2026-10-11 16:38 UTC

Tencent claims its released EVIE visual-document retrieval models achieve 66.75 nDCG@10 on ViDoRe V3 using 4096-dimensional per-token embeddings that preserve layout, charts, and tables, potentially improving retrieval for visually structured document RAG.

state: seedheat: lowuncertainty: highknownscott: lowvisual-document-retrieval multimodal-rag open-modelsTencent

What is this?

Tencent has a visual-document retrieval model page on Hugging Face for EVIE-Preview-4.5B, which claims top ViDoRe rankings and native 128-dimensional token vectors. ViDoRe V3 evaluates multimodal document RAG, including interpretation of tables, charts, and images, cross-document synthesis, and source grounding; its retrieval metric includes nDCG@10. The supplied search summary repeats the case’s 66.75 score and 4096-dimensional embedding claim, but the underlying snippets do not substantiate that score or an EVIE-8B release, and the Tencent page instead specifies 128-dimensional vectors for the preview model. The claimed release details and layout-preservation benefits therefore remain unverified in this material.

Why it matters to Scott

The radar already tracks this development in radar:tencent-evie-128d-visual-retrieval; the supplied grounding does not verify the new 66.75 score, 4096-dimensional vectors, or EVIE-8B release. Visual retrieval touches Scott’s “Text Is the Model’s Home Turf” distinction—retain pixels when layout carries meaning—but this case supplies neither a validated comparison that changes that boundary nor a demonstrated improvement to his workflows.
ip:concept.text-is-the-models-home-turfradar:tencent-evie-128d-visual-retrieval
queries asked of Scott's wikis
  • visual document RAG versus OCR text extraction
  • multivector retrieval token embeddings index cost
  • chart table layout preservation knowledge ingestion
  • multimodal retrieval evaluation source grounding
  • self-hosted embedding models retrieval infrastructure

Measured heat

now 0 pts/hpeak 0 pts/hcomments 0/hpeers p0momentum: steady1 platformsage 822h
points/hour across evidence · reading as of 2026-10-12 02:59:37.977291+11:00 · deterministic, not a model opinion

How the heat travelled

09-07 09:47⭐ origin directly observedtencent/EVIE-8B and EVIE-4.5B (High-Capacity Visual Document Retrieval)
jacek2023 on r/LocalLLaMA
—
09-07 09:47amplified on r/LocalLLaMA 👑reddit.post.1w9nphc
jacek2023
peak 61 · 10 comments · 100% of case engagement
09-07 10:20our radar first saw it · +0.6hdiscovery anchor: reddit.post.1w9nphc—
pace: p64 vs 519 stories at the 720h mark (now 822h old) — ahead of hunterbench-live-pentesting-benchmark (1.0x), behind google-finland-15b-ai-investment (1.0x)

Evidence (1) — ⭐ canonical anchor

sourceobjectauthorscorecomments
🟠 reddit ⭐tencent/EVIE-8B and EVIE-4.5B (High-Capacity Visual Document Retrieval)
LocalLLaMA
jacek20235510

Interpretation history

Decision trace