New Model: Inkling by Thinking Machine on Hugging Face
Thinking Machines announced Inkling, a massive open model with nearly one trillion parameters. It is designed as a natively multimodal architecture, accepting image, text, and audio inputs simultaneously. Key technical features include a Mixture-of-Experts (MoE) structure (975B total / 41B active params), a 1M token context window, and advanced deployment support across multiple frameworks like `transformers`, SGLang, vLLM, and `llama.cpp`. The model is available in BF16 and NVFP4 formats, facilitating high-performance inference on various hardware setups.
Key takeaways
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Multimodal Capability & Scale
3:50
Inkling is a true multimodal model that natively processes image, text, and audio inputs using a single architecture. It boasts an immense 1M token context window and was trained on 45T tokens.
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Architectural Innovations
5:10
The model utilizes relative attention (replacing RoPE) and a specialized SConv layer to efficiently aggregate hidden states, making it highly efficient for multimodal tasks compared to previous models.
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Deployment Flexibility
7:10
Inkling supports multiple deployment paths: BF16 (requiring ~2TB VRAM) and NVFP4 (600GB VRAM). It provides day-zero support for `transformers`, SGLang, vLLM, and `llama.cpp` (including GGUF quants via Unsloth), enabling diverse inference environments.