Model Strategy: Picking the Right Brain for the Job

Since many great models are free to use via web interfaces (like Gemini in AI Studio, Grok, Deepseek), I prioritize these. Poe.com also gives free daily credits for top models like Claude and the new o4 series.

Gemini 2.5 Pro (via AI Studio) is great for debugging, great for planning, and also finding it the best at lots of things now. For really thorny issues, I might try the new o4-mini (available via OpenRouter or Poe). It surprisingly fixed a persistent bug for me right away, though I'm still figuring out its best use cases. It's notably cheaper via API than the previous top dogs like Claude 3.5/3.7/4.

I usually try Claude 3.7 or 4 at some point, via Poe or API (OpenRouter makes this easy), or github Copilot chat (you can get some free usage from that if you don't pay) but it's pricier for frequent use. Think of Claude 3.7 and 4 as Claude on Adderall – brilliant, sometimes verbose, maybe a bit 'psychotic' like Hunter S. Thompson. Lots of great output, but you might need a calmer model like Claude 3.5 to refine it or do the actual coding.

Gemini 2.5 Pro (via AI Studio) is great for debugging, great for planning, and also finding it the best at lots of things now. The new Gemini 2.5 Pro model shows even better performance across coding tasks. For really thorny issues, I might try the new o4-mini (available via OpenRouter or Poe). It surprisingly fixed a persistent bug for me right away, though I'm still figuring out its best use cases. It's notably cheaper via API than the previous top dogs like Claude 3.5/3.7.

For really hard problems, try using OpenAI's o3 or GLM 4.5, Qwen3 Coder 480b. You can get lots of free daily tokens if you set your account to allow sharing of your data to help train models. Go to the Open AI Playground page, click the settings icon in the upper right, then click Data Controls on the left sidebar, then Sharing on the displayed page, there you can change the "Share inputs and outputs with OpenAI" setting to Enabled, which will give you:

• Up to 250 thousand tokens per day across gpt-5, gpt-4.1, gpt-4o, o1 and o3
• Up to 2.5 million tokens per day across gpt-4.1-mini, gpt-4.1-nano, gpt-4o-mini, o1-mini, o3-mini, o4-mini, and codex-mini-latest

This is really awesome, o3 and GPT 4.5 seem super genius! Sometimes in the OpenAI Playground, I have it set up to use o3 and o4-mini side-by-side, to compare them. This helps me get a feel for which ones are best for which types of problems.

Claude 4 and 3.7 is always a good option to try and fix hard problems quickly, it is just harder to access it for cheap or free. But it is often the best out of them all. When you really need to fix something fast, use it. Poe has free tokens for all models, daily. OpenRouter has all models paid and/or free. Claude 3.7 is Claude on caffeine – brilliant, sometimes verbose, maybe a bit 'psychotic' like Hunter S. Thompson. Lots of great output, but you might need a calmer model like Claude 3.5 / 4 to refine it or do the actual coding.

The Hybrid Approach: Premium Planning + Budget Execution

After extensive testing with various models, I've developed a hybrid strategy that maximizes both quality and cost-effectiveness. The key insight is that different models excel at different parts of the development process.

My "smart juice" theory of model intelligence - How Models become stupid under certain circumstances

AI models are usually smarter the less text you send to them. Think of each model as having a fixed amount of "intelligence" or "smart juice" available for every question or problem you ask. When you send a simple, focused prompt, nearly 100% of that intelligence is available to solve your problem. But the more complex your input—long agentic instructions about how to use tools, lots of context unrelated to your specific problem, or multiple pages of code—the more of that "smart juice" gets used up just processing the unrelated stuff like how it can use tools in your IDE, leaving less intelligence energy available for your actual problem.

This is why tools like Cursor, Cline, and other agentic systems can sometimes seem less effective: if they send five giant pages of instructions and context before even getting to your real question, the model's available intelligence for your specific problem drops. The more "stuff" you send, the more diluted the model's focus becomes. For best results, keep your prompts as concise and targeted as possible—curate the context so the model can use its full intelligence on what matters most.

When you have a hard problem or bug, you will usually save time by using AI Code Prep to dump it into a web chat (as discussed on page 1 of this guide). It cuts out all the extra instructions and stuff that get sent in agentic IDEs/apps. I noticed that this works better even if you give the AI ALL of the files from your project. The agentic instructions/stuff/bloat that is unrelated to your actual problem is the content that seems to make the AI dumber/run out of juice.

My Workflow is something like this when starting a new project:

1. Plan & Brainstorm: Use the smarter/free web models (Gemini 2.5, o4-mini, Claude 3.7, 4, o3, etc) to figure out the approach, plan the steps, identify libraries, etc.
2. Generate Agent Prompt: Ask one of these smart models: "Write a detailed-enough prompt for Cline, my AI coding agent, to complete the following tasks: [describe tasks]". Sometimes, I'll copy this generated prompt and paste it into another free AI good at rewriting (like ChatGPT) to refine it further.
3. Execute with Cline: Paste the step-by-step task list into Cline, configured to use a stable and efficient model like GPT 4.1 or Claude 3.5 (or Claude 4 if it is doing really complicated things). The 4.1's have been trained to follow instructions well.
4. Fallback: If GPT 4.1 struggles, switch Cline to use Claude 3.5 via API. It seems to be the next best for reliable execution. Deepseek v3 or R1 is really great at following instructions as well.

Essentially: Use expensive/smart models (and the excellent free Gemini 2.5 Pro) to strategize and plan. Validate the plan by pasting it into 2-3 other free models (Deepseek R1, Claude on Poe if context allows) and ask "Is this good? Can you improve it or find flaws?". Then, use a stable workhorse like GPT 4.1 or Claude 3.5 within Cline to do the heavy lifting (coding).

o4-mini seems particularly adept at untangling complex code logic or figuring out high-level implementation strategies (like choosing frameworks or libraries). I'll often throw my initial idea at Gemini 2.5, o4-mini, GPT 4.1, ChatGPT, maybe o3-mini (try duck.ai - often free), and Phind to get a range of ideas. If the free/cheap options don't crack it, I'll escalate to pricier models via API.

Alternative Agents & Setups

Trae.ai (from Bytedance, makers of TikTok) is a free VS Code compatible IDE with free AI usage, including Claude 4, Claude 3.7, Claude 3.5, and GPT 4.1. Their agents aren't as good as Cline (nothing is as good, to be honest!) but it's free and gives access to the best models. Sometimes, I find its built-in agent isn't as robust as Cline. However, since Trae seems to be a VS Code clone, you can likely install the Cline extension within it! However... it is too overloaded to get any free usage from it, its too slow. I'll still mention it though.. but meh.

So, you could have two setups:

• VS Code + Cline extension + Copilot extension (get the $10/mo subscription for cheap API access via Cline, though the free tier might offer some basic use).
• Trae.ai + Cline extension (potentially leveraging Trae's free model access if Cline can use it, or using your own API keys).

Try both! Sometimes the native Copilot agent solves things Cline struggles with, and vice-versa. I suspect Cline sometimes sends overly large prompts which might hinder performance on certain tasks compared to the more integrated Copilot agent.

Roo Code: Cline's Clone

Cline for VS Code is free, but remember you pay for the API calls unless you're leveraging the Copilot subscription trick. Using the VS Code LM API setting in Cline with a $10/month Copilot sub is currently the most cost-effective way to get near-unlimited access to powerful models within the agent.