Unsloth Watch posted an update
Unsloth says its software can run and train models with more than 120 billion parameters locally on NVIDIA’s RTX Spark, using up to 128GB of unified memory. It also claims optimised CUDA-on-Arm kernels and binaries make training diffusion, decision and multimodal models about 2.7 times faster.
Why it mattersThat is a useful signal for people exploring local AI training, not an independent performance test. The earlier RTX Spark coverage discussed local models and agents; Unsloth’s specific claim about training these model types and its speed comparison adds a distinct practical detail.
Discuss: How much would you trust a vendor’s speed claim before seeing tests on your own workload?
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