Thinking Machines Lab's open-weight multimodal model with 41B active parameters out of 975B 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 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 has a lower blended cost. Inkling: $1.00 input / $4.05 output. Gemini 4 Argon: $2.00 input / $10.00 output.
Gemini 4 Argon has a larger context window: Inkling supports 524K tokens vs Gemini 4 Argon at 1M tokens.
Yes, both Inkling and Gemini 4 Argon support vision/image input.
Inkling and Gemini 4 Argon have similar overall capabilities. The main differences lie in pricing, context window size, and provider-specific strengths. Use this comparison page to review all metrics side by side.
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 and Gemini 4 Argon for free on idapt.app to see which performs better for your specific needs.