Mac mini M4 16GB vs NVIDIA GeForce RTX 4060 Ti 16GB
For running models locally, priced in Canada. At 128k context the first runs 4 models fully in memory, the second 5.
In short
Both have 16 GB of memory for models; the Mac mini M4 16GB has 120 GB/s of bandwidth and the NVIDIA GeForce RTX 4060 Ti 16GB 288 GB/s. At 128k context the NVIDIA GeForce RTX 4060 Ti 16GB runs 5 of the models we track fully in memory and the Mac mini M4 16GB 4; only the NVIDIA GeForce RTX 4060 Ti 16GB holds LFM2.5 8B-A1B. On the models both run fully in memory, the NVIDIA GeForce RTX 4060 Ti 16GB is about 1.8× as fast as the Mac mini M4 16GB (estimated, median across models).
Updated . Speeds are estimates; how they are worked out.
Specifications
| Spec | Mac mini M4 16GB | NVIDIA GeForce RTX 4060 Ti 16GB |
|---|---|---|
| Chip | Apple M4 (10-core GPU) | – |
| Memory bus | 128-bit | 128-bit |
| Memory bandwidth | 120 GB/s | 288 GB/s |
| FP16 compute | 3.76 TFLOPS | 44 TFLOPS |
| Software | Metal | CUDA |
| Unified memory | 16 GB | – |
| GPU can use by default | 10.7 GB | – |
| GPU can use, tuned | 10.666666666666666 GB | – |
| Operating system | macos | – |
| Processor | M4 10-core | – |
| Storage | 256 GB | – |
| GPU | – | GeForce RTX 4060 Ti 16GB |
| Memory | – | 16 GB GDDR6 |
| Board power | – | 165 W |
| PCIe generation | – | Gen 4 |
| PCIe lanes | – | x8 |
What each runs
Estimated decode speed with the most precise quant that fits each one est.
| Model | Mac mini M4 16GB | NVIDIA GeForce RTX 4060 Ti 16GB |
|---|---|---|
| Gemma 4 12B | 8tok/sQ4_K_M | 15tok/sQ6_K |
| Qwen 3.5 9B | 8tok/sQ4_K_M | 13tok/sQ8_0 |
| Qwen 3.5 4B | 9tok/sQ8_0 | 20tok/sQ8_0 |
| Gemma 4 E4B | 8tok/sQ5_K_M | 15tok/sQ8_0 |
| LFM2.5 8B-A1B | won't run | 15tok/sUD-Q6_K |
| Qwen 3.8 27B | won't run | offload |
| Qwen 3.6 27B | won't run | offload |
| Gemma 4 31B | won't run | offload |
| Qwen 3.5 27B | won't run | offload |
| Qwen 3.6 35B-A3B | won't run | offload |
| Gemma 4 26B-A4B | won't run | offload |
| Devstral Small 2 24B | won't run | offload |
| GLM 4.7 Flash | won't run | offload |
| Qwen 3.5 35B-A3B | won't run | offload |
| Nemotron 3.5 Lightning 30B-A3B | won't run | offload |
| Kimi Linear 48B-A3B | won't run | offload |
| Qwen3 Coder 30B-A3B | won't run | offload |
| gpt-oss 20B | won't run | offload |
| Gemma 3 27B | won't run | offload |
| Mistral Small 3.2 24B | won't run | offload |
| Ministral 3 14B | won't run | offload |
| Qwen3 14B | won't run | offload |
| DeepSeek R1 0528 Qwen3 8B | won't run | offload |
| Phi-4 14B | won't run | offload |
| Qwen3 8B | won't run | offload |
| Granite 4.2 8B | won't run | offload |
| Ministral 3 8B | won't run | offload |
| Llama 3.1 8B | 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 |
| Qwen 3.5 122B-A10B | 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 |
| Mistral Small 4 119B | 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 |
| Qwen3 32B | won't run | won't run |
| DeepSeek R1 Distill Qwen 32B | won't run | won't run |
| Llama 3.3 70B | won't run | won't run |
Questions
- Which is better for local AI, the Mac mini M4 16GB or the NVIDIA GeForce RTX 4060 Ti 16GB?
- Choose the NVIDIA GeForce RTX 4060 Ti 16GB to run bigger models. Choose the NVIDIA GeForce RTX 4060 Ti 16GB for speed.
- Which can run bigger models, the Mac mini M4 16GB or the NVIDIA GeForce RTX 4060 Ti 16GB?
- At 128k context the NVIDIA GeForce RTX 4060 Ti 16GB runs 5 of the models we track fully in memory and the Mac mini M4 16GB 4; only the NVIDIA GeForce RTX 4060 Ti 16GB holds LFM2.5 8B-A1B.
- Which is faster for local AI, the Mac mini M4 16GB or the NVIDIA GeForce RTX 4060 Ti 16GB?
- On the models both run fully in memory, the NVIDIA GeForce RTX 4060 Ti 16GB is about 1.8× as fast as the Mac mini M4 16GB (estimated, median across models).