Fast Apply. Get what AI suggested into files - 1600+ tok/sec Productivity • Developer Tools • Artificial Intelligence 8 128 AppSignal Real-time monitoring that helps you ship with confidence Productivity • Analytics • Developer Tools HΞNRY I've been using AppSignal for a little while now and I cannot imagine working without it. Their support is awesome, the interface is super clean and it was so easy to get it up and running.
Morph builds subagents those are intended to be used by Frontier models at Claude or Gemini as tools Our primary two models are: 1. FastApply model which is used for editing files quickly 2. WarpGrep model which is for fast context retrieval
Compact compacts long sessions 50–70% at 33,000 tokens/sec using byte-identical verbatim compression, not summarization. Achieves +0.6% improvement on SWE-Bench Pro and reduces context rot by 70% compared to full-context approaches.
Morph's specialized models and inference stack deliver production-grade reliability: 99.9% uptime SLA, SOC2 certification, and 98% edit accuracy. Binance deployed Morph org-wide without review layers; HeroUI reduced churn by fixing slow applies and mangled code output.
WarpGrep v2 searches repositories in under 6 seconds and returns the right files with 15.8% lower cost and 22% faster performance than in-context search. Ranked #1 on SWE-Bench Pro, it isolates search as a separate subagent to reduce context pollution and improve agent reasoning.
Fast Apply merges LLM-generated edits at 10,500+ tokens/sec with 98% accuracy using lazy edit snippets and semantic merging. Eliminates brittle search-and-replace, preserves code structure, and delivers sub-10ms latency for real-time IDE streaming or batched multi-file refactors.
Morph provides an OpenAI-compatible API (api.morphllm.com) with support for Anthropic and Vercel AI SDKs. Developers can access Fast Apply, WarpGrep, Compact, and general coding models (Qwen, MiniMax) through one endpoint with flexible deployment: cloud, self-hosted, or on-prem.