Mac mini M4 Pro 64GB vs NVIDIA GeForce RTX 4090

For running models locally, priced in Germany. At 32k context the first runs 61 models fully in memory, the second 53.

In short

The Mac mini M4 Pro 64GB has more memory for models: 64 GB against 24 GB. At 32k context the Mac mini M4 Pro 64GB runs 61 of the models we track fully in memory and the NVIDIA GeForce RTX 4090 53; only the Mac mini M4 Pro 64GB holds Qwen 3.5 122B-A10B. On the models both run fully in memory, the NVIDIA GeForce RTX 4090 is about 3.5× as fast as the Mac mini M4 Pro 64GB (estimated, median across models). In Germany the Mac mini M4 Pro 64GB costs 3.199 € at eBay (used) and the NVIDIA GeForce RTX 4090 3.955 € at eBay: the Mac mini M4 Pro 64GB is 756 € cheaper.

Updated . Speeds are estimates; how they are worked out.

Specifications

SpecMac mini M4 Pro 64GBNVIDIA GeForce RTX 4090
ChipApple M4 Pro (20-core GPU)–
Memory bus256-bit384-bit
Memory bandwidth273 GB/s1,008 GB/s
FP16 compute8.08 TFLOPS165 TFLOPS
SoftwareMetalCUDA
Unified memory64 GB–
GPU can use by default48 GB–
GPU can use, tuned56 GB–
Operating systemmacos–
ProcessorM4 Pro 14-core–
Storage1000 GB–
GPU–GeForce RTX 4090
Memory–24 GB GDDR6X
Board power–450 W
PCIe generation–Gen 4
PCIe lanes–x16

What each runs

Estimated decode speed with the most precise quant that fits each one est.

ModelMac mini M4 Pro 64GBNVIDIA GeForce RTX 4090
Qwen 3.8 27B6tok/sQ8_027tok/sQ5_K_M
Qwen 3.5 122B-A10B25tok/sUD-Q2_K_XLoffload
Qwen 3.6 27B6tok/sQ8_029tok/sQ5_K_M
Qwen3 Coder Next33tok/sQ4_K_Moffload
Gemma 4 31B5tok/sQ8_029tok/sQ4_K_M
Mistral Small 4 119B34tok/sUD-Q2_K_XLoffload
Qwen 3.6 35B-A3B28tok/sQ8_0145tok/sQ4_K_M
Qwen 3.5 27B6tok/sQ8_029tok/sQ5_K_M
Gemma 4 26B-A4B21tok/sQ8_084tok/sUD-Q6_K
Qwen3 Next 80B-A3B40tok/sQ4_K_Moffload
Qwen 3.5 35B-A3B28tok/sQ8_0146tok/sQ4_K_M
GLM 4.7 Flash15tok/sQ8_070tok/sQ5_K_M
Devstral Small 2 24B6tok/sQ8_028tok/sQ5_K_M
Nemotron 3.5 Lightning 30B-A3B30tok/sUD-Q6_K_XL153tok/sMXFP4
Kimi Linear 48B-A3B38tok/sQ6_Koffload
gpt-oss 20B33tok/sMXFP4116tok/sMXFP4
Qwen3 Coder 30B-A3B17tok/sQ8_074tok/sQ4_K_M
Qwen3 32B4tok/sQ8_0offload
Gemma 4 12B13tok/sQ8_046tok/sQ8_0
Qwen 3.5 9B17tok/sQ8_059tok/sQ8_0
Mistral Small 3.2 24B6tok/sQ8_028tok/sQ5_K_M
Gemma 3 27B6tok/sQ8_028tok/sQ5_K_M
DeepSeek R1 Distill Qwen 32B4tok/sQ8_0offload
Ministral 3 14B9tok/sQ8_032tok/sQ8_0
Qwen3 14B8tok/sQ8_030tok/sQ8_0
DeepSeek R1 0528 Qwen3 8B13tok/sQ8_046tok/sQ8_0
Qwen3 8B13tok/sQ8_046tok/sQ8_0
Phi-4 14B8tok/sQ8_028tok/sQ8_0
Qwen 3.5 4B32tok/sQ8_0112tok/sQ8_0
Ministral 3 8B13tok/sQ8_046tok/sQ8_0
Granite 4.2 8B12tok/sQ8_043tok/sQ8_0
Gemma 4 E4B19tok/sQ8_068tok/sQ8_0
LFM2.5 8B-A1B40tok/sQ8_0140tok/sQ8_0
Llama 3.1 8B16tok/sQ6_K57tok/sQ6_K
Qwen2.5 0.5B190tok/sQ8_0669tok/sQ8_0
Qwen3.5 0.8B144tok/sQ8_0507tok/sQ8_0
Qwen3.5 2B96tok/sQ5_K_M337tok/sQ5_K_M
DeepSeek R1 Distill Qwen 1.5B63tok/sQ8_0221tok/sQ8_0
MiniCPM5 2B43tok/sQ8_0153tok/sQ8_0
Spark X2.5 4B41tok/smlx-4bit145tok/smlx-4bit
LFM2.5 2.6B36tok/sQ8_0128tok/sQ8_0
LFM2.5 VL 3B36tok/sQ8_0128tok/sQ8_0
Mellum2.1 12B A2.5B Thinking34tok/sQ8_0118tok/sQ8_0
granite vision 4.1 4b28tok/sQ8_099tok/sQ8_0
granite 4.2 3b27tok/sQ8_095tok/sQ8_0
Kimi VL A3B Thinking 250626tok/sQ8_091tok/sQ8_0
Kimi VL A3B25tok/smlx-8bit88tok/smlx-8bit
LFM2.5 24B A2B22tok/sQ8_084tok/sQ6_K
GLM 4 9B 041419tok/smlx-5bit65tok/smlx-5bit
DeepSeek R1 Distill Qwen 7B18tok/sQ8_063tok/sQ8_0
GLM 4.6V Flash16tok/sQ8_055tok/sQ8_0
DeepSeek R1 Distill Llama 8B14tok/sQ8_049tok/sQ8_0
GLM 4.1V 9B Thinking14tok/smlx-8bit48tok/smlx-8bit
Ministral 3 8B Reasoning 251213tok/sQ8_046tok/sQ8_0
DeepSeek R1 Distill Qwen 14B8tok/sQ8_028tok/sQ8_0
Qwen3.8 27B OBLITERATED8tok/smlx-4bit27tok/smlx-4bit
Devstral Small 25076tok/sQ8_028tok/sQ5_K_M
Magistral Small 25066tok/sQ8_028tok/sQ5_K_M
Magistral Small 25076tok/sQ8_028tok/sQ5_K_M
Magistral Small 25096tok/sQ8_028tok/sQ5_K_M
granite 4.2 30b5tok/sQ8_0offload
GLM 4.5 Airwon't runoffload
DeepSeek V4 Flashwon't runwon't run
GLM 5.3 Flashwon't runwon't run
Qwen 3.8 Flash Nextwon't runwon't run
MiniMax M2.7won't runwon't run
Nemotron 3 Super 120B-A12Bwon't runwon't run
gpt-oss 120Bwon't runwon't run
Llama 3.3 70Bwon't runwon't run
DeepSeek R1won't runwon't run
DeepSeek R1 0528won't runwon't run
DeepSeek R1 Distill Llama 70Bwon't runwon't run
DeepSeek R1 Zerowon't runwon't run
DeepSeek V3 0324won't runwon't run
DeepSeek V3.1won't runwon't run
DeepSeek V3.1 Terminuswon't runwon't run
DeepSeek V3.2won't runwon't run
DeepSeek V4 Flash 0731won't runwon't run
DeepSeek V4 Flash Vision Expwon't runwon't run
Devstral 2 123B Instruct 2512won't runwon't run
GLM 4.5Vwon't runwon't run
GLM 4.6won't runwon't run
GLM 4.6Vwon't runwon't run
GLM 4.7won't runwon't run
GLM 5.1won't runwon't run
GLM 5.2won't runwon't run
GLM 5.3won't runwon't run
Kimi Dev 72Bwon't runwon't run
Kimi K2won't runwon't run
Kimi K2 Instruct 0905won't runwon't run
Kimi K2 Thinkingwon't runwon't run
Kimi K2.5won't runwon't run
MiniMax M2won't runwon't run
MiniMax M2.1won't runwon't run
MiniMax M2.5won't runwon't run
MiniMax M3won't runwon't run
Mistral Medium 3.5 128Bwon't runwon't run

Questions

Which is better for local AI, the Mac mini M4 Pro 64GB or the NVIDIA GeForce RTX 4090?
Choose the Mac mini M4 Pro 64GB to run bigger models. Choose the NVIDIA GeForce RTX 4090 for speed. Choose the Mac mini M4 Pro 64GB to spend less.
Which can run bigger models, the Mac mini M4 Pro 64GB or the NVIDIA GeForce RTX 4090?
At 32k context the Mac mini M4 Pro 64GB runs 61 of the models we track fully in memory and the NVIDIA GeForce RTX 4090 53; only the Mac mini M4 Pro 64GB holds Qwen 3.5 122B-A10B.
Which is faster for local AI, the Mac mini M4 Pro 64GB or the NVIDIA GeForce RTX 4090?
On the models both run fully in memory, the NVIDIA GeForce RTX 4090 is about 3.5× as fast as the Mac mini M4 Pro 64GB (estimated, median across models).
What is the price difference between the Mac mini M4 Pro 64GB and the NVIDIA GeForce RTX 4090?
In Germany the Mac mini M4 Pro 64GB costs 3.199 € at eBay (used) and the NVIDIA GeForce RTX 4090 3.955 € at eBay: the Mac mini M4 Pro 64GB is 756 € cheaper.

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