{ "disclosures": { "disclaimer": "Structured dataset metadata used for pre- and post-training IBM Granite 4 base and instruct models is being released as part of IBM's effort to provide the community with highly transparent open source model development. In this spirit, we are releasing metadata related to datasets directly ingested during training and metadata for datasets used to source seed data for IBM's synthetic data pipelines. This structured disclosure is provided in machine readable .JSON format as a governance artifact to inform risk-based controls for downstream model use. For more information on IBM's compliance with AI laws and regulations, go to: https://www.ibm.com/granite and https://www.ibm.com/granite/docs/resources/responsible-use-guide.pdf.", "timestamp": "2026-09-03T14:02:36Z", "model": { "name": "Granite-4.2-8b", "developer": "IBM", "family": "IBM Granite", "version": "4.2", "release_date": "08/25/2026", "approx_parameter_count": 8000000000, "active_approx_parameter_count": 8000000000, "intended_use": "Reasoning, Code Generation, Tool Calling, Agentic Workflows, Multilingual Dialog", "architecture": { "type": "Dense Transformer (Reasoning)", "transformer_class": "GraniteForCausalLM", "layers": 40, "embedding_size": 4096, "context_length": "128K", "head_dim": 128, "MLP_activation": "SwiGLU", "attention_heads": 32, "attention_head_dim": 128, "KV_heads": 8, "MLP_shared_expert_hidden_size": 12800, "positional_embeddings": { "type": "RoPE" } }, "license": { "type": "Apache License 2.0", "url": "https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/apache-2.0.md" } }, "pre-training": { "stage": "initial training phase", "methods": [ { "category": "web", "datasets": [ { "name": "GneissWeb", "url": "https://huggingface.co/datasets/ibm-granite/GneissWeb", "description": "GneissWeb is a large-scale dataset for LLM pretraining, consisting of around 10 trillion tokens. 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