tencent · Released Oct 22, 2026 · observed 23 Oct 2026
Public-source support evidence
Exact checkpoint execution is unverified. The architecture is listed in llama.cpp, MLX / mlx-lm, and vLLM.
tencent/WeVisOne-VL-4B
WeVisOne-VL-4B is an image text to text model published by tencent on Hugging Face. We have not written a summary yet; see the model card ↗.
View source model ↗SUPPORT EVIDENCE
The model config architecture is listed in this runtime registry. This is family/architecture evidence only; exact checkpoint loading, model-specific configuration, hardware, and generation were not tested.
Checked 2026-10-23 19:47 UTC
Evidence source ↗The exact model and runtime-specific sources were checked; no positive model-level evidence was established.
Checked 2026-10-23 19:28 UTC
Version v0.40.10
Checked source ↗The exact model and runtime-specific sources were checked; no positive model-level evidence was established.
Checked 2026-10-23 19:26 UTC
Checked source ↗The model config architecture is listed in this runtime registry. This is family/architecture evidence only; exact checkpoint loading, model-specific configuration, hardware, and generation were not tested.
Checked 2026-10-23 19:47 UTC
Evidence source ↗The model config architecture is listed in this runtime registry. This is family/architecture evidence only; exact checkpoint loading, model-specific configuration, hardware, and generation were not tested.
Checked 2026-10-23 19:47 UTC
Evidence source ↗MLX community uploads may target mlx-vlm; an upload observation does not establish mlx-lm compatibility.
MEMORY ESTIMATES
Which file should I grab?
No observed complete artifact currently qualifies.Unknown: no observed complete artifact fits this capacity with documented headroom.
Which file should I grab?
No observed complete artifact currently qualifies.Unknown: no observed complete artifact fits this capacity with documented headroom.
Which file should I grab?
No observed complete artifact currently qualifies.Unknown: no observed complete artifact fits this capacity with documented headroom.
Which file should I grab?
No observed complete artifact currently qualifies.Unknown: no observed complete artifact fits this capacity with documented headroom.
Which file should I grab?
No observed complete artifact currently qualifies.Unknown: no observed complete artifact fits this capacity with documented headroom.
Which file should I grab?
No observed complete artifact currently qualifies.Unknown: no observed complete artifact fits this capacity with documented headroom.
Which file should I grab?
No observed complete artifact currently qualifies.Unknown: no observed complete artifact fits this capacity with documented headroom.
Which file should I grab?
No observed complete artifact currently qualifies.Unknown: no observed complete artifact fits this capacity with documented headroom.
Memory estimates are the observed file size plus fixed headroom (20% plus 1.5 GB runtime allowance); real needs also depend on context length, KV cache and runtime settings. Fit is an estimate; it does not establish runtime compatibility, speed, context length, or hardware performance. Text-weights-only estimates do not include a projector or total vision memory where unknown.
Terms: a quant is a lower-precision version of the weights; GGUF is a file format used by llama.cpp and compatible apps; MLX targets Apple silicon; vLLM is a model-serving engine for NVIDIA GPUs; the KV cache is stored attention state that grows with context length. Terms explained ↗
OBSERVED FILES
Sizes and file groups come from the listed uploader repositories. A size is marked as an estimated fit only for a complete observed GGUF quant group.
No observed quant uploads in this snapshot.
CURATED TRACKING
No curated issues verified for this snapshot. An empty list does not mean there are no bugs.
HARDWARE NOTES
No execution or benchmark results are published for this model yet.
COMPARE
No comparison page is generated for this model yet. Browse all comparisons →
EMBED
Works in GitHub READMEs and Hugging Face model cards. The badge updates when the site rebuilds.