inclusionAI/Ling-3.0-flash-VL

image-text-to-text model by inclusionAI

Open original source ↗

Older snapshot: check the original source for current information.

From the publisher

Model card & documentation

Source preview

Read the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.

🤗 Hugging Face   |   🤖 ModelScope    We are introducing Ling-3.0-flash-VL, our next-generation native multimodal model. Built upon Ling-3.0-flash, it brings visual information into the complete process of understanding, reasoning, acting, and verification—advancing beyond image and video perception to solving real-world tasks through vision. With 124B total parameters, only 5.5B activated parameters per token, support for image and video inputs, and a context window of up to 256K tokens, Ling-3.0-flash-VL delivers powerful multimodal reasoning and agentic capabilities with exceptional efficiency. Ling-3.0-flash-VL inherits the language, reasoning, and long-context capabilities of Ling-3.0-flash, while extending them with native image and video understanding. The model has 124B total parameters, with only 5.5B parameters activated per token, and supports a context window of up to 256K tokens. The architecture of Ling-3.0-flash-VL is designed to integrate visual information into real-world reasoning and agentic workflows. Overall, these designs make vision more than just an input, integrating it…

inclusionAI/Ling-3.0-flash-VL on Hugging Face A short preview, not the full document.

Read the full model card ↗ · Preview checked 2026-10-30T11:34:33.586Z

Inside the original model card — Document outline
  1. Introduction
  2. Model Overview
  3. Evaluation
  4. Quickstart
  5. SGLang
  6. Install SGLang
  7. Run Inference
  8. vLLM
  9. Environment Preparation
  10. Run Inference
  11. Training content summary

Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.

Links from the model card

References supplied by the publisher, not independently verified endorsements. Check the destination before downloading files or entering credentials.

Documentation belongs to its respective authors. Reported project/model license: mit. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.

Model overview

inclusionAI/Ling-3.0-flash-VL is a image-text-to-text model repository published by inclusionAI on Hugging Face. A library was not reported.

This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.

Model facts

Task
image-text-to-text
Library
Not reported
Recent downloads (30 days)
6,426
Cumulative likes
96
Hugging Face trending score
53
Reported safetensors parameters
124,848,460,496
Architecture
BailingMoeV3VLForConditionalGeneration
License
mit
Access
Not gated by Hugging Face
Created
2026-09-04T15:24:37.000Z
Last modified
2026-09-11T00:49:28.000Z

Compatibility and lineage

Language coverage was not reported.

Base-model lineage was not included.

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

Use and evaluate

Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.

No model weights are downloaded or executed by AltAPIs. Never enable remote model code without reviewing it.

Model card and usage instructions

Model files and configuration

Community discussion

Source and freshness

Source: Hugging Face Hub. Metadata observed 2026-09-17T06:34:57.398Z. Daily imports are snapshots, not real-time monitoring.

Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.

Open original source

Related models

google/gemma-4-31B-it

ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF

Qwen/Qwen3.8-27B

Qwen/Qwen3.5-4B

Qwen/Qwen3-VL-8B-Instruct

Qwen/Qwen3.5-9B