IBM Releases Granite 4.2: Bringing Native Reasoning and Agentic RL to Open Enterprise Models

IBM has released Granite 4.2, a family of open reasoning language models in 3B, 8B, and 30B parameter sizes. Unlike earlier Granite releases, which were instruction-following assistants, Granite 4.2 is built around explicit reasoning. Every model can emit a chain of thought before answering, and every model exposes a thinking / non-thinking switch plus a low-effort mode that spends a short reasoning budget on easy questions. The models are decoder-only dense transformers, pre-trained from scratch on roughly 15 trillion tokens, then post-trained through a multi-stage reinforcement learning chain. For the 8B and 30B, that chain includes an agentic RL block where the model learns to edit code, drive a terminal, and run web searches inside real sandboxed environments. All three ship under Apache 2.0. IBM also released two 470M-parameter Granite Speech 5.0 Turbo CTC models alongside the LLMs.

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‘> user: Whatu0027s the weather like in Boston right now?nn<think>nThe user is asking for the weather in Boston. Let me check thentools available. There is get_current_weather, which takes ancity parameter. I need to call it with city set to Boston.n</think>‘,
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reason:[[‘AIME25’,78.33,86.67,89.17],[‘HMMT Feb25’,66.67,78.33,89.17],[‘GPQA’,54.80,64.14,66.41],[‘LiveCodeBench v6’,69.71,73.24,75.77],[‘SciCode’,24.11,36.09,38.76],[‘MMLU-Pro’,67.84,74.04,77.60],[‘Arena-Hard-V2’,34.96,65.19,67.93]],
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