Question 1

What AI models can run on M60?

Accepted Answer

The M60 (8 GB VRAM) can run models including paligemma-3b-ft-refcoco-seg-896-jax, Llama-3.2-1B-Instruct-SpinQuant_INT4_EO8, Llama-3.2-3B-Instruct-QLORA_INT4_EO8, Llama-3.2-3B-Instruct-SpinQuant_INT4_EO8, paligemma-3b-ft-vizwizvqa-448-jax and more — 10 compatible models indexed so far. Compatible models are determined by whether the model's memory footprint fits within the GPU's 8 GB VRAM, potentially using quantization (Q8, Q6, or Q4) to reduce memory usage.

Question 2

What is the cheapest cloud option for M60?

Accepted Answer

The cheapest on-demand option for the M60 is Microsoft Azure at $0.23/hr (Standard_NV6_Promo). We track pricing across 7 providers to help you find the best deal.

Question 3

Is M60 good for fine-tuning?

Accepted Answer

The M60 has limited capacity for fine-tuning with only 8 GB of VRAM. It can handle QLoRA fine-tuning of small models (up to ~3B parameters) but is not recommended for larger training workloads. Consider a GPU with more VRAM for serious fine-tuning.

Question 4

How much VRAM does M60 have?

Accepted Answer

The M60 has 8 GB of VRAM (GDDR5). It also offers 160 GB/s memory bandwidth, 9.6 TFLOPS of FP16 compute.

Question 5

What quantization formats work on M60?

Accepted Answer

The M60 supports the following quantization formats: Q8 (8-bit), Q6 (6-bit), Q4 (4-bit). Q4 quantization can fit models requiring up to ~32 GB at FP16 into 8 GB.

M60

Specifications

Cloud pricing

Compatible models

Compare this GPU

Frequently asked questions

VRAM	8 GB
Memory type	GDDR5
Bandwidth	160 GB/s
FP16 TFLOPS	9.6
FP8 support	No

M60