This is an AWQ 4-bit quantized version of the Qwen3-VL-2B-Instruct model, optimized for efficient inference while maintaining strong performance on vision and language tasks. It supports tool calling, multimodal inputs, and follows a specific chat template for instruction following. The model is suitable for deployment in resource-constrained environments.
Qwen3 VL 2B Instruct sits in PulseGate's Multimodal & vision category. It focuses on running efficient multimodal vision-language inference with reduced memory requirements. Qwen3 VL 2B Instruct is an open-source project aimed at developers deploying vision-language models. Qwen3 VL 2B Instruct is open source under the Open Source license. It runs on the web, the command line, and API.
cyankiwi builds and maintains Qwen3 VL 2B Instruct, and it first shipped in 2025. It competes in a saturated segment with 25 similar projects in PulseGate's index. Key capabilities include Vision-Language Processing, Quantized Inference, and Tool Calling Support. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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