HN Explorer

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

217 points by bhaktatejas922 ↗ HN
Hey HN, I’m Tejas at Morph. We’ve built a blazing-fast model for applying AI-generated code edits directly into your files at 4,500+ tokens/sec. No more slow full-file rewrites or brittle search-and-replace hacks.

Here's a demo video: https://www.youtube.com/watch?v=LdT8epGHJPk.

Why? AI spits out code that can’t reliably be inserted into existing code. Full file rewrites, brittle search-and-replace hacks are too slow, expensive, or error-prone.

Morph's approach:

- Your agent outputs edits “lazily”, referencing unmodified lines in the existing file (ex: // ...existing code...)

- Morph instantly applies these edits to a file using our Fast Apply model + speculative decoding against the original file, making AI patches fast, reliable, and production-ready.

This approach was pioneered by Cursor last year, but their models aren’t available as APIs—so we built Morph for developers everywhere (with a large free tier!)

Live demo (no signup): https://morphllm.com/dashboard and docs: https://docs.morphllm.com/quickstart

We have 2 Fast Apply models: morph-v3-fast - 4500+ tok/sec, and morph-v3-large - 2500+ tok/sec. These models power Fast Apply at create.xyz, databutton, continue.dev, and more!

We also provide retrieval models for embedding + reranking. Next Up: Inline Edit Model (Cmd-K): Extremely fast inline edits - keep dev flow state; and Morph Tab API: Our Next Edit Prediction model guesses your next code edit + action with sub-500ms latency. It's currently in private beta, but you can request early access here: https://morphllm.com/tab

Hot takes:

1) Raw inference speed matters more than incremental accuracy gains for dev UX—agree or disagree?

2) Full-file rewrites by frontier models are legacy—Fast Apply edits win on speed, cost, reliability.

3) As benchmarks on narrow tasks saturate to 99%+, complexity is shifting from single frontier models to specialized inference-optimized models. As frontier models move upmarket, they'll leave simple tasks behind, and they'll be used to do tasks only frontier models can do

We’d love to hear your ideas and experiences with coding agents!

53 comments

[ 5.7 ms ] story [ 53.5 ms ] thread
deepdarkforest
> 1) Raw inference speed matters more than incremental accuracy gains for dev UX—agree or disagree?

I know you are trying to generate some controversy/visibility, but i think if we are being transparent here, you know this is wrong. People prefer using larger (or reasoning) models, with much bigger diff in tok/sec just for quality in coding, it comes first. Even if i have a big edit to apply, like 5k tokens, 200-300ms of difference in edit time are nothing. Edit speed is definitely not a bottleneck for dev UX, quality is. A dev who wants to save 200ms every code change over quality is someone who well, i cannot relate. If im using 1-2 agents in parallel, most of the time the edits are already applied while im reviewing code from the other agents. But again maybe that's just me.

Speaking of quality, how do you measure it? Do you have any benchmarks? How big is the difference in error rate between the fast and large model?

rs186
Sounds interesting, but I imagine all the big players (Cursor, Windsurf, and maybe even OpenAI/Anthropic) will achieve something similar very quickly in their tools first-party, which will decimate the company. And I don't get the API part of this -- at the end of the day people use those IDEs, and I don't see developers/companies want to send their code to yet another endpoint.
Qerbz
Heard some insane rumors of the efficacy increase of this in action even though I don't know how you do it
simonw
This uses an OpenAI-compatible endpoint, so got this working with my https://llm.datasette.io/ CLI tool.

First I added their models to my ~/Library/Application Support/io.datasette.llm/extra-openai-models.yaml file:

  - model_id: morph-auto
    model_name: auto
    api_base: https://api.morphllm.com/v1
    api_key_name: morph
Then I added the API key like this:

  llm keys set morph
  # Paste in API key from https://morphllm.com/api-keys
Then I saved an LLM template with their prompting pattern:

  llm -m morph-auto '<code>$code</code><update>$update</update>' --save morph
Now I can run operations like this:

  llm -t morph -p code "$(cat orig.txt)" -p update "$(cat update.txt)"
The -t option is the template I named when I ran --save. The -p name value options then set the content for the template $code and $update variables.

Example transcript here: https://gist.github.com/simonw/de67818603d448a3fee788ace2976...

One thing that worries me: since it's using XML-style tags <code> and <update>, if my own source code contains those tags I expect it may get confused.

seanw265
Last time I looked into Morph, I noticed you weren’t yet on OpenRouter. I see that’s changed, but it looks like only an older model is listed. Any plans to be more active there?

Also, are there any benchmarks comparing your fast apply models to others like Relace or even Llama via Cerebras? I’m particularly interested in output accuracy.

bijection
How does this compare to relace, which I believe is also a YC company? They seem to have very similar functionality [0]

[0] https://www.relace.ai/

Workaccount2
Just for clarification here because I am a bit confused,

Morph is a tool for integrating the output of other LLMs and not an LLM itself? It doesn't generate 4500 tok/sec, it can edit 4500 tok/sec?

eabeezxjc
why not ruby?

because ruby no need corecting. It works.

nico
Would be awesome to have a browser extension that could create a bridge between ChatGPT and VSCode, applying Morph in between (or Claude instead of ChatGPT). Essentially use the web interface, instead of the APIs for agentic coding
elzbardico
1) Raw inference speed matters more than incremental accuracy gains for dev UX—agree or disagree?

Yeah, I love reviewing and debugging thousands of lines of buggy and dirty AI generated code. Who cannot love it?

laborcontract
Really like this. I've been trying microsoft's copilot and it's so clunky, particularly when applying edits. One would assume they have the resources to train the model..

Request: please provide a system prompt in the docs to help the llm generate the diff format that performs best w/ your models. LLMs frequently change the way they present diffs on upgrades and I don't want to be guessing which format is best.

EDIT: Please clarify your privacy policy. If my interpretation is correct, paying users will have their data retained and trained on? Is there any way to pay to use the service (w/o picking up the phone) and not have my data trained on?

  4.1 Use of Service Data

  Depending on your subscription tier:

  Free Tier: We may use your submitted code data to train our models, improve our Services, and develop new features.
  Engineer Tier: We may use your submitted code data to train our models, improve our Services, and develop new features, subject to the confidentiality provisions in your service agreement.
  Enterprise Tier: We do not use your submitted code data for any purpose other than processing your immediate request. Your code data is never used for model training or service improvement.
[0] https://morphllm.com/privacy
lastdong
Is this similar to Gemini Diffusion? Thanks
[deleted]
(comment deleted)
scottpersinger
I’d just like to put a pitch in here for someone to do “smart rebase+merge” with AI. Now THAT would really speed up development, if my AI was intelligently merging code from different users in the background, based on understanding the intent behind each conflicting change.
FridgeSeal
> Raw inference speed matters more than incremental accuracy gains for dev UX

Now I can be wrong, faster!

z3ugma
How do I start using this on a codebase on my local computer? I'm quite confused by the quickstart. Do I use a VSCode extension? One of the Claude Code like clones but with this as a custom model?
michaelneale
Have been using morph for a while (I am one of the authors of goose) and was surprised when introduced at the boost it gave me (much less iteration with the main expensive LLM, and I can even make the editing process simpler to take a load off the agent). Used it with claude 3.5, 3.7, 4 and currently with a o3/openai and anthropic/claude4 + morphllm combo today.
orge
It would be great to have an integration with Aider or OpenCode.