My current stack, favorite models, and the tools I actually use every day. Updated as things change, which is constantly.
Last updated: March 2026
01My daily driver. Best at long-running agentic coding tasks. Slower and more deliberate. Thinks before it acts, takes time to understand the codebase. Doesn't default to action like Opus. The model you want for complex backend work.
Best for complex, multi-step coding tasks
Deliberate, thinks before acting
Strong at understanding large codebases
Slower than Opus
UI output not as polished
02Easily the best at UI and front-end work. Nicest to talk to: natural, fluid, pleasant. 1M token context window. Fast, prone to action. Very expensive on API, incredible value on a subscription.
Best at UI and frontend code
1M token context window
Natural, fluid conversation style
Fast and action-oriented
Very expensive on API
Can be too eager to act before thinking
032M token context window, the biggest available. Fast. Built-in access to X/Twitter data, making it the best for real-time research, trends, and social intelligence.
2M token context, largest available
Built-in X/Twitter data access
Fast inference
Less polished for coding tasks
X integration only useful for certain workflows
04The multimodal leader. Best for video, images, and massive documents. Useful when you need to process visual content or very large files.
Best multimodal capabilities (video, image, audio)
Excellent at structured output from messy input
Huge context window
Unreliable at tool calling in agent loops
Less predictable in complex harnesses
0590% of Opus intelligence at a fraction of the cost. Open source. The sleeper pick if you need near-frontier reasoning without frontier pricing.
Near-frontier intelligence, fraction of the cost
Open source
Great value for high-volume workloads
Not quite frontier on the hardest tasks
Smaller ecosystem and tooling