Public benchmark
Code-retrieval quality and cost
Profile sota-challenge: 600 held-out queries across 6 public CoIR tasks, repeated 3 times. No private corpus or local path is included.
600held-out queries
6public tasks
3languages
3repetitions
2048query char limit
Aggregate results
| Mode | nDCG@10 | MRR@10 | P@5 | R@20 | Warm p95 | Index size |
|---|---|---|---|---|---|---|
hash | 0.5900 | 0.5582 | 0.1287 | 0.7000 | 688.94 ms | 45.43 MiB |
hybrid | 0.5896 | 0.5578 | 0.1287 | 0.7000 | 722.46 ms | 45.45 MiB |
blended | 0.5955 | 0.5652 | 0.1300 | 0.7000 | 778.19 ms | 65.54 MiB |
neural | 0.5963 | 0.5661 | 0.1303 | 0.7000 | 798.38 ms | 65.55 MiB |
Population variance, phase timings, peak RSS, binary identity, dataset revisions, and checksums are retained in the raw JSON.
Per-task quality
| Task | Mode | nDCG@10 | MRR@10 | R@20 |
|---|---|---|---|---|
stackoverflow-qa | hash | 0.5829 | 0.5231 | 0.7700 |
stackoverflow-qa | hybrid | 0.5810 | 0.5206 | 0.7700 |
stackoverflow-qa | blended | 0.5988 | 0.5458 | 0.7700 |
stackoverflow-qa | neural | 0.5988 | 0.5458 | 0.7700 |
apps | hash | 0.0033 | 0.0014 | 0.0200 |
apps | hybrid | 0.0033 | 0.0014 | 0.0200 |
apps | blended | 0.0033 | 0.0014 | 0.0200 |
apps | neural | 0.0033 | 0.0014 | 0.0200 |
codefeedback-mt | hash | 0.5657 | 0.5112 | 0.7600 |
codefeedback-mt | hybrid | 0.5657 | 0.5112 | 0.7600 |
codefeedback-mt | blended | 0.5788 | 0.5243 | 0.7600 |
codefeedback-mt | neural | 0.5788 | 0.5243 | 0.7600 |
synthetic-text2sql | hash | 0.8662 | 0.8366 | 0.9800 |
synthetic-text2sql | hybrid | 0.8662 | 0.8366 | 0.9800 |
synthetic-text2sql | blended | 0.8658 | 0.8330 | 0.9800 |
synthetic-text2sql | neural | 0.8683 | 0.8363 | 0.9800 |
CodeSearchNet-python | hash | 0.9400 | 0.9400 | 0.9400 |
CodeSearchNet-python | hybrid | 0.9400 | 0.9400 | 0.9400 |
CodeSearchNet-python | blended | 0.9400 | 0.9400 | 0.9400 |
CodeSearchNet-python | neural | 0.9400 | 0.9400 | 0.9400 |
CodeSearchNet-java | hash | 0.5816 | 0.5370 | 0.7300 |
CodeSearchNet-java | hybrid | 0.5816 | 0.5370 | 0.7300 |
CodeSearchNet-java | blended | 0.5865 | 0.5465 | 0.7300 |
CodeSearchNet-java | neural | 0.5885 | 0.5488 | 0.7300 |
Every retained task remains visible so aggregate improvements cannot hide regressions.
Scope
Matrix covers held-out natural-language and code-to-code retrieval. Exact-search tools require a separate exact-query workload.