What are the differences in memory bandwidth between the RTX 4070 and the MacBook Pro M4 in 3D modeling applications

1. Memory Bandwidth of RTX 4070:
- The original RTX 4070 uses GDDR6X memory, offering a memory bandwidth of 504 GB/s. However, a new variant of the RTX 4070 has been introduced with GDDR6 memory, which reduces the memory bandwidth to 480 GB/s. This change is primarily due to a shift from GDDR6X to GDDR6, which provides slightly lower bandwidth but is more readily available[1][7].
- The RTX 4070's performance in 3D modeling is less dependent on memory bandwidth due to its large L2 cache, which helps mitigate the impact of reduced memory bandwidth[1].

2. Memory Bandwidth of MacBook Pro M4:
- The MacBook Pro with M4 chips features unified memory, which is shared between the CPU and GPU. The base M4 model offers 120 GB/s of memory bandwidth, while the M4 Pro provides 273 GB/s, and the M4 Max offers over half a terabyte per second (approximately 546 GB/s for the fastest variant)[2][3][5].
- The unified memory architecture in MacBooks means that both CPU and GPU tasks benefit from the same memory bandwidth, which is particularly advantageous for tasks like 3D modeling that require fast memory access for both processing units[8].

3. Performance in 3D Modeling Applications:
- For 3D modeling, the MacBook Pro with M4 chips, especially the M4 Max, offers significantly higher memory bandwidth compared to the RTX 4070. This can result in faster rendering times and better performance in complex scenes, as the unified memory architecture efficiently handles both CPU and GPU tasks[2][3].
- The RTX 4070, despite its lower memory bandwidth compared to the M4 Max, still performs well in 3D modeling due to its dedicated GPU architecture and large L2 cache. However, it might not match the M4 Max's performance in tasks heavily reliant on memory bandwidth[1][7].

In summary, while the RTX 4070 offers robust performance for 3D modeling with its dedicated GPU, the MacBook Pro with M4 chips, particularly the M4 Max, provides significantly higher memory bandwidth, which can be advantageous for tasks that heavily rely on fast memory access.