Thinking Machines Lab's smaller, more efficient open-weight multimodal model, with 12B active parameters out of 276B total.
Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents.
No shared demos for these models yet.
No captured outputs for these models yet.
Both Inkling Small and Gemini 4 Argon are capable AI models. The best choice depends on your specific use case: consider pricing, context window, speed, and which capabilities (vision, reasoning, audio) you need.
Inkling Small has a lower blended cost. Inkling Small: $0.45 input / $1.20 output. Gemini 4 Argon: $2.00 input / $10.00 output.
Gemini 4 Argon has a larger context window: Inkling Small supports 524K tokens vs Gemini 4 Argon at 1M tokens.
Yes, both Inkling Small and Gemini 4 Argon support vision/image input.
Key differences: Inkling Small is significantly cheaper. Compare full specs on this page.
If cost is your priority, choose the cheaper option. If you need the highest intelligence for complex tasks, pick the higher-scoring model. For long documents or codebases, choose the larger context window. You can try both Inkling Small and Gemini 4 Argon for free on idapt.app to see which performs better for your specific needs.