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·2 min read

How fast is CGraph? Benchmarking our open-source code-graph engine

We benchmarked CGraph, our open-source code-intelligence engine: 12-198x faster builds than Graphify, a 15.8x faster warm query, and ~82% fewer tokens than the grep-and-read loop AI agents use today.

engineeringbenchmarksopen sourceai agentsdeveloper tools

Ascending performance bars with velocity streaks sweeping to the right, evoking speed.

At NxtSoft we build developer tools in the open, and we measure them the same way we'd expect a client to. CGraph is our native code-intelligence engine: it turns a repository into a queryable knowledge graph so AI coding agents can navigate code by its structure instead of re-reading files with grep. Recently we sat it down against two baselines — an existing Python code-graph tool called Graphify, and the grep-and-read loop agents run today. Here are the headline results.

Three headline benchmark results: builds 12 to 198 times faster (0.42 seconds versus 83 seconds), warm queries 15.8 times faster (10.6 versus 167 milliseconds), and about 82% fewer tokens (3,966 versus 22,373).

Faster where it counts

  • Builds: 12–198x faster than Graphify. A full graph of CGraph's own repository builds in 0.42 seconds — including community detection and every export — versus 83 seconds for Graphify doing strictly less work.
  • Queries: 15.8x faster. Because CGraph keeps the graph resident in a local daemon, a warm query is one in-memory round-trip: 10.6 ms, against 167 ms for a tool that reloads the graph from disk each time.
  • Tokens: ~82% fewer. Across four realistic navigation tasks, CGraph answered in 3,966 tokens and 4 calls where a typical grep-and-read agent spent 22,373 tokens across 10 calls — and it turns transitive impact analysis ("what breaks if I change this?") from a tedious manual trace into a single query.

Why it matters

For an AI agent working in a large codebase, most of the cost isn't reasoning — it's re-discovering context it already loaded. A resident code graph collapses that: structure questions cost a few hundred tokens and a single millisecond-scale call, returning file:line ready to open. Cheaper context and fewer round-trips mean agents that move faster and cost less to run.

We're deliberate about honesty here: this was a self-run benchmark on our own repository, and the full write-up publishes the methodology, the caveats (grep is still the right tool for content search), and the scripts so you can reproduce every number yourself.

Read the full technical benchmark — methodology, the complete token-cost table, and where grep still wins — on NxtSoft Labs: Benchmarking CGraph: native code graphs vs Graphify and grep.

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