MacBook Pro M5 Pro (16-inch), 64GB vs AMD Radeon AI PRO R9700, 32GB for local AI
Both hold 33 of the 49 current models here. The Radeon AI PRO R9700, 32GB costs $2,700 less, though the Radeon AI PRO R9700, 32GB is priced as the card alone, without the PC around it. On Qwen3.8 27B, the strongest model both hold, the Radeon AI PRO R9700, 32GB is about 2.5× faster: 30 tok/s against 12, both estimated from memory bandwidth. The Radeon AI PRO R9700, 32GB pays for itself sooner, in 84 years against 269 years at 500k tokens a day.
| MacBook Pro M5 Pro (16-inch), 64GB | AMD Radeon AI PRO R9700, 32GB | |
|---|---|---|
| Price | $3,999 | $1,299card only |
| Memory | 64 GB | 32 GB |
| Usable by the GPU | 48 GB | 31 GB |
| Memory bandwidth | 307 GB/s | 640 GB/s |
| Power under load | 140 Wstand-in | 300 W |
| Models that fit | 33 | 33 |
| Best model it runs | Qwen3.8 27B | Qwen3.8 27B |
| Speed on that model | 12 tok/s estimated | 30 tok/s estimated |
| Pay-back on that model | Pays back in 269 years | Pays back in 84 years |
The 140 W beside the MacBook Pro M5 Pro (16-inch), 64GB is a stand-in, not a figure for that machine: the data borrows it from the nearest hardware it does have, and the machine's own page names which and why. So the two figures above are not like for like, and the electricity in its pay-back here is priced from a borrowed number.
Run the numbers on the MacBook Pro M5 Pro (16-inch), 64GB · or the AMD Radeon AI PRO R9700, 32GB
How much use it takes to pay back
Everything above is at 500k tokens a day. Pay-back moves with how much you actually run, so here are both machines on Qwen3.8 27B, the strongest model both hold, at the five levels of use the calculator names. The AMD Radeon AI PRO R9700, 32GB pays back sooner at every level of use, so this is not a choice that turns on how hard you work it.
| A day's use | MacBook Pro M5 Pro (16-inch), 64GB | AMD Radeon AI PRO R9700, 32GB |
|---|---|---|
| 50ka few chats a day | 2,694 years | 836 years |
| 200klight assistant use | 673 years | 209 years |
| 1Ma moderate coding-assistant day | 135 years | 42 years |
| 4Mheavy coding with an agent | 34 years | 10 years |
| 20Magents running most of the day | 7.9 yearsits ceiling | 2.1 years |
On Qwen3.8 27B the MacBook Pro M5 Pro (16-inch), 64GB generates at most 17.1M tokens a day, so its figure at 20M tokens a day is for the most it can do, not for the whole of what was asked.
Run the MacBook Pro M5 Pro (16-inch), 64GB at 20M tokens a day · or the AMD Radeon AI PRO R9700, 32GB
The same models, not to the same length
Every model on this list that fits one machine fits the other at 32k of context, so memory does not change what they run. What it changes is how far you can take the context on 10 of them. The MacBook Pro M5 Pro (16-inch), 64GB has 48 GB usable against 31 GB, and spare memory is what the KV cache grows into as you keep more tokens.
| Model | MacBook Pro M5 Pro (16-inch), 64GB | AMD Radeon AI PRO R9700, 32GB |
|---|---|---|
| Qwen3.8 27B16 GB of weights | 256k | 128k |
| Qwen3.6 27B17 GB of weights | 256k | 128k |
| Gemma 4 31B it20 GB of weights | 256k | 64k |
| Granite 4.2 30B18 GB of weights | 64k | 32k |
| Qwen3-Coder 30B-A3B19 GB of weights | 256k | 64k |
| Devstral Small 2 24B14 GB of weights | 128k | 64k |
| Ministral 3 8B5.2 GB of weights | 256k | 128k |
| Laguna XS 2.120 GB of weights | 256k | 128k |
| Flint 40B-A2.5B25 GB of weights | 256k | 128k |
| Nanbeige4.3 33B21 GB of weights | 64k | 32k |
Each figure is the longest context the calculator offers that the machine still holds that model at, and no model is taken past its own context limit. The other 39 models the calculator counts reach the same length on both machines, at every setting from 4k to 256k.
Run Qwen3.8 27B on the MacBook Pro M5 Pro (16-inch), 64GB at 256k · or on the AMD Radeon AI PRO R9700, 32GB at 128k
The MacBook Pro M5 Pro (16-inch), 64GB is also head to head with another computer: Mac mini M5 Pro, 24GB · Mac Studio M5 Max, 128GB · DGX Spark, 128GB · GMKtec EVO-X2, 128GB · MacBook Air M5 (15-inch), 16GB · Beelink GTR9 Pro, 128GB · Minisforum MS-S1 Max, 128GB. With a graphics card: RTX PRO 6000 Blackwell, 96GB. With the same machine at another memory size: 24GB · 48GB.
The Radeon AI PRO R9700, 32GB is also head to head with another card: RTX PRO 6000 Blackwell, 96GB · GeForce RTX 5090, 32GB · GeForce RTX 4090, 24GB · GeForce RTX 3090, 24GB · GeForce RTX 4080, 16GB · GeForce RTX 3060, 12GB. With a complete computer: Mac mini M5 Pro, 24GB · Mac Studio M5 Max, 128GB · DGX Spark, 128GB · GMKtec EVO-X2, 128GB · MacBook Air M5 (15-inch), 16GB · Mac mini M6, 32GB.
The assumptions behind both columns
Both columns use the same usage: 500k tokens a day at 15:1 input to output, 32k of context, $0.17 per kWh, and today's API prices held flat. Speeds marked estimated are worked out from memory bandwidth rather than measured, and pay-back scales with them. The Radeon AI PRO R9700, 32GB is priced as the card alone, so add the PC around it before comparing it with a complete computer. All seven cards here are ranked by what each one holds. Change any of it in the calculator.
More head to head: everything the MacBook Pro M5 Pro (16-inch), 64GB runs · everything the AMD Radeon AI PRO R9700, 32GB runs · every other match-up · the quickest pay-back at each level of use · every model against the frontier