# Tencent/WeMM-Embedding

> A family of universal multimodal embedding models from Tencent's WeChat Vision team (2B, 4B, 9B) producing unified vectors for text, images, videos, visual documents, and interleaved multimodal inputs. Supports Matryoshka dimensions and serving via vLLM/SGLang.

- Magnitude: 1.0 out of 10 — Steady
- Stars: 1,713 total · +0 stars on 2026-10-04 (UTC), ≈ 6 by evening
- Star trust: star growth looks organic
- Category: Language models · Language: Python · Created: 2026-08-25 · Last push: 2026-09-20
- GitHub: https://github.com/Tencent/WeMM-Embedding · Page: https://gitnova.dev/en/r/Tencent/WeMM-Embedding

## Useful for

- Build multimodal retrieval over a mixed corpus of images, videos, and documents with one index
- Truncate embeddings to 256 dimensions via Matryoshka to save memory with minimal quality loss
- Serve embeddings for text and video online using vLLM or SGLang

## Why it’s here

- 0 stars so far today, about 6 expected by the end of the day.
- The repository is 40 days old and already has 1,713 stars.

## Star trust

Star growth looks organic.

Star-trust labels are heuristics based on the repository’s behavior, not a check of every stargazer.

## Numbers

- Forks: 120
- Issues and pull requests: 13
- Watchers: 11
- Average over the last week: 5 per day
- Usual pace: 18 per day

## Stars per day, last 30 days (oldest → newest, today is partial)

2026-09-30 … 2026-10-29: 2, 5, 1, 6, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None

## Magnitude by day, last 14 days

09-21 1.4, 09-22 1.2, 09-23 1.3, 09-24 1.2, 09-25 0.8, 09-26 1.0, 09-27 1.1, 09-28 1.1, 09-29 1.2, 09-30 1.3, 10-01 1.0, 10-02 1.1, 10-03 0.8, 10-04 1.0

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Magnitude (0–10) measures how fast and how unusually interest in a repository is growing right now. It is not a quality score.
Days are UTC. “So far today” is a fact; “expected by the end of the day” is a forecast.
Summaries and use cases are written by an LLM (DeepSeek V4.1 Flash) from the README and may be inaccurate: verify specific claims (benchmarks, speed, hardware) in the repository itself.
Data as of 2026-10-04 00:26 UTC, updated every 30 minutes.