Qwen3.5 35B A3B vs Qwen3 VL 30B A3B Instruct
Compare Qwen3.5 35B A3B and Qwen3 VL 30B A3B Instruct side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.
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Qwen3.5 35B A3B vs Qwen3 VL 30B A3B Instruct: Overview
The Qwen3.5-35B-A3B is a native vision-language model developed by Alibaba Cloud’s Qwen team, released on February 24, 2026, as a high-efficiency entry in the Qwen 3.5 family. It utilizes a sophisticated hybrid architecture that integrates Gated Delta Networks with a sparse Mixture-of-Experts (MoE) system. While the model houses 35 billion total parameters, its routing mechanism activates only 8 routed experts and 1 shared expert per token, totaling approximately 3 billion active parameters. This design achieves cross-generational parity with the previous flagship Qwen3-235B dense model, delivering comparable reasoning and multimodal intelligence with significantly reduced inference latency and compute requirements. Available under the Apache 2.0 license, it is released in both base and instruction-tuned variants for seamless integration with open-source stacks like vLLM and Hugging Face Transformers.
Designed for the emerging era of agentic AI, the model utilizes a unified multimodal foundation built through early-fusion training. This approach allows it to outperform the prior Qwen3-VL series in spatial grounding, document analysis, and UI/GUI interaction. It features a native context window of 262,144 tokens, which is extensible up to 1,010,000 tokensvia RoPE scaling, and provides global support for 201 languages and dialects. This combination of a compact active parameter count and frontier-level visual comprehension makes it a versatile tool for developers requiring a balance of high-throughput speed and sophisticated visual reasoning for long-context workflows.
Qwen3 VL 30B A3B Instruct is an open-weight multimodal large language model developed by Alibaba as part of the Qwen family, built for instruction-following tasks that unify text generation with visual and video understanding. Released around October 2025 under the Apache-2.0 license, it targets efficient, high-fidelity vision-language reasoning across very long contexts.
The model accepts text and image inputs and produces text outputs, with strong performance in OCR, spatial reasoning, long-video understanding, and agentic or GUI-centric visual tasks. It uses a Mixture-of-Experts (A3B) design with ~31.1B total parameters and ~3B active per token, paired with Qwen3-VL’s unified multimodal stack (including Interleaved-MRoPE and DeepStack fusion) to process text, images, and video in a single architecture. OCR support expands to 32 languages, enhancing document workflows. With a native ~262K token context window (extendable further), it stands out today for its balance of scale, efficiency, long-context support, and open accessibility in multimodal systems.
Qwen3.5 35B A3B vs Qwen3 VL 30B A3B Instruct Comparison Table
| Property | Qwen3.5 35B A3B | Qwen3 VL 30B A3B Instruct |
|---|---|---|
| Organization | Qwen | Qwen |
| Category | open | open |
| Modality | multimodal | multimodal |
| Release Date | Feb 2026 | Oct 2025 |
| Context Window | 262K | 262K |
| Parameters | 35B | 31B |
| License | Apache 2.0 | Apache 2.0 |
| Pricing per 1M tokens | ||
| Input $/1M | $0.140 | $0.130 |
| Output $/1M | $1.00 | $0.520 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Object Detection | ||
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalspass/fail results · 67 prompts Score key:≥75%40–74%<40% | ||
| Visual Understanding | ||
| Overall Score | 79.1% | |
| Avg Response Time | 20.94s | |
| Defect Detection | 93.3%(14/15) | |
| Document Understanding | 77.8%(7/9) | |
| Object Counting | 40%(4/10) | |
| Object Understanding | 85.7%(12/14) | |
| Spatial Understanding | 84.2%(16/19) | |