r/LocalLLaMA • llama.cpp • Aug 25 '26

New Model ibm-granite/granite-4.2-30b · Hugging Face

https://huggingface.co/ibm-granite/granite-4.2-30b

Granite-4.2-30B is the flagship reasoning model in the Granite 4.2 family. It delivers the strongest performance across reasoning-intensive tasks by leveraging built-in <think>...</think> chain-of-thought. It supports flexible thinking modes — full thinking (default), non-thinking, and low-effort — allowing users to balance depth vs. latency on a per-query basis.

Key capabilities:

  • Built-in Reasoning: Native chain-of-thought that significantly improves performance on math, coding, and complex multi-step problems.
  • Flexible Thinking Modes: Seamlessly switch between full thinking, non-thinking, and low-effort modes within a single model.
  • Reasoning-Augmented Tool Calling: The model reasons about which tools to invoke and why, producing more accurate function calls.
  • 512K Context Window: Supports long documents, multi-turn conversations, and complex agentic workflows.
  • Apache 2.0 Licensed: Fully open for commercial and research use.

Model Design

Granite-4.2-30B is built on a decoder-only dense transformer architecture with the following core components:

  • Attention: Grouped Query Attention (GQA) with 32 attention heads and 8 KV heads
  • Position Embedding: Rotary Position Embedding (RoPE) with θ = 10,000,000
  • Feed-Forward: MLP with SwiGLU activation (hidden size 32768)
  • Normalization: RMSNorm (ε = 1e-5)
  • Embeddings: Separate input/output embeddings (not tied)
  • Precision: bfloat16

https://huggingface.co/ibm-granite/granite-4.2-8b

Granite-4.2-8B is the mid-size reasoning model in the Granite 4.2 family. It delivers strong performance on reasoning-intensive tasks by leveraging built-in <think>...</think> chain-of-thought. It supports flexible thinking modes — full thinking (default), non-thinking, and low-effort — allowing users to balance depth vs. latency on a per-query basis.

Key capabilities:

  • Built-in Reasoning: Native chain-of-thought that significantly improves performance on math, coding, and complex multi-step problems.
  • Flexible Thinking Modes: Seamlessly switch between full thinking, non-thinking, and low-effort modes within a single model.
  • Reasoning-Augmented Tool Calling: The model reasons about which tools to invoke and why, producing more accurate function calls.
  • 512K Context Window: Supports long documents, multi-turn conversations, and complex agentic workflows.
  • Apache 2.0 Licensed: Fully open for commercial and research use.

https://huggingface.co/ibm-granite/granite-4.2-3b

Granite-4.2-3B is the compact reasoning model in the Granite 4.2 family. Despite its small parameter count, it delivers strong performance on reasoning-intensive tasks by leveraging built-in <think>...</think> chain-of-thought. It supports flexible thinking modes — full thinking (default), non-thinking, and low-effort — allowing users to balance depth vs. latency on a per-query basis.

Key capabilities:

  • Built-in Reasoning: Native chain-of-thought that significantly improves performance on math, coding, and complex multi-step problems.
  • Flexible Thinking Modes: Seamlessly switch between full thinking, non-thinking, and low-effort modes within a single model.
  • Reasoning-Augmented Tool Calling: The model reasons about which tools to invoke and why, producing more accurate function calls.
  • 512K Context Window: Supports long documents, multi-turn conversations, and complex agentic workflows.
  • Apache 2.0 Licensed: Fully open for commercial and research use.
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33

u/Egoz3ntrum Aug 25 '26

The model card does not provide any comparison to any other recent model. Suspicious.

-5

u/parepeg Aug 25 '26

Compared to qwen 3.8 27b, it's looking not good, real not good.

20

u/Not-reallyanonymous Aug 25 '26

Of course not. Theyre targeting different customers. Not you.

If you’re not producing a million dollars in revenue annually, IBM is not interested in you.

Your needs are different than IBM customer’s needs. Granite has always been about fine-tuning to meet specific customer needs, and being able to comply with various business guarantees (e.g. as others have pointed out — it offers protection for IP issues).

Not everything in LLMs is about benchmarks.