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Open-Weight Models

343 summarised stories about Open-Weight Models, each linking back to the original source. Browse all topics →

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Tuesday, 25 August 2026

IBM’s new Granite 4.2 models add reasoning and stay dense

The New Stack 1 month ago 33 ● 5 sources

IBM launched Granite 4.2, a new open-weight family of dense, decoder-only, reasoning-capable large language models with optional “thinking” behavior. The release ships models with 3 billion, 8 billion, and 30 billion parameters and was pre-trained on 15 trillion tokens. IBM positions the update as enabling enterprises to run multi-step agentic workflows more cheaply by limiting reasoning-token use on easy questions, while keeping overall architecture dense for flexible fine-tuning.

Perplexity Ships Portable Computer on NVIDIA DGX Spark: Local Harness, OS-Enforced Sandbox, and Zero Per-Token Cost for Local Steps

MarkTechPost 1 month ago 6 ● 5 sources

Perplexity released Portable Computer, a local-first agent platform that runs its agent harness, orchestrator, planner, tool routing, and post-trained models on NVIDIA DGX Spark with an OS-enforced sandbox. The DGX Spark hardware requirement is a GB10 superchip with 128 GB memory plus at least 1 TB storage. Local-handled steps incur no per-token charge, while steps needing live web or frontier reasoning require explicit per-step user approval before being sent to one of 15+ cloud models, changing how tasks escalate from device to the cloud.

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