AI models are getting better, cheaper, faster, and often harder to compare. A single headline number rarely tells the whole story: one model may be strong at reasoning, weaker at coding UI, fast but expensive, or reliable in security tests while still drifting in grounded-answer tasks.
BLXBench is our attempt to make that comparison easier to inspect: a community-driven benchmark system with a local CLI, public fixtures, and a leaderboard that shows results by task domain, difficulty, score, pass rate, latency, and cost.
What BLXBench Measures
BLXBench evaluates models across focused test areas instead of hiding everything behind one large average:
- Speed — how quickly a model responds.
- Security — whether risky requests are handled appropriately.
- Reasoning — how consistently logical tasks are solved.
- Debugging — whether bugs are identified and fixed in useful ways.
- Refactoring — whether code improves without breaking behavior.
- Hallucination — whether answers stay grounded under tricky prompts.
- Coding UI — whether a model can generate runnable, visually checkable UI artifacts.
Every run writes inspectable reports. Results stay tied to artifacts like report.json, so the leaderboard is built from reproducible runs rather than loose claims.
Run Locally, Compare Publicly
The core is the CLI:
npm i -g @bitslix/blxbench
blxbench
You choose providers, models, categories, and scope. The benchmark then runs locally against your own API credentials. Eligible runs can be submitted back to the public leaderboard.
That distinction matters to us: BLXBench should not be a static ranking page. It should grow from real runs that developers can inspect, repeat, question, and improve.
Why Community-driven?
Benchmarks get better when more perspectives shape them. New fixtures, more providers, different model classes, and more realistic tasks all make the comparison more useful.
That is why BLXBench is built as open infrastructure: tests can evolve, local runs remain reproducible, and the public dashboard gives a fast overview without hiding the underlying detail.
Next Step
The leaderboard is live:
We are launching early on purpose. The most useful benchmarks are not written in isolation; they emerge where people run them, challenge them, improve them, and feed them new models.