Qwen3-VL-235B-A22B vs GLM 4.5V: Which Handles Visual Code Better?

As small businesses look to adopt AI for tasks like document parsing, customer support, visual automation, or coding assistance, the choice between powerful open-source models like Qwen3-VL-235B-A22B and GLM 4.5V can feel overwhelming. What’s the real difference between their performance, cost, accessibility, and deployment difficulty?

This article breaks down the comparison across architecture, application capabilities, performance benchmarks, pricing, and access methods, giving you a clear path to decide which model suits your business best. Whether you’re building intelligent workflows, deploying locally, or calling APIs, this guide helps you make an informed, confident choice.

What Can Qwen3-VL-235B-A22B and GLM 4.5V Really Do For Your Small Business?

Want to see which model fits your workflow best?
Both Qwen3-VL-235B-A22B and GLM 4.5V offer free online demos from Novita AI!

Try GLM 4.5V Now!

Try Qwen 3 VL 235B A22B Now!

Application Area	Qwen3-VL-235B-A22B	GLM 4.5V	Who Wins
GUI Interaction	Operates PC/mobile UIs, understands interface elements, invokes tools.	Supports screen reading and basic desktop actions.	May Tie
Visual-to-Code Generation	✅ Converts screenshots/videos into HTML, CSS, JS, Draw.io diagrams.	❌ No visual-to-code capabilities disclosed.	Qwen Wins
3D & Spatial Reasoning	✅ Advanced: recognizes object position, occlusion, viewpoint; enables 3D grounding.	⚠️ Handles spatial layout across images, no 3D grounding or embodied AI.	Qwen Wins
Video Understanding	✅ Handles hours-long videos with 256K–1M token context; fine-grained temporal analysis.	⚠️ Supports event segmentation but likely limited by 66K token window.	Qwen Wins
Visual Recognition Scope	✅ Trained to “recognize everything”: celebrities, anime, rare species, landmarks, signs, ancient text.	⚠️ Strong scene analysis, but no claim of niche/rare entity recognition.	Qwen Wins
OCR/Text Extraction	✅ 32 languages, robust under blur/tilt, supports rare/ancient characters and structured layouts.	⚠️ Extracts long documents well but lacks language and rare-text breadth.	Qwen Wins
Text Understanding	✅ Comparable to pure LLMs; fluent vision-text fusion with no comprehension loss.	✅ Strong generator with “reasoning mode” toggle; high language quality.	May Tie
Ease of Access	Available via API or demo.	Available via API or demo and a Desktop Assistant supporting images, PDFs, videos, etc.	GLM Wins

How Do Qwen3-VL-235B-A22B and GLM 4.5V Differ in Architecture?

Qwen3-VL stands out as the “heavyweight” option, prioritizing scale and information capacity: its 235B total parameters, 256K (expandable to 1M) token context window, and specialized reasoning variants make it ideal for large-scale tasks.

GLM 4.5V, by contrast, emphasizes flexibility and efficiency without sacrificing performance. Its more compact 106B parameter design, 128K token context window, and unified model with a toggleable “Thinking Mode” strike a balance between speed and depth

Comparison Dimension	Qwen3-VL-235B-A22B	GLM 4.5V
Model Size & MoE Architecture	Total Parameters: 235B Active Parameters per Input: 22B	Total Parameters: 106B Active Parameters per Input: 12B
Context Window Capacity	Native: 256K tokens Expandable to: 1M tokens	Native: 128K tokens
Reasoning & Instruction Modes	a Thinking Mode switch, allowing users to balance between quick responses and deep reasoning.	a Thinking Mode switch, allowing users to balance between quick responses and deep reasoning.
Visual Processing	ViT-based encoder + text decoder Enhancements: Interleaved-MRoPE (video reasoning), fused vision features	ViT-based encoder + text decoder Enhancement: Clean adapter for vision-language fusion
Speed	Latency in 1.8-2s	Lantecy in 0.3-1.5s
Hardware Requirements	8 NVIDIA H200 GPUs.	a single 80GB GPU (like one NVIDIA A100/H100 80GB) in 16-bit precision

So,which Model Performs Better: Qwen3-VL-235B-A22B or GLM 4.5V?

Qwen3-VL-235B-A22B generally leads in core reasoning, document processing, and code generation. GLM 4.5V performs closely in several tasks but doesn’t surpass Qwen in any shown benchmark.

Category	Benchmark	Qwen3-VL-235B-A22B	GLM 4.5V
1. General VQA	MMbench v1.1	89.9	88.2
	MMStar	78.4	75.3
	MUIRBENCH	72.8	75.3
	HallusionBench	63.2	65.4
2. STEM & Puzzle	MMMU (val)	78.7	75.4
	MMMU Pro	68.1	65.2
	MathVista	84.9	84.6
	MathVision	66.5	65.6
	MathVerse	72.5	72.1
	AI2D	89.7	88.1
3. Long Doc & OCR/Chart	MMLongBench-Doc	57.0	44.7
	OCRBench	920.0*	86.5
4. Coding	Design2Code	92.0	82.2
5. Video Understanding	VideoMME (w/o sub)	79.2	74.6

You can also use a Novita AI API key to access GLM’s Desktop Assistant for free—no payment required, unlike the official site!

The Desktop is designed for the GLM series multimodal models (GLM-4.5V, compatible with GLM-4.1V), supporting interactive conversations with text, images, videos, PDFs, PPTs, and more. It connects to the GLM multimodal API to enable intelligent services across various scenarios.

The setting:

Model name:zai-org/glm-4.5v

API URL:https://api.novita.ai/openai

Endpoint: /v1/chat/completions

API Key: from Novita AI

Get API Key and Try Free GLM’s Desktop Assistant Now!

How to Access Qwen3-VL-235B-A22B and GLM 4.5V in Cheap and Fast Way?

Novita AI offers Qwen3-VL APIs with a 131K context window at $0.98 per input and $3.95 per output. It also provides GLM-4.6V APIs with a 208K context window at $0.60 per input and $2.20 per output, supporting structured outputs and function calling.

1. Web Interface (Easiest for Beginners)

2. API Access (For Developers)

Step 1: Log In and Access the Model Library

Log in to your account and click on the Model Library button.

Step 2: Choose Your Model

Browse through the available options and select the model that suits your needs.

Step 3: Start Your Free Trial

Begin your free trial to explore the capabilities of the selected model.

Step 4: Get Your API Key

To authenticate with the API, we will provide you with a new API key. Entering the “Settings“ page, you can copy the API key as indicated in the image.

Step 5: Install the API

Install API using the package manager specific to your programming language.

After installation, import the necessary libraries into your development environment. Initialize the API with your API key to start interacting with Novita AI LLM. This is an example of using chat completions API for python users.

from openai import OpenAI
  
client = OpenAI(
    base_url="https://api.novita.ai/openai",
    api_key="session_UxQ9B4FllYcK6ZwMw6OFh5Q15fFCM4gMHoTbNh4vB3ZF_Dc5yN4RzVXxOHjarOF-AhMO61lRJN8plthUCfFvZA==",
)

model = "qwen/qwen3-vl-235b-a22b-thinking"
stream = True # or False
max_tokens = 16384
system_content = "Be a helpful assistant"
temperature = 1
top_p = 1
min_p = 0
top_k = 50
presence_penalty = 0
frequency_penalty = 0
repetition_penalty = 1
response_format = { "type": "text" }

chat_completion_res = client.chat.completions.create(
    model=model,
    messages=[
        {
            "role": "system",
            "content": system_content,
        },
        {
            "role": "user",
            "content": "Hi there!",
        }
    ],
    stream=stream,
    max_tokens=max_tokens,
    temperature=temperature,
    top_p=top_p,
    presence_penalty=presence_penalty,
    frequency_penalty=frequency_penalty,
    response_format=response_format,
    extra_body={
      "top_k": top_k,
      "repetition_penalty": repetition_penalty,
      "min_p": min_p
    }
  )

if stream:
    for chunk in chat_completion_res:
        print(chunk.choices[0].delta.content or "", end="")
else:
    print(chat_completion_res.choices[0].message.content)
  
  

3. Local Deployment (Advanced Users)

Requirements:

• Qwen3-VL-235B-A22B: 8 NVIDIA H200 GPUs.
• GLM 4.5V: a single 80GB GPU (like one NVIDIA A100/H100 80GB) in 16-bit precision

Installation Steps:

1. Download model weights from HuggingFace or ModelScope
2. Choose inference framework: vLLM or SGLang supported
3. Follow deployment guide in the official GitHub repository

4. Integration

Using CLI like Trae,Claude Code, Qwen Code

If you want to use Novita AI’s top models (like Qwen3-Coder, Kimi K2, DeepSeek R1) for AI coding assistance in your local environment or IDE, the process is simple: get your API Key, install the tool, configure environment variables, and start coding.

For detailed setup commands and examples, check the official tutorials:

• Trae : Step-by-Step Guide to Access AI Models in Your IDE
• Claude Code:How to Use Kimi-K2 in Claude Code on Windows, Mac, and Linux
• Qwen Code:How to Use OpenAI Compatible API in Qwen Code (60s Setup!)

Multi-Agent Workflows with OpenAI Agents SDK

Build advanced multi-agent systems by integrating Novita AI with the OpenAI Agents SDK:

• Plug-and-play: Use Novita AI’s LLMs in any OpenAI Agents workflow.
• Supports handoffs, routing, and tool use: Design agents that can delegate, triage, or run functions, all powered by Novita AI’s models.
• Python integration: Simply set the SDK endpoint to https://api.novita.ai/v3/openai and use your API key.

Connect API on Third-Party Platforms

OpenAI-Compatible API: Enjoy hassle-free migration and integration with tools such as Cline and Cursor, designed for the OpenAI API standard.

Hugging Face: Use Modeis in Spaces, pipelines, or with the Transformers library via Novita AI endpoints.

Agent & Orchestration Frameworks: Easily connect Novita AI with partner platforms like Continue, AnythingLLM,LangChain, Dify and Langflow through official connectors and step-by-step integration guides.

Qwen3-VL-235B-A22B demonstrates clear strengths in advanced reasoning, visual coding, multilingual OCR, and long-context processing—making it a top choice for demanding workflows and multimodal tasks.

GLM 4.5V, while slightly behind in raw performance, is more lightweight and offers a desktop assistant, faster inference speed, and broader plug-and-play usability—especially for developers and startups.For most use cases, Qwen3-VL-235B-A22B is ideal for depth and complexity, while GLM 4.5V excels in ease of use and flexibility.

Frequently Asked Questions

Novita AI is an AI cloud platform that offers developers an easy way to deploy AI models using our simple API, while also providing an affordable and reliable GPU cloud for building and scaling.

Recommend Reading

• How to Access Qwen3-Next-80B-A3B in Trae with Extended Context Support
• Comparing Kimi K2-0905 API Providers: Why NovitaAI Stands Out
• How to Use GLM-4.6 in Cursor to Boost Productivity for Small Teams