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 Foundation models & chat category. It focuses on running efficient multimodal vision-language inference with reduced memory requirements. It is built as an open-source project for developers deploying vision-language models. Qwen3 VL 2B Instruct is open source under the Open Source license. Qwen3 VL 2B Instruct is available on the web, the command line, and API.
cyankiwi builds and maintains Qwen3 VL 2B Instruct, and the product first shipped in 2025. The category is crowded — PulseGate's index counts 25 comparable apps. Key capabilities include Vision-Language Processing, Quantized Inference, and Tool Calling Support. It exposes integrations via a public API.
Latest indexed changes and source events
cyankiwi/Qwen3-VL-2B-Instruct-AWQ-4bit verified by the PulseGate indexer
Other apps tracked under the same category.
