claude code vs aider

by Ray Svitla

both live in your terminal. both edit your files directly. both want to be the AI pair programmer you never had. but claude code and aider are built on fundamentally different assumptions about how developers should work with AI.

I’ve used both extensively. here’s the honest breakdown.

the philosophical split

aider is model-agnostic by design. it works with claude 3.7 sonnet, deepseek, GPT-4o, local models via ollama — basically anything with an API endpoint. it treats the LLM as a replaceable component. this is a feature, not a limitation.

claude code is locked to anthropic’s models. sonnet and opus, nothing else. in exchange, you get deeper integration — the tool is tuned specifically for how claude thinks, how it handles context, how it structures edits. it’s opinionated in the way that apple products are opinionated.

the question isn’t which is better. it’s which constraint you prefer.

how they edit code

aider uses a diff-based editing system. it generates search-and-replace blocks or unified diffs, applies them to your files, and commits the changes to git automatically. every edit becomes a git commit. this is brilliant for traceability and terrible if you like to batch your commits semantically.

claude code edits files directly, more like a human would. it reads the file, makes changes, and lets you review before accepting. no automatic commits — you manage your own git workflow. the edits feel more natural, but you lose the automatic audit trail.

aider’s approach: edit → auto-commit → move on claude code’s approach: edit → review → you decide

if you’ve ever had an AI tool make 47 micro-commits in a row and then had to squash them all, you know the pain of aider’s default behavior. if you’ve ever wished claude code would just commit things so you don’t forget what changed, you know the other side.

context and repo awareness

aider has a concept of “added files” — you explicitly tell it which files to include in context. /add src/auth.ts and now it can see and edit that file. /drop src/auth.ts and it’s gone. this is manual context management, and it works well once you build the habit.

claude code reads your whole repo structure and decides what to look at. it uses tools to search, read files, run commands. you don’t manage context manually — you describe the task and it figures out what to read. this is more magical and more expensive.

the tradeoff: aider gives you precise control over token spend. claude code gives you convenience at the cost of sometimes reading files it didn’t need to.

model flexibility

aider connects to basically anything. claude, openai, deepseek, groq, local models through litellm or ollama. you can use deepseek for cheap exploration and switch to sonnet for the actual edit. you can run it entirely locally with zero API costs.

claude code runs claude. that’s it. you pick sonnet or opus (if your plan includes it), and that’s your universe.

if you care about: → running local models: aider wins, no contest → mixing cheap and expensive models: aider wins → not being locked to one vendor: aider wins → getting the best possible claude experience: claude code wins

the cost question

aider with API keys means you pay per token. a typical coding session might cost $0.50-$3.00 depending on the model and how much context you’re feeding. you can see exactly what you’re spending.

claude code on a pro plan ($20/month) gives you rate-limited access. max plan ($100/month) gives you substantially more throughput. API mode charges per token like aider, but exclusively at anthropic’s rates.

for light use, aider + deepseek is absurdly cheap. for heavy daily use, claude code’s max plan provides more predictable costs. for enterprise use, both support team configurations but claude code has tighter anthropic ecosystem integration.

what aider does better

→ model flexibility. use whatever model you want, including local ones. → git integration. automatic commits with meaningful messages. → linting integration. auto-runs linters after edits, fixes issues. → transparency. you see exactly what tokens cost, what files are in context. → open source. it’s on github, you can fork it, modify it, contribute. → image support. drop screenshots into chat for visual context.

what claude code does better

→ agentic capability. it runs commands, reads files, iterates autonomously. → tool use. bash, file editing, search — it chains them without you orchestrating. → plan mode. think through a problem before writing code. → deep reasoning. ultrathink mode for complex architecture decisions. → MCP integration. connect external tools through the model context protocol. → CLAUDE.md. project-specific instructions that shape behavior per-repo.

the real difference

aider is a coding tool that uses AI. claude code is an AI agent that writes code.

that distinction matters. aider is fantastic when you know exactly what you want changed and need a fast way to express it. “change this function to use async/await.” “add error handling to this endpoint.” “refactor this class to use composition.”

claude code shines when the task is fuzzy. “this test is failing and I don’t know why.” “set up authentication for this app.” “find all the places where we’re not handling errors properly.” it explores, hypothesizes, tries things, backs up, tries again.

which one should you use

if you’re cost-sensitive and work with multiple AI providers, use aider. if you want maximum control over your context window and git history, use aider. if you run local models, aider is your only option here.

if you want an autonomous agent that can handle multi-step tasks, use claude code. if you’re deep in the anthropic ecosystem already, claude code. if you value plan-then-execute workflows, claude code.

or use both. I do. aider for quick, targeted edits when I know exactly what I want. claude code for exploration and complex tasks where I need the agent to think.

the best tool is the one that matches how you think about the problem, not the one with the most features on a comparison chart.

→ why claude code wins in the terminal — the case for terminal-first AI → context optimization — managing tokens in any tool → reduce claude code costs — if you pick claude code, spend less

Ray Svitla stay evolving