v0.4.0

Added

• Three new provider targets for token estimation and dimension snapping: llama, qwen, deepseek (CLI --model, MCP target_model).
  • Llama 3.2 / 3.3 Vision (Mllama) — 560×560 tiles, aspect-ratio canvas capped at 4 tiles, ~1601 tokens/tile. Source: transformers MllamaVisionConfig. (Llama 4's native-multimodal vision encoder is a different scheme and is not modeled.)
  • Qwen2-VL / 2.5-VL / 3-VL — 28px effective grid (14px patch × 2×2 merge), tokens = (W/28)·(H/28) bounded to [4, 16384]. Source: qwen_vl_utils.smart_resize.
  • DeepSeek-VL2 — SigLIP-SO400M-384 + 2× pixel-shuffle (14×14 = 196 tokens/tile), anyres (m·384, n·384) canvas with m·n ≤ 9; exact token layout 210 (global) + 1 (separator) + (nh·14)·(nw·14 + 1). Source: DeepSeek-VL2 paper §2 (arXiv:2412.10302, 13 Dec 2024) + reference processor. Open-weights; the win is local-inference context, not API billing.
• Documentation site rebuilt on Nuxt UI + Nuxt Content (multi-page, auto sitemap / llms.txt / OG images). New per-provider pages with exact formulas, cited primary sources, verification dates, and proportional savings tables.

Notes

• Formula constants were verified against primary sources (model configs, reference tokenizer code, technical reports) on 2026-06-11. Hosted-API per-tile billing can differ from a model's own token footprint — treat absolute numbers as indicative and the tile/patch counts as authoritative.

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