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Thinking Machines Releases Inkling-Small, a 276B Parameter Mixture-of-Experts Model
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Thinking Machines Releases Inkling-Small, a 276B Parameter Mixture-of-Experts Model

Jul 30, 2026

On July 30, 2026, Thinking Machines released Inkling-Small, an open-weights Mixture-of-Experts model with 276 billion total and 12 billion active parameters. Despite being a quarter of the size of the original 975-billion-parameter Inkling, Inkling-Small achieves comparable performance, scoring 31.6% on Humanity's Last Exam and over 80% on SWEBench-Verified. The model features native multimodal capabilities for audio and vision, and matches its predecessor on safety benchmarks like StrongREJECT.

Inkling-Small model release

  • ▪Inkling-Small is available for fine-tuning on Tinker and for text, image, and audio chat on Tinker Playground as of July 30, 2026
  • ▪Thinking Machines released Inkling-Small, an open-weights artificial intelligence model, on July 30, 2026

Mixture-of-Experts architecture efficiency

  • ▪Inkling-Small is a Mixture-of-Experts transformer model featuring 276 billion total parameters and 12 billion active parameters
  • ▪Inkling-Small achieves comparable performance to the original Inkling model, which has 975 billion total parameters, at approximately one-quarter of its size

Agentic coding task performance

  • ▪Inkling-Small achieved a score exceeding 80% on the SWEBench-Verified benchmark using a bash-only harness
  • ▪Inkling-Small scored 31.6% on the Humanity's Last Exam benchmark, surpassing the original Inkling model's score of 29.7%

Multimodal audio processing

  • ▪Inkling-Small processes audio natively by representing it as dMel spectrograms within an encoder-free architecture
  • ▪Inkling-Small retains strong performance on speech understanding and long-form audio reasoning at a lower cost than the original Inkling model

Vision reasoning capabilities

  • ▪Inkling-Small processes images by dividing them into 40x40-pixel patches and transforming them using a four-layer hMLP
  • ▪Inkling-Small combines visual reasoning with Python operations like cropping, zooming, and programmatic image inspection to analyze documents and charts

Safety benchmarking results

  • ▪Inkling-Small is competitive in refusal and over-refusal rates on the FORTRESS benchmark, which measures safety across crime, violence, and dual-use risks
  • ▪Inkling-Small matches the performance of the original Inkling model on the StrongREJECT benchmark, which measures the refusal of harmful requests

1 source

Thinkingmachines
Introducing Inkling-Small
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Large language models (LLMs)Mixture of experts (MoE)Open-source AIAI foundation models

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