507 | 7tok/sQ8_0 | 29tok/sQ4_K_M |
| Magistral Small 2509 | 7tok/sQ8_0 | 29tok/sQ4_K_M |
| granite 4.2 30b | 5tok/sQ8_0 | offload |
| Qwen 3.5 122B-A10B | won't run | offload |
| Mistral Small 4 119B | won't run | offload |
| DeepSeek V4 Flash | won't run | won't run |
| GLM 5.3 Flash | won't run | won't run |
| Qwen 3.8 Flash Next | won't run | won't run |
| MiniMax M2.7 | won't run | won't run |
| Nemotron 3 Super 120B-A12B | won't run | won't run |
| Qwen3 Coder Next | won't run | won't run |
| gpt-oss 120B | won't run | won't run |
| GLM 4.5 Air | won't run | won't run |
| Qwen3 Next 80B-A3B | won't run | won't run |
| Llama 3.3 70B | won't run | won't run |
| DeepSeek R1 | won't run | won't run |
| DeepSeek R1 0528 | won't run | won't run |
| DeepSeek R1 Distill Llama 70B | won't run | won't run |
| DeepSeek R1 Zero | won't run | won't run |
| DeepSeek V3 | won't run | won't run |
| DeepSeek V3 0324 | won't run | won't run |
| DeepSeek V3.1 | won't run | won't run |
| DeepSeek V3.1 Terminus | won't run | won't run |
| DeepSeek V3.2 | won't run | won't run |
| DeepSeek V4 Flash 0731 | won't run | won't run |
| DeepSeek V4 Flash Vision Exp | won't run | won't run |
| Devstral 2 123B Instruct 2512 | won't run | won't run |
| GLM 4.5 | won't run | won't run |
| GLM 4.5V | won't run | won't run |
| GLM 4.6 | won't run | won't run |
| GLM 4.6V | won't run | won't run |
| GLM 4.7 | won't run | won't run |
| GLM 5 | won't run | won't run |
| GLM 5.1 | won't run | won't run |
| GLM 5.2 | won't run | won't run |
| GLM 5.3 | won't run | won't run |
| Kimi Dev 72B | won't run | won't run |
| Kimi K2 | won't run | won't run |
| Kimi K2 Instruct 0905 | won't run | won't run |
| Kimi K2 Thinking | won't run | won't run |
| Kimi K2.5 | won't run | won't run |
| MiniMax M2 | won't run | won't run |
| MiniMax M2.1 | won't run | won't run |
| MiniMax M2.5 | won't run | won't run |
| MiniMax M3 | won't run | won't run |
| Mistral Medium 3.5 128B | won't run | won't run |
Questions
- Which is better for local AI, the Mac mini M4 Pro 48GB or the NVIDIA GeForce RTX 4080 Super?
- Choose the Mac mini M4 Pro 48GB to run bigger models. Choose the NVIDIA GeForce RTX 4080 Super for speed. Choose the NVIDIA GeForce RTX 4080 Super to spend less.
- Which can run bigger models, the Mac mini M4 Pro 48GB or the NVIDIA GeForce RTX 4080 Super?
- At 8k context the Mac mini M4 Pro 48GB runs 58 of the models we track fully in memory and the NVIDIA GeForce RTX 4080 Super 41; only the Mac mini M4 Pro 48GB holds Qwen 3.8 27B.
- Which is faster for local AI, the Mac mini M4 Pro 48GB or the NVIDIA GeForce RTX 4080 Super?
- On the models both run fully in memory, the NVIDIA GeForce RTX 4080 Super is about 2.6× as fast as the Mac mini M4 Pro 48GB (estimated, median across models).
- What is the price difference between the Mac mini M4 Pro 48GB and the NVIDIA GeForce RTX 4080 Super?
- In Germany the Mac mini M4 Pro 48GB costs 2.649 € at eBay (used) and the NVIDIA GeForce RTX 4080 Super 1.990 € at Amazon: the NVIDIA GeForce RTX 4080 Super is 659 € cheaper.
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