Inkling is the latest open-weights multimodal foundation model from Thinking Machines Lab, released on July 15, 2026. Built as a mixture-of-experts transformer, Inkling features 975 billion parameters with 41 billion active, supports a context length of up to one million tokens, and accommodates inputs in text, image, and audio formats. A smaller variant, Inkling-Small, shares the same foundational architecture with 276 billion parameters and 12 billion active parameters, offering many of the same strengths at lower compute cost and latency.<\/p>\n
Inkling is designed for business owners, developers, and decision-makers who require a foundation model that can be customized to domain-specific workflows. It is particularly suited for organizations with needs in coding assistants, long-context document processing, multimodal analysis (e.g. image and audio tasks), AI agents or tools requiring web interaction, and applications where cost or latency are constraints. Inkling-Small is targeted at those who want similar core strengths with lower resource demands, ideal for experimentation, deployment in less powerful environments, or workloads sensitive to inference cost.<\/p>\n
Inkling is available via the Tinker platform, Thinking Machines Lab\u2019s API for model customization, fine-tuning, and inference. For a limited time, users can access Inkling and Inkling-Small at 50% discount. Pricing is usage-based, billed per million tokens. For Inkling at a 64K context window, input (\u201cprefill\u201d) tokens cost approximately $1.87\/M, with output (\u201csample\u201d) tokens at $4.68\/M and training (forward + backward passes) at $5.61\/M. Extended 256K context incurs higher token costs roughly double those of the 64K context variant. Inkling-Small follows a similar structure but with lower per-token rates: $0.58 for prefills (64K context), $1.44 for sample-token output, and similar scaled train costs. Context window sizes of 64K and 256K tokens are supported. Token-cache mechanisms offer heavily discounted prefill rates when inputs hit cache. Storage of checkpoints is priced separately, typically at around $0.10 per gigabyte per month.<\/p>\n
Inkling represents a carefully balanced open-weights model that emphasizes versatility and accessibility alongside capability. It won\u2019t be the absolute top performer in every benchmark compared to closed-source frontier models, but its strengths lie in broad support for multimodal tasks, adjustable computation trade-offs, and open distribution under an Apache 2.0 license. For businesses prioritizing customization, control, domain specificity, or cost containment, Inkling offers a viable and compelling option. Organizations considering adoption should assess whether they need the extended context variants, prepare for infrastructure demands if self-hosting, and plan for fine-tuning workflows to unlock Inkling\u2019s full potential in their use cases.<\/p>\n
Keep up to date with our stories on LinkedIn, Twitter, Facebook and Instagram.<\/p>\n
Built by our team member Maziar Foroudian, Mazi is an intelligent agent designed to research across trusted websites and craft insightful, up-to-date content tailored for business professionals.<\/p>\n
Learn why choosing an MAS-licensed cryptocurrency exchange ensures maximum security and transparency.<\/p>\n
How telematics and fleet technology help businesses cut costs, reduce downtime, improve productivity, and make smarter operational decisions.<\/p>\n
Essential guide for Australian SMEs on navigating the AI search revolution and maintaining online visibility in 2026.<\/p>\n
Planet Ark\u2019s revamped recycling equipment catalogue helps businesses reduce waste, lower costs, improve recycling performance, and achieve sustainability goals efficiently.<\/p>\n
How a maths-based judging system is eliminating bias and reshaping trust in global business awards.<\/p>\n