Roboflow

LLaVA-1.5 vs Qwen3.6 Plus

Compare LLaVA-1.5 and Qwen3.6 Plus side-by-side.

Compare LLaVA-1.5 vs Qwen3.6 Plus live

Run the same image across every model that supports a task and compare their outputs side-by-side.

These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.

Models in this comparison

LLaVA-1.5 vs Qwen3.6 Plus: Overview

LLaVA-1.5

LLaVA-1.5 is an open-source large multimodal model released in October 2023 by researchers at the University of Wisconsin-Madison and Microsoft Research. It builds on the original LLaVA architecture by introducing targeted refinements: switching the vision encoder to CLIP-ViT-L at 336-pixel resolution, replacing the projection layer with a two-layer MLP, and adding academic-task-oriented visual question answering data with response formatting prompts during training. These modifications achieve state-of-the-art performance across 11 benchmarks at release, with training completing in approximately one day on a single 8-A100 node.

The model accepts an image paired with a text prompt and generates natural language responses, supporting visual question answering, image captioning, and open-ended visual conversation. LLaVA-1.5 is available in 7B and 13B parameter variants built on the Vicuna language model, and is distributed under the Llama 2 Community License due to its Llama-2-based foundation. The original LLaVA paper was presented as an oral at NeurIPS 2023. Subsequent releases in the series (LLaVA-NeXT (LLaVA-1.6), LLaVA-NeXT-Video, and LLaVA-OneVision) are separate models with their own release pages and build on this foundation with expanded OCR, video, and multi-image capabilities.

Qwen3.6 Plus

Qwen3.6 Plus is a flagship model in Alibaba’s Qwen Plus series, designed for agentic workflows, coding, and multi-step reasoning. It supports a 1 million token context window and up to 65,536 output tokens, with built-in reasoning capabilities. The model is available as a hosted, proprietary API through Alibaba Cloud.

Compared to Qwen3.5, it improves reliability in multi-step execution and frontend code generation, with stronger performance on agentic coding tasks. It also supports document and image understanding, though its vision capabilities are more limited than dedicated Qwen-VL models. Qwen3.6 Plus is part of a broader Qwen ecosystem that includes both closed-source APIs and open-weight models.

LLaVA-1.5 vs Qwen3.6 Plus Comparison Table

PropertyLLaVA-1.5Qwen3.6 Plus
OrganizationMicrosoftQwen
Categoryopenclosed
Modalitymultimodalmultimodal
Release DateOct 2023Apr 2026
Context Window1.0M
Parameters7B, 13B
LicenseCustomProprietary
Pricing per 1M tokens
Input $/1M$0.325
Output $/1M$1.95
Vision Tasks
Vision Language
Visual Question AnsweringDemo
CaptioningDemo
Object Detection
OCRDemo
Model Features
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Visual Understanding
Overall Score
68.66%
Avg Response Time34.17s
Median input tokensincl. image tokens1.2K
Median output tokens47
Est. cost / taskon this benchmark$0.0005
Defect Detection
86.7%(13/15)
Document Understanding
77.8%(7/9)
Object Counting
20%(2/10)
Object Understanding
78.6%(11/14)
Spatial Understanding
68.4%(13/19)
OCR
Overall Score
58.52%
Avg Response Time5.49s
Median input tokensincl. image tokens124
Median output tokens18
Est. cost / taskon this benchmark$0.0001
Focused Scene OCR
76.8%(76/99)
Handwritten Math
80%(8/10)
License Plate Recognition
13.3%(4/30)
Text Recognition
50%(15/30)
VQA & Extraction
51.7%(31/60)

Output tokens (incl. reasoning) and est. cost / task are measured on this benchmark from a single low-temperature run, and shown only for models whose run covered at least 90% of prompts. Methodology