NVIDIA RTX 5090 vs Apple M4 Max (128GB)
Side-by-side local AI comparison — VRAM, memory bandwidth, model compatibility, and estimated tokens per second across 70 open-weight models.
Quick verdict
Apple M4 Max (128GB) wins for local AI inference. It has 96 GB more VRAM and -70% more memory bandwidth, runs 61 models natively (vs 47), and exclusively fits 14 models the other cannot. Note: NVIDIA RTX 5090 uses CUDA while Apple M4 Max (128GB) uses METAL — software ecosystem matters for your framework.
Specs comparison
| Spec | NVIDIA RTX 5090 | Apple M4 Max (128GB) |
|---|---|---|
| VRAM | 32 GB | 128 GB unified |
| Memory type | GDDR7 | LPDDR5X |
| Bandwidth | 1792 GB/s(+228%) | 546 GB/s |
| CPU cores | — | 16 (12P + 4E) |
| Architecture | Blackwell | Apple M4 Max |
| Backend | CUDA | METAL |
| Tier | Consumer | Laptop |
| Released | 2025 | 2024 |
| Models (native) | 47 | 61 |
Estimated tokens per second
Computed from memory bandwidth and model active-parameter weight. Assumes model fits natively in VRAM.
| Model | NVIDIA RTX 5090 | Apple M4 Max (128GB) | Delta |
|---|---|---|---|
| Llama 3.3 70B Instruct(70B) | 85.3 t/s(Q2_K) | 7.8 t/s(Q8) | +994% |
| Qwen 3.6 27B(27B) | 88.5 t/s(Q6_K) | 10.1 t/s(FP16) | +776% |
| Llama 3.1 8B Instruct(8B) | 112 t/s(FP16) | 34.1 t/s(FP16) | +228% |
| Qwen 2.5 7B Instruct(7.6B) | 117.9 t/s(FP16) | 35.9 t/s(FP16) | +228% |
Delta is NVIDIA RTX 5090 relative to Apple M4 Max (128GB).
Only NVIDIA RTX 5090 can run(0)
No exclusive models — Apple M4 Max (128GB) can run everything NVIDIA RTX 5090 can.
Only Apple M4 Max (128GB) can run(14)
- GLM-4.7 358B358B
- GLM-4.5 355B355B
- GLM-4.6 355B355B
- DeepSeek V4 Flash 284B284B
- Qwen3 235B-A22B (MoE)235B
- MiniMax M2.5 229B229B
- MiniMax M2.7 229B229B
- Mixtral 8x22B Instruct v0.1141B
- Qwen 3.5 122B-A10B (MoE)122B
- Nemotron 3 Super 120B120B
- GPT-OSS 120B117B
- Llama 4 Scout 109B109B
- +2 more
Both run natively(47)
These models fit in VRAM on both GPUs. Bandwidth determines which runs them faster.
- Qwen 2.5 72B Instruct83 t/svs7.6 t/s
- Llama 3.3 70B Instruct85.3 t/svs7.8 t/s
- DeepSeek R1 Distill Llama 70B85.3 t/svs7.8 t/s
- Llama 3.1 70B Instruct85.3 t/svs7.8 t/s
- Mixtral 8x7B Instruct v0.1305.6 t/svs23.3 t/s
- Command-R 35B128 t/svs7.8 t/s
- Qwen 3.5 35B-A3B (MoE)876.1 t/svs100.1 t/s
- Qwen 3.6 35B81.9 t/svs7.8 t/s
- Yi 1.5 34B Chat83.3 t/svs7.9 t/s
- Qwen3 32B72.8 t/svs8.3 t/s
- Qwen 2.5 32B Instruct73.5 t/svs8.4 t/s
- Qwen 2.5 Coder 32B Instruct73.5 t/svs8.4 t/s
- DeepSeek R1 Distill Qwen 32B73.5 t/svs8.4 t/s
- Nemotron 3 Nano 30B876.1 t/svs100.1 t/s
- Gemma 4 31B77.1 t/svs8.8 t/s
- Qwen3 30B-A3B (MoE)876.1 t/svs100.1 t/s
- +31 more on both
Which should you choose?
Choose NVIDIA RTX 5090 if:
- • Faster token generation is the priority
- • You rely on CUDA-based tools (PyTorch, vLLM, Ollama)
- • You want the newer architecture and longer driver support lifecycle
Choose Apple M4 Max (128GB) if:
- • You need to run larger models (>32 GB VRAM)
- • You're on macOS and want native Metal acceleration (MLX, llama.cpp)
- • Unified memory matters (CPU/GPU share the same pool — no data copy overhead)
Frequently asked questions
- Which is better for local AI, the NVIDIA RTX 5090 or Apple M4 Max (128GB)?
- For local AI inference, the Apple M4 Max (128GB) has the edge. It offers 128 GB VRAM (vs 32 GB) and 546 GB/s bandwidth (vs 1792 GB/s), letting it run 61 models natively in VRAM vs 47 for its rival.
- How much VRAM does the NVIDIA RTX 5090 have vs the Apple M4 Max (128GB)?
- The NVIDIA RTX 5090 has 32 GB of GDDR7 at 1792 GB/s. The Apple M4 Max (128GB) has 128 GB of LPDDR5X at 546 GB/s. The Apple M4 Max (128GB) has 96 GB more VRAM, allowing it to run 14 models the NVIDIA RTX 5090 cannot fit natively.
- Can the NVIDIA RTX 5090 run Llama 3.3 70B?
- Yes. The NVIDIA RTX 5090 runs Llama 3.3 70B natively at Q2_K quantization at approximately 85.3 tokens per second.
- Can the Apple M4 Max (128GB) run Llama 3.3 70B?
- Yes. The Apple M4 Max (128GB) runs Llama 3.3 70B natively at Q8 quantization at approximately 7.8 tokens per second.
- What is the difference between the NVIDIA RTX 5090 and Apple M4 Max (128GB) for AI?
- The key difference for AI inference is VRAM and memory bandwidth. The NVIDIA RTX 5090 has 32 GB VRAM at 1792 GB/s (CUDA backend). The Apple M4 Max (128GB) has 128 GB VRAM at 546 GB/s (METAL backend). VRAM determines which models fit; bandwidth determines tokens per second. The NVIDIA RTX 5090 runs 47 models natively vs 61 for the Apple M4 Max (128GB).