
IBM released Granite 4.2 language models in 3B, 8B, and 30B sizes.
They are trained from scratch on about 15 trillion tokens.
The models can switch between thinking and non-thinking modes to save compute.
What happened
IBM released its Granite 4.2 language models in 3B, 8B, and 30B sizes. The models were trained from scratch on about 15 trillion tokens and support context windows up to 512,000 tokens.
Why it matters
The 8B and 30B variants undergo agentic RL training to use tools, write and run code, and search the web in real sandbox environments. The 30B model leads across all three agentic benchmarks, and all models run on vLLM or SGLang.
What to watch
IBM also introduced Granite Speech 5.0 Turbo CTC models with just 470 million parameters. They are twice as fast as the previous leaders on the Open ASR Leaderboard and can transcribe three hours of audio in one second.
Ask the AI about this article →
IBM's release of Granite 4.2 builds on the trend of open-weight models that aim to offer competitive performance in agentic workflows. The integration of agentic RL training in the 8B and 30B variants directly addresses the growing need for models that can interact with external tools and execute tasks autonomously. By supporting OpenAI-format tool calling and running on popular inference engines like vLLM or SGLang, IBM positions these models as practical options for developers integrating AI into production systems.
The availability of the models under the Apache 2.0 license on multiple platforms lowers the barrier for adoption, particularly for businesses looking to avoid proprietary lock-in. The Granite Speech 5.0 Turbo models, with their speed advantage on the Open ASR Leaderboard, complement the text models, potentially offering a comprehensive on-premise or hybrid AI toolset. As the landscape of open-weight models grows, performance on specialized tasks like agentic tool use will likely become a key differentiator for enterprises making deployment decisions.
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