For many buyers, yes. If your models are under about 70B parameters, or you need CUDA or fast image generation, a machine in the S$5,000–6,700 range does the job, and the extra S$10,000 or so buys capacity you won't use. A Mac Studio M5 Ultra with 256 GB, about S$16,699 configured (calculated from Apple Singapore's upgrade pricing — confirm on apple.com/sg), earns its price only when you need to run models of 100 GB or more on the GPU, want fast token generation on large models, or plan to serve a team. The "S$5,000" and "S$15,000" in the title are illustrative price points. Below we map them to real configurations sold in Singapore.
What do S$5,000 and S$15,000 actually buy?
| Configuration | Price | Memory the GPU can use | Memory bandwidth | Software |
|---|---|---|---|---|
| GMKtec EVO-X2 (AMD Ryzen AI Max+ 395, 128 GB/2 TB) | S$5,844.54 (SourceIT, listed 8 Nov 2026) | About 96 GB on Windows | About 256 GB/s | Windows 11 Pro; llama.cpp, LM Studio; no CUDA |
| ASUS ROG NUC 16 (RTX 5080 Laptop GPU, 32 GB RAM, 1 TB) | S$5,650.03 (SourceIT, listed 8 Nov 2026) | The laptop GPU's dedicated memory, far less than 128 GB | Fast, but limited to the GPU's own memory | Windows 11; full CUDA |
| ASUS Ascent GX10 (NVIDIA GB10, 64 GB/1 TB) | S$6,670 (SourceIT, listed 8 Nov 2026) | Most of 64 GB unified | 273 GB/s | Linux (NVIDIA DGX OS); full CUDA |
| Mac Studio M5 Max (40-core GPU, 64 GB/1 TB) | About S$5,449 configured (calculated from Apple Singapore's upgrade pricing — confirm on apple.com/sg) | About 48 GB by default | 614 GB/s | macOS; MLX, llama.cpp; no CUDA |
| Mac Studio M5 Ultra (36-core CPU, 80-core GPU, 256 GB/2 TB) | About S$16,699 configured (calculated from Apple Singapore's upgrade pricing — confirm on apple.com/sg) | About 192 GB by default | 1.2 TB/s | macOS; MLX, llama.cpp; no CUDA |
Source: SourceIT store listings (8 Nov 2026); Apple Singapore list and upgrade prices (accessed 8 Nov 2026); Apple, AMD, NVIDIA and ASUS specifications. GPU-usable memory: macOS defaults to about 75% of unified memory; the Ryzen AI Max+ figure is for Windows. Prices change; ask for a current quotation.
Where is the S$5,000 machine the better buy?
The Mac Studio M5 Ultra 256 GB costs about 2.9 times as much as the GMKtec EVO-X2 and about 2.5 times as much as the GX10 64 GB (calculated from the prices above). For a large share of real AI work, that extra money changes little:
- Everyday assistants and coding models. Models up to about 30B parameters at 4-bit need under 20 GB. All five machines run them, and the ROG NUC's discrete NVIDIA GPU is likely the quickest when the model fits in its memory.
- Medium mixture-of-experts models. The EVO-X2 runs gpt-oss-120b at roughly 30–56 tokens per second in community tests, depending on engine and settings. That's usable for one person.
- CUDA development. The GX10 gives you NVIDIA's full Linux CUDA stack, the same software as NVIDIA's data-centre systems, for S$6,670. A Mac can't do that at any price. Our post on why some developers still choose a Mac over a DGX Spark covers the other side of that argument.
- Image generation. ComfyUI and most image tools are built for CUDA first, which favours the ROG NUC or the GX10.
Running costs don't close the gap either. Apple rates the M5 Ultra at 9 W at idle. At SP Group's 31.16 cents per kWh including GST, that's about S$25 a year. Even at a constant 300 W, the peak Apple's researchers measured during LLM inference, it would be about S$819 a year (illustrative; calculated as 0.3 kW × 8,760 hours × S$0.3116). Our hidden costs of building versus buying covers the other costs of ownership.
What does the extra S$10,000 buy?
About S$10,850 more than the EVO-X2 buys three things the S$5,000 class can't offer:
- Capacity. About 192 GB of GPU-usable memory against about 96 GB. That's the difference between running a 155 GB model such as Qwen3.8-Flash-Next at 4-bit, which MacStories ran at 54 tokens per second on the M5 Ultra, and not running it at all.
- Bandwidth. At 1.2 TB/s, the M5 Ultra has about 4.8 times the EVO-X2's bandwidth and 4.5 times the GX10's. Token generation on large dense models scales roughly with that. The EVO-X2 ran Llama 3.3 70B at 4.89 tokens per second in a community test; the M5 Ultra's theoretical ceiling for the same 40 GB model is about 31 (calculated as bandwidth divided by model size).
- Room to share. More memory and bandwidth leave space for several users or agents at once. That is a different job from a personal machine. See can one Mac Studio run a whole company's AI.
What it doesn't buy: CUDA, upgradeable parts, or faster prompt processing than NVIDIA's discrete GPUs. MacStories measured the RTX 5090 processing a 6K-token prompt about 1.8 times faster than the M5 Ultra.
Pay for the largest model you will actually run, not the largest model you might one day want to try.
How do the options compare by workload?
- Chat and coding with models up to about 30B: any S$5,000-class machine. Spending more mostly buys spare capacity.
- 70B dense models: the EVO-X2 and GX10 run them, but slowly (about 4–5 tokens per second in published tests on these chips). The Mac Studio M5 Max 64 GB is too tight once you allow for context. The M5 Ultra is the comfortable choice.
- gpt-oss-120b and similar mixture-of-experts models: the EVO-X2 is usable. The M5 Ultra is faster: one community run reported about 110 tokens per second, unverified. The 64 GB machines are too small.
- Models above 100 GB: only the M5 Ultra with 256 GB or more.
- Image and video generation, CUDA training: the NVIDIA options.
Our post on whether buyers are overspending on AI hardware explores the overbuying risk, and our S$30,000 workstation comparison looks at the next step up.
Is there a S$5,000 Mac Studio option?
Yes, and it's worth considering. Apple Singapore's list price for the base Mac Studio M5 Max (36 GB/512 GB) is S$3,499. The M5 Max with the 40-core GPU and 64 GB/1 TB comes to about S$5,449 configured (calculated from Apple Singapore's upgrade pricing — confirm on apple.com/sg). It has 614 GB/s of bandwidth, more than double the EVO-X2 or GX10, but only about 48 GB for the GPU by default. That makes it a fast machine for models up to about 30B, not a 70B or 120B machine. If you want large models on a Mac for less than the Ultra, the M5 Max with 128 GB, about S$7,849 configured, is the middle step. Our three-way comparison of Mac Studio, RTX Spark and custom PCs sets these against each other.
Buying in Singapore
SourceIT supplies every machine in this comparison. The GMKtec EVO-X2 128GB/2TB is S$5,844.54, the ASUS ROG NUC 16 with RTX 5080 Laptop GPU is S$5,650.03 and the ASUS Ascent GX10 64GB/1TB is S$6,670 (listed 8 Nov 2026). Mac Studio models, including the M5 Max with 128 GB and the M5 Ultra with 256 GB, are price on request. Prices change; ask for a current quotation. Use Request for Quotation on the product page, call (65) 6978 3502, email Sales@sourceit.com.sg or use our contact page.
Frequently asked questions
Is a S$15,000 Mac Studio worth it for local AI? Only if you need to run models of roughly 100 GB or more, want faster generation on large models, or plan to share the machine. For models up to about 30B, a S$5,000-class machine does the same job.
What is the cheapest machine that runs a 70B model? Among the machines here, the GMKtec EVO-X2 at S$5,844.54. With 128 GB it fits a 4-bit 70B model, but community tests show under 5 tokens per second, which is slow for interactive use.
Can a S$5,000 PC run gpt-oss-120b? A 128 GB Ryzen AI Max+ 395 machine such as the EVO-X2 can, at roughly 30–56 tokens per second in community tests. Machines with 64 GB or less don't have enough memory.
Why choose the GX10 over a cheaper Windows PC? It runs NVIDIA's full Linux CUDA stack, including vLLM and TensorRT-LLM, which matters if your work will move to NVIDIA servers.
Does a Mac Studio save enough electricity to pay for itself? No. Even running constantly at 300 W, the electricity bill would be about S$819 a year at SP Group's current tariff, far less than the price difference between these machines.
