BridgeBench — The vibe coding benchmark.
BridgeBench is BridgeMind's open-source vibe coding benchmark — it measures AI model speed, cost and code quality direct from each provider across nine suites, publishes live leaderboards at bridgebench.ai, and is recruiting community contributors for v3.
Speed, cost and code quality, measured direct from every provider — no aggregators in the middle. Now a BridgeMind open-source community project, recruiting builders for v3.
100M+ views on X · 60+ models benchmarked · Open harness, open results
- 1GPT-5.4CLI 13095.5
- 2GPT-5.4 MiniCLI 13094.8
- 3GPT-5.4 NanoCLI 13092.9
- 4GPT-4.1Security v191.8
- 5Qwen 3.5 35B-A3Bv291.7
- 6Claude Sonnet 4.5Security v190.7
- 7Qwen 3.5 122B-A10Bv290.0
- 8o3-miniSecurity v189.6
Nine benchmarks. No middlemen.
Every score comes from the provider's own API — the real model, not an aggregator in front of it.
Speed
Tokens/sec, time-to-first-token and cost, measured direct from each provider.
Algorithms
Data structures, dynamic programming and graph problems graded on hidden test cases.
Debugging
Find and fix realistic bugs in existing code without breaking anything else.
Refactoring
Restructure code with AST-backed checks that the refactor actually happened.
Security
Vulnerability detection, input sanitization, auth and crypto correctness.
UI / Creative HTML
Browser-validated interactive UI generation scored for completeness and polish.
Reasoning
Multi-step problems graded on both the answer and the evidence behind it.
Hallucination & Pushback
Factual accuracy plus the discipline to reject nonsensical premises.
Cost
Cost-per-correct-solution — the metric that actually matters when you ship.
v3: the full shipping loop.
Builders don't ask a model for isolated functions — they ask it to behave like a strong partner across the whole loop. v3 adds ten workflow-shaped tracks to the deterministic core.
Plus DGX Spark integration: cloud APIs and locally-hosted open-weight models on the same chart, with GPU, power and energy-per-token numbers.
Reproducible by design — append-only run journal, version-pinned scoring, and a provider abstraction where a new model is two files.
- Catch real bugs like a senior engineer.
- Rough idea to implementation-ready PRD.
- Ask the right questions when a task is underspecified.
- Find the right files in a real codebase.
- Close the loop without collateral damage.
- PR descriptions, migration notes, release docs.
- Wire Stripe, auth, email and storage correctly.
- Turn functional UI into product-grade UI.
- Spot the final production blockers.
- Orchestrate inspect, edit, run, observe.
Built in public. Build with us.
Design eval tasks, run models on your own hardware, or sharpen the methodology — there's a clear way in.
- Author tasks and rubrics for review, clarification, writing, launch readiness and more.
- Integrate new frontier and open-weight models — a provider is two files.
- Extend beyond DGX Spark to RTX, Apple Silicon and AMD via Ollama, vLLM and llama.cpp.
- Run the suite on your hardware and contribute results to the public leaderboard.
- Sharpen scoring, harden the harness, and document how it all works.
- Help build the web UI for rankings, filtering and model comparisons.
Frequently asked.
What is BridgeBench?
BridgeBench is BridgeMind’s vibe coding benchmark. It measures what matters when you ship with AI — speed, cost and code quality — by calling model APIs directly from each provider (bypassing aggregators) across Speed, Algorithms, Debugging, Refactoring, Security, UI, Reasoning, Hallucination and Cost benchmarks.
Is BridgeBench open source?
Yes. BridgeBench is now a BridgeMind community project with open methodology, an open harness and open results. It is built in public, and we are actively recruiting contributors for the v3 expansion.
What is the goal of BridgeBench v3?
v3’s mission is to be the world’s number-one vibe coding benchmark — expanding from code generation into the full shipping loop with new tracks for code review, spec generation, clarification, repo orientation, test repair, writing, integration, UX polish, launch readiness and multi-step tool use, plus local-vs-cloud model comparison via DGX Spark.
How can I contribute to BridgeBench?
You can design benchmark tracks, add models, run the suite on your own hardware and submit reference results, expand local inference support, or improve methodology and docs. Join the BridgeMind Discord to get started.