> For the complete documentation index, see [llms.txt](https://docs.algenta.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.algenta.ai/benchmarks/code-retrieval.md).

# Code retrieval quality

Code retrieval quality on CoIR, measured with nDCG\@10 against BM25 baselines evaluated on the same harness.

The retrieval engine indexes code, so quality is measured on CoIR, a code-specific information-retrieval benchmark. All systems on this page are evaluated by `mteb.evaluate` through the `mteb` `SearchProtocol` interface, on the same data and the same scoring path.

**Metric:** nDCG\@10. Higher is better.

## Results

| CoIR task             | multigram | bm25-ref | bm25-code | code-lexical | Ratio vs best baseline |
| --------------------- | --------- | -------- | --------- | ------------ | ---------------------- |
| CodeTransOceanContest | 0.160     | 0.478    | 0.600     | 0.718        | 1.197                  |
| SyntheticText2SQL     | 0.265     | 0.249    | 0.372     | 0.441        | 1.185                  |
| CodeFeedbackMT        | 0.288     | 0.592    | 0.591     | 0.674        | 1.139                  |
| CodeFeedbackST        | 0.162     | 0.682    | 0.682     | 0.722        | 1.059                  |
| CodeTransOceanDL      | 0.340     | 0.344    | 0.351     | 0.366        | 1.043                  |
| StackOverflowQA       | 0.223     | 0.703    | 0.687     | 0.733        | 1.043                  |
| CosQA                 | 0.048     | 0.188    | 0.213     | 0.218        | 1.023                  |
| Average               | 0.212     |          |           | 0.553        | 1.102                  |

The ratio column compares against the higher of `bm25-ref` and `bm25-code` on each task. Average nDCG\@10 is 0.553, versus 0.502 for the per-task best baseline. Rows are ordered by ratio, descending.

## Method

* All systems are scored by `mteb.evaluate` through the same `SearchProtocol` interface.
* Baseline figures are runs executed on 2026-07-21 on this harness.

## Scope

* `AppsRetrieval`, CoIR's eighth task, pairs long natural-language problem statements with code. Lexical methods score near zero on it (baselines: 0.001, 0.048, 0.014), so it is out of scope for this lexical-retrieval comparison.
* This page measures retrieval quality. Latency and throughput are measured separately.
* nDCG\@10 measures ranking quality within the top ten results.

## See also

* [Benchmarks](/benchmarks/overview.md)
* [Compute kernels](/benchmarks/compute-kernels.md)
* [Runtime library catalog](/engine-runtime/runtime-library-catalog.md)


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