Model Size Explorer
AI models come in different sizes measured by their parameters. More parameters generally mean more capability, but also more compute and memory requirements.
Size Comparison
Click on any bar to see details. Bar widths use logarithmic scale for visibility.
Example Models
Typical Use Cases
- •Quick chatbots and assistants
- •Text summarization
- •Simple code completion
- •Personal devices / edge deployment
Specifications
Agentic Potential with Tools
Small models become dramatically more capable when equipped with tools. A 7B model with tools can accomplish tasks that a 405B model without tools cannot.
Used in: Cursor, Windsurf, Claude Code, and other AI-powered dev tools
Example Models
Typical Use Cases
- •Production-grade assistants
- •Complex code generation
- •Document analysis
- •Multi-turn conversations
Specifications
Example Models
Typical Use Cases
- •State-of-the-art reasoning
- •Complex multi-step problems
- •Research and analysis
- •Enterprise applications
Specifications
At a Glance
Capability Comparison
How different model sizes perform across various tasks.
| Capability | 7B | 70B | 405B |
|---|---|---|---|
Basic Q&A Simple questions and answers | ✓ | ✓✓ | ✓✓ |
Code Generation Writing and debugging code | ~ | ✓✓ | ✓✓ |
Complex Reasoning Multi-step logical analysis | ~ | ✓ | ✓✓ |
Multi-step Math Advanced mathematical problems | ✗ | ✓ | ✓✓ |
Creative Writing Stories, essays, poetry | ✓ | ✓✓ | ✓✓ |
Tool Augmentation
The secret to unlocking small model potential
How Tools Work
Tools are functions with descriptions that nudge the model's latent space. They provide structured ways for models to interact with the outside world, compensating for knowledge and capability gaps.
The 5 Agent Primitives
These 5 primitives enable coding agents to accomplish complex software engineering tasks
Key Insights
- A 7B model with tools can accomplish tasks a 405B model without tools cannot
- Mini-SWE-agent (small model) scored 68% on SWE-bench
- It's just "300 lines of code running in a loop with LLM tokens"
"Less is more" - Context optimization matters more than raw model size. The model does the heavy lifting; tools just give it leverage.
Learn How Agents Work
Discover the agent loop, the five primitives, and what makes models agentic.
Understanding Model Sizes
Parameters are the learned values in a neural network. More parameters allow the model to capture more complex patterns and nuances in language.
VRAM (Video RAM) is GPU memory. Larger models need more VRAM to run. The values shown are approximate for running at 16-bit precision.
Speed vs Capability: Smaller models respond faster but may produce lower quality outputs. The right size depends on your use case and hardware.