Inkling 2 Small model demands 200GB RAM, posing local deployment hurdles

Running the new Inkling 2 Small model locally presents significant hardware challenges, primarily due to its 594 billion parameters. While the model supports 17 billion active parameters per token, the entire model must be accessible, requiring an estimated 190-200 GB of RAM and VRAM. This demand exceeds the capacity of typical consumer hardware, with even high-end solutions like dual DGX Sparks potentially falling short or requiring substantial workarounds. Furthermore, the availability of local weights and compatible software, such as specific llama.cpp pull requests, remains uncertain. AI

IMPACT Local deployment of large models like Inkling 2 Small requires significant hardware investment, potentially limiting accessibility for individual users and smaller organizations.

RANK_REASON The item discusses the practicalities and hardware requirements for running a specific large language model locally, rather than a new model release or significant research breakthrough.

Read on dev.to — LLM tag →

• colingauvin
• DataCamp
• DeepSeek
• DGX Spark
• Hacker News
• Inkling 2 Small
• llama.cpp
• MXFP8
• NVFP4
• Nvidia RTX Pro 6000 Blackwell Edition
• Thinking Machines
• Tinker
• Unsloth

• model release
• infra

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