Another open-weight release from @thinkymachines 👀 Inkling-Small is here. With native reasoning…
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TL;DR - Thinking Machines released Inkling-Small, an open-weights multimodal MoE model (276B total / 12B active) that reportedly matches the larger Inkling at a quarter of its size, and NVIDIA is amplifying it with an NVFP4 checkpoint for fine-tuning on NeMo/DGX Station.
- Mixture-of-Experts architecture: 276B total parameters with only 12B active per token, targeting Inkling-level quality at ~1/4 the size.
- Natively reasons over text, images, and audio, with controllable/variable "thinking effort" as a user-tunable knob.
- Full weights are open; an NVFP4-quantized checkpoint is published on Hugging Face for low-precision inference and fine-tuning on NVIDIA NeMo + DGX Station.
- Available to fine-tune via Thinking Machines' Tinker platform and to try interactively in Tinker Playground; no benchmark numbers are given in the post beyond the "comparable performance" claim.
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Another open-weight release from @thinkymachines 👀 Inkling-Small is here. With native reasoning…
Public signals
N/A
TL;DR - Thinking Machines released Inkling-Small, an open-weights multimodal MoE model (276B total / 12B active) that reportedly matches the larger Inkling at a quarter of its size, and NVIDIA is amplifying it with an NVFP4 checkpoint for fine-tuning on NeMo/DGX Station.
- Mixture-of-Experts architecture: 276B total parameters with only 12B active per token, targeting Inkling-level quality at ~1/4 the size.
- Natively reasons over text, images, and audio, with controllable/variable "thinking effort" as a user-tunable knob.
- Full weights are open; an NVFP4-quantized checkpoint is published on Hugging Face for low-precision inference and fine-tuning on NVIDIA NeMo + DGX Station.
- Available to fine-tune via Thinking Machines' Tinker platform and to try interactively in Tinker Playground; no benchmark numbers are given in the post beyond the "comparable performance" claim.