Inkling
Thinking Machines Lab's open-weight multimodal MoE model with a 1M-token context and native text, image, and audio input.
Overview
Inkling is an open-weight multimodal large language model released by Thinking Machines Lab on July 15, 2026, built as a decoder-only mixture-of-experts model with 975B total and 41B active parameters (a smaller Inkling-Small variant has 276B total and 12B active parameters). It natively processes text, image, and audio inputs, was trained on roughly 45 trillion tokens spanning text, images, audio, and video, and supports a 1-million-token context window with variable reasoning-effort levels from "none" to "max."
This is a sourced directory entry. Features and capabilities are reported in the linked sources; this entry does not document independent Aymorphic testing.
Key features
- Decoder-only MoE: 975B total / 41B active parameters (Inkling-Small: 276B total / 12B active)
- Native multimodal input: text, image, and audio
- 1M-token context window with hybrid global/sliding-window attention
- Variable reasoning-effort levels and multi-token prediction layers for speculative decoding
- Available in BF16 and quantized NVFP4 variants
Use cases
- Long-context multimodal reasoning over mixed text, image, and audio inputs
- Self-hosted deployment on GPU clusters via Inference Endpoints
- Real-time voice and multimodal application prototyping
Pricing
Open-weight model, free to download; Hugging Face Inference Endpoints deployment on 8x RTX PRO 6000 quoted at $22/hour of uptime.
Pricing reflects the source record and may change. Confirm current terms with the provider.
Dates and sources
- Released
- 15 Jul 2026
- Record updated
- 23 Sept 2026
- Record last checked
- 23 Sept 2026