From the source
Today, we are releasing Inkling-Small, an efficient open-weights model that achieves comparable performance to Inkling at a quarter of its size.
Inkling-Small is a Mixture-of-Experts transformer with 276B total parameters, 12B active, trained on NVIDIA GB300 NVL72 systems.
Like Inkling, it features native reasoning over audio and images, variable thinking effort, a context window of up to 1M tokens, and well-rounded performance across a range of benchmarks.
Inkling-Small Inkling Compared to Inkling, Inkling-Small achieves comparable performance with much less compute.
Across agentic tool use (Terminal-Bench 2.1), reasoning (HLE text-only, no tools), and instruction following (IFBench) benchmarks, Inkling-Small is more efficient than Inkling and competitive with other models in its weight class.
Furthermore, its variable thinking effort lets users easily adapt it to target their use case, balancing cost and performance.
We are releasing the full weights of Inkling-Small.
We’re also making it available for fine-tuning on Tinker, and for text, image, and audio chat on Tinker Playground .
Capabilities As we build our model family, we are always iterating on our approach.
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