h2ovl-mississippi-800m β€” CrispEmbed GGUF

Edge-sized H2OVL for CrispEmbed. Needs MSAC two-scale tiling and the h2ogpt2 prompt template (no BOS); the runtime handles both.

file size use
h2ovl-800m-q4_k.gguf 676 MB default β€” edge/WASM, transcribes
h2ovl-800m-q8_0.gguf 1175 MB quality tier, vision tower at F16

Both transcribe a full scanned page (q4_k 1749 chars, q8_0 1764). The registry ships q4_k deliberately: this is the small model, and the extra 499 MB does not change the decoded output.

Parity

Per-stage against a Python-blueprint reference (internvl2/h2ovl-mississippi-800m/ref.gguf in cstr/crispembed-regression-fixtures), CPU backend:

stage f16 q8_0
vis_proj_output 0.999701 0.999701
vis_pixel_unshuffle 0.998199 0.998199
llm_layer_0 1.000000 0.995712
llm_layer_2 1.000000 0.494781
decoded page transcribes transcribes

The f16 LLM is exact. Read the q8_0 llm_layer_2 figure with care: 0.494781 looks alarming and the model still transcribes the page correctly. The probe is a 5-token synthetic sequence, and on this checkpoint it does not track decoded quality β€” the value that matters is the sign. A comparable-magnitude but negative cosine (h2ovl-2b at q4_k, βˆ’0.27) does mean the output is wrong. The decoded roundtrip is the acceptance gate here, not the cosine.

Attribution

Upstream Β© H2O.ai, Apache-2.0 β€” see h2oai/h2ovl-mississippi-800m; vision tower InternViT-300M is MIT. Conversion and quantization do not relicense it. Per CrispEmbed POLICY.md, OCR output is a probabilistic reconstruction, not a faithful copy.

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