Launch HN: Morph (YC S23) – Apply AI code edits at 4,500 tokens/sec

What Morph Is (and Isn’t)

  • Clarified multiple times: Morph is an LLM, but its role is to apply edits, not to design them.
  • Typical workflow: a “big” model (Claude, Gemini, o3, etc.) proposes changes; Morph’s “small” model merges them into the original file.
  • Positioned as a more accurate, faster alternative to full-file rewrites or brittle search-and-replace / patch approaches.

Patch/Diff vs Model-Based Apply

  • Some ask why not just have the main LLM output a patch.
  • Reported issues with patches: search mismatches, missing context (e.g., commas, scattered edits), and failure on “make this page nicer”–style large edits.
  • Proponents argue smart diffing is “edge case hell”; LLMs are better at handling semantic, fuzzy, human-like edit instructions.
  • Skeptics suggest redefining the problem to avoid making a mess with one LLM and then cleaning it with another.

Speed vs Accuracy & Developer Flow

  • Intense debate around the claim that raw speed matters more than incremental accuracy for dev UX.
  • One camp: accuracy is the main bottleneck; 200–300 ms savings are irrelevant compared to debugging wrong code.
  • Other camp: once accuracy is high enough, latency strongly affects “flow state”; faster tools (like Cursor with fast apply) feel dramatically better.
  • Team says accuracy “comes first”, fast vs large model differs by ~2% error rate, with auto-routing for harder cases.
  • Several ask for public, reproducible benchmarks; current docs are seen as unclear.

Integrations & Ecosystem

  • Strong demand for: Claude Code integration (via hooks or MCP), Aider/OpenCode, Kilo Code, Zed, VS Code, Obsidian, browser bridges.
  • An MCP server and OpenAI-compatible API are already available; Morph is on OpenRouter (with some model/version confusion).
  • Some see this as an infra feature that IDEs/agents should embed rather than an end-user product.

Reliability, Privacy, and Trust

  • One HTML demo behaved unexpectedly (adding CSS/sections). This was first attributed to a hardcoded snippet, then to “semantic” correction; a critic called this broken behavior and misleading.
  • Another user reports difficulty getting the platform to work at all.
  • Privacy policy draws concern: free/engineer tiers allow training on user code; enterprise tier and OpenRouter use promise zero data retention, with ZDR opt-in available by email.

Competition & Alternatives

  • Comparisons to Relace, Osmosis-Apply, conventional search/replace, Google Gemini Diffusion, Apple DiffuCoder, and Gemini Flash pricing.
  • Some predict big IDEs and model vendors will subsume this functionality; others argue focus and specialization can still justify a dedicated company.