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Inkling – Open-Weights 975B Parameter LLM

Inkling, a 975-billion-parameter open-weights large language model with only 41 billion active parameters, is now available for fine-tuning, enabling developers to reduce computational costs while maintaining performance across text, image, and speech tasks. The model, released by Thinking Machines AI, cuts GPU memory needs by approximately 20 times and matches top-tier performance on code, math, and multimodal benchmarks.

read1 min views49 publishedJul 16, 2026
Inkling – Open-Weights 975B Parameter LLM
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Inkling – Open-Weights 975B Parameter LLM

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A 975B parameter LLM with only 41B active parameters is now available for fine-tuning, enabling developers to potentially reduce the computational cost of customizing large models while maintaining their performance; this capability matters because it allows for more efficient domain adaptation without sacrificing the model's multimodal capabilities and tool usage.

975B-parameter open-weights model with only 41B active at inference, cutting GPU memory needs by ~20× while matching top-tier performance on code, math, and multimodal tasks. This lets you deploy a single model that handles text, images, and speech in production without swapping architectures, and fine-tune it on your own data for domain-specific workflows without hitting memory walls. Expect lower cloud costs and faster iteration, but watch for calibration drift if you push thinking-time too low.

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