CrystalFormer v0.6 is a unified autoregressive transformer foundation model for inorganic crystalline materials that supports both de novo generation (DNG) and crystal structure prediction (CSP) within a single probabilistic framework. By leveraging space group symmetry to compactly represent crystals, the model seamlessly switches between unconditional generation and formula-conditioned prediction — no architectural changes required.