well that explains quite a bit
Memory comparison of AI coding CLIs (single session, idle):
| Tool | Footprint | Peak | Language |
|-------------|-----------|--------|---------------|
| Codex | 15 MB | 15 MB | Rust |
| OpenCode | 130 MB | 130 MB | Go |
| Claude Code | 360 MB | 746 MB | Node.js/React |
vmmap shows Claude Code reserves 32.8 GB virtual memory just for the V8 heap, has 45% malloc fragmentation, and a peak footprint of 746 MB that never gets released, classic leak pattern.
On my 16 GB Mac, a "normal" workload (2 Claude sessions + browser + terminal) pushes me into 9.5 GB swap within hours. My laptop genuinely runs slower with Claude Code than when I'm running local LLMs.
I get that shipping fast matters, but building a CLI with React and a full Node.js runtime is an architectural choice with consequences. Codex proves this can be done in 15 MB. Every Claude Code session costs me 360+ MB, and with MCP servers spawning per session, it multiplies fast.
Codex (by openai ironically) seems to be the fastest/most-responsive, opens instantly and is written in rust but doesn't contain that many features
Claude opens in around 3-4 seconds
Opencode opens in 2 seconds
Gemini-cli is an abomination which opens in around 16 second for me right now, and in 8 seconds on a fresh install
Codex takes 50ms for reference...
--
If their models are so good, why are they not rewriting their own react in cli bs to c++ or rust for 100x performance improvement (not kidding, it really is that much)
React itself is a frontend-agnostic library. People primarily use it for writing websites but web support is actually a layer on top of base react and can be swapped out for whatever.
So they’re really just using react as a way to organize their terminal UI into components. For the same reason it’s handy to organize web ui into components.
Who cares, and why?
All of the major providers' CLI harnesses use Ink: https://github.com/vadimdemedes/ink
To me, their claim that they are vibe coding Claude code isn’t the flex they think it is.
I find it harder and harder to trust anthropic for business related use and not just hobby tinkering. Between buggy releases, opaque and often seemingly glitches rate limits and usage limits, and the model quality inconsistency, it’s just not something I’d want to bet a business on.
i wonder how many are real and not duplicates. i doubt github is well setup to handle said volume
they're also total garbage