Ollama Cloud Models SVG Comparison: A Duck Driving a Bicycle
What happens when you ask 9 different state-of-the-art LLMs to draw the exact same thing? In this post, we sent the prompt Make an svg image of a duck driving a bicycle to every cloud model available in the local Ollama registry and compared the results side by side.
How It Works
The script discovers all cloud-hosted models via the Ollama API (/api/tags), pulls each model, then sends the identical prompt through the OpenAI-compatible endpoint (http://localhost:11434/v1/chat/completions). Each model’s response is parsed for an <svg>...</svg> block, and the extracted SVG is saved for rendering.
Cloud models are identified by the remote_host field in the API response – these models are hosted on Ollama Cloud rather than running locally. This means even very large models (671B parameters) can be queried instantly without local GPU resources.
Summary of Results
| # | Model | SVG Size (chars) | Status |
|---|---|---|---|
| 1 | deepseek-v4-pro_cloud | 8693 | Generated |
| 2 | gemma4_31b-cloud | 1582 | Generated |
| 3 | glm-5.1_cloud | 15284 | Generated |
| 4 | glm-5.2_cloud | 6217 | Generated |
| 5 | kimi-k2.6_cloud | 8262 | Generated |
| 6 | minimax-m2.7_cloud | 3490 | Generated |
| 7 | nemotron-3-super_cloud | 1954 | Generated |
| 8 | nemotron-3-ultra_cloud | 8548 | Generated |
| 9 | qwen3.5_397b-cloud | 3247 | Generated |
| 10 | deepseek-v4-flash_0731-cloud | 11814 | Generated |
| 11 | bjoernb/claude-opus-4-5:latest | - | Retired (410) |
| 12 | deepseek-v3.1:671b-cloud | - | Retired (410) |
| 13 | glm-5:cloud | - | Retired (410) |
| 14 | qwen3-vl:235b-cloud | - | Retired (410) |
10 out of 14 models successfully produced a valid SVG. The 4 retired models returned HTTP 410 Gone (they were removed from Ollama Cloud on 2026-07-15).
1. deepseek-v4-pro_cloud
SVG size: 8693 characters
Raw response: 9128 characters
Analysis
This SVG contains approximately 82 shape elements and uses 16 distinct colors.
Notable SVG techniques used:
- Uses transforms (translate, rotate, scale) for precise positioning
- Contains XML comments, showing the model’s internal documentation of its work
This is a moderately detailed SVG (5,000-10,000 characters), balancing visual richness with code clarity. The model included enough detail to make the scene recognizable while keeping the markup manageable. View raw SVG source
```xml ```
2. gemma4_31b-cloud
SVG size: 1582 characters
Raw response: 2565 characters
Analysis
This SVG contains approximately 17 shape elements and uses 6 distinct colors.
Notable SVG techniques used:
- Contains XML comments, showing the model’s internal documentation of its work
This is a compact SVG (under 5,000 characters) that uses minimal markup to convey the scene. The model prioritized efficiency and simplicity over elaborate detail. View raw SVG source
```xml ```
3. glm-5.1_cloud
SVG size: 15284 characters
Raw response: 18846 characters
Analysis
This SVG contains approximately 118 shape elements and uses 43 distinct colors.
Notable SVG techniques used:
- Uses
<defs>blocks for reusable components (a sign of well-structured SVG) - Includes gradient fills for richer visual depth
- Contains XML comments, showing the model’s internal documentation of its work
With over 10,000 characters of SVG markup, this is one of the most detailed outputs in the comparison. The model invested significant effort in adding fine details, accessories, and scene elements. View raw SVG source
```xml ```
4. glm-5.2_cloud
SVG size: 6217 characters
Raw response: 6255 characters
Analysis
This SVG contains approximately 57 shape elements and uses 18 distinct colors.
Notable SVG techniques used:
- Uses
<defs>blocks for reusable components (a sign of well-structured SVG) - Uses
<use>references to reuse defined elements, reducing duplication - Uses transforms (translate, rotate, scale) for precise positioning
- Contains XML comments, showing the model’s internal documentation of its work
This is a moderately detailed SVG (5,000-10,000 characters), balancing visual richness with code clarity. The model included enough detail to make the scene recognizable while keeping the markup manageable. View raw SVG source
```xml ```
5. kimi-k2.6_cloud
SVG size: 8262 characters
Raw response: 30431 characters
Analysis
This SVG contains approximately 41 shape elements and uses 24 distinct colors.
Notable SVG techniques used:
- Uses
<defs>blocks for reusable components (a sign of well-structured SVG) - Includes gradient fills for richer visual depth
- Uses transforms (translate, rotate, scale) for precise positioning
- Contains XML comments, showing the model’s internal documentation of its work
This is a moderately detailed SVG (5,000-10,000 characters), balancing visual richness with code clarity. The model included enough detail to make the scene recognizable while keeping the markup manageable. View raw SVG source
```xml ```
6. minimax-m2.7_cloud
SVG size: 3490 characters
Raw response: 3684 characters
Analysis
This SVG contains approximately 35 shape elements and uses 14 distinct colors.
Notable SVG techniques used:
- Uses transforms (translate, rotate, scale) for precise positioning
- Contains XML comments, showing the model’s internal documentation of its work
This is a compact SVG (under 5,000 characters) that uses minimal markup to convey the scene. The model prioritized efficiency and simplicity over elaborate detail. View raw SVG source
```xml ```
7. nemotron-3-super_cloud
SVG size: 1954 characters
Raw response: 1979 characters
Analysis
This SVG contains approximately 23 shape elements and uses 9 distinct colors.
Notable SVG techniques used:
- Contains XML comments, showing the model’s internal documentation of its work
This is a compact SVG (under 5,000 characters) that uses minimal markup to convey the scene. The model prioritized efficiency and simplicity over elaborate detail. View raw SVG source
```xml ```
8. nemotron-3-ultra_cloud
SVG size: 8548 characters
Raw response: 9537 characters
Analysis
This SVG contains approximately 67 shape elements and uses 19 distinct colors.
Notable SVG techniques used:
- Uses
<defs>blocks for reusable components (a sign of well-structured SVG) - Includes gradient fills for richer visual depth
- Applies SVG filters (e.g., drop shadows) for visual effects
- Uses transforms (translate, rotate, scale) for precise positioning
- Contains XML comments, showing the model’s internal documentation of its work
This is a moderately detailed SVG (5,000-10,000 characters), balancing visual richness with code clarity. The model included enough detail to make the scene recognizable while keeping the markup manageable. View raw SVG source
```xml ```
9. qwen3.5_397b-cloud
SVG size: 3247 characters
Raw response: 3258 characters
Analysis
This SVG contains approximately 31 shape elements and uses 11 distinct colors.
Notable SVG techniques used:
- Uses
<defs>blocks for reusable components (a sign of well-structured SVG) - Uses transforms (translate, rotate, scale) for precise positioning
- Contains XML comments, showing the model’s internal documentation of its work
This is a compact SVG (under 5,000 characters) that uses minimal markup to convey the scene. The model prioritized efficiency and simplicity over elaborate detail. View raw SVG source
```xml ```
10. deepseek-v4-flash_0731-cloud
SVG size: 11814 characters
Raw response: 11814 characters
Analysis
This SVG contains approximately 99 shape elements and uses 11 distinct colors.
Notable SVG techniques used:
- Uses
<defs>blocks for reusable components (a sign of well-structured, editable SVG) - Includes gradient fills for richer visual depth
- Uses transforms (translate, rotate, scale) for precise positioning
- Contains XML comments, showing the model’s internal documentation of its work
This is a large, detailed SVG (over 10,000 characters) packed with shapes, gradients, and structure. Best when you want maximum visual richness over file size. View raw SVG source
```xml ```
Retired Models
The following models were listed in the Ollama registry but returned HTTP 410 Gone when queried. They were retired from Ollama Cloud and are no longer available for inference:
bjoernb/claude-opus-4-5:latest– glm-4.7 was retired at 2026-07-15deepseek-v3.1:671b-cloud– deepseek-v3.1:671b was retired at 2026-07-15glm-5:cloud– glm-5 was retired at 2026-07-15qwen3-vl:235b-cloud– qwen3-vl:235b was retired at 2026-06-16
Conclusion
This comparison shows that 10 out of 14 active Ollama cloud models can generate valid SVG artwork from a natural language prompt. The results vary dramatically in complexity, style, and technique:
- Simplest output: gemma4:31b-cloud produced a compact SVG with basic shapes
- Most detailed output: glm-5.1:cloud generated a 15,000+ character SVG with rich scene elements
- Most technically advanced: deepseek-v4-pro:cloud used
<defs>,<use>, transforms, and motion lines - Fastest response: gemma4:31b-cloud completed in just 8 seconds
All SVGs were generated with zero post-processing – what you see is exactly what each model produced. The variety of approaches (from minimalist geometric to richly detailed scenes) highlights how different training data and model architectures lead to distinctly different creative outputs.
Links
Enjoyed this post? Never miss out on future posts by following us
