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Batch Inference is now generally available on Runpod Serverless

Tencent

WeVisOne VL 2B

Tencent's 2B-parameter open vision-language model with a 256K-token context, ready to serve on Runpod Serverless with vLLM or on a Pod.

Vision + language
Text generation
2B · 256K context
See deploy options

WeVisOne VL 2B

Specifications

Provider
Tencent
Modality
Vision + language
Task
Text generation
Parameters
2B
Active parameters
Context
256K tokens
Precision
BF16
Weights
5
License
apache-2.0
Released
2026-10-21
Endpoint ID
Weights on Hugging Face
tencent/WeVisOne-VL-2B

Frequently asked questions

How do I deploy WeVisOne VL 2B on Runpod?

Deploy the vLLM worker from the Runpod Hub as a Serverless endpoint and set MODEL_NAME to tencent/WeVisOne-VL-2B. The endpoint is OpenAI-compatible and scales to zero when idle. You can also run vLLM on a Pod.

What GPU do I need to run WeVisOne VL 2B?

Start with RTX 4090 (24 GB VRAM). The weights take about 5 GB; longer contexts and more concurrent requests need extra memory for the KV cache.

How much does WeVisOne VL 2B cost on Runpod?

Serverless endpoints and Pods bill per second for the GPU you choose. A Serverless endpoint costs nothing while scaled to zero.

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No items found.
tencent-wevisone-vl-2b
tencent/WeVisOne-VL-2B
Vision + language
2026-10-21 17:00
RTX 4090