agents benchmark
SWE Atlas - Codebase QnA Leaderboard
SWE Atlas - Codebase QnA evaluates a model's ability to answer questions about real codebases.
Updated Sep 5, 2026
Models3
Model coverage3
MetricScore
EvidenceB
SWE Atlas - Codebase QnA Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelME | Score59.40% | Percentile100.00% | Participants3 | EvidenceC | Evaluated |
| Rank02 | ModelPO | Score46.20% | Percentile50.00% | Participants3 | EvidenceC | Evaluated |
| Rank03 | ModelMI | Score37.90% | Percentile0.00% | Participants3 | EvidenceC | Evaluated |
SWE Atlas - Codebase QnA Highlights
The leading models and scores on this benchmark.
SWE Atlas - Codebase QnA Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for SWE Atlas - Codebase QnA
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
What is SWE Atlas - Codebase QnA?
What SWE Atlas - Codebase QnA measures and how its scores work.
SWE Atlas - Codebase QnA is a benchmark for evaluating models on questions about real codebases.
It measures repository-level comprehension and the ability to reason about code structure, behavior, and intent across an entire project, using the Score metric as a ratio.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- SWE Atlas - Codebase QnA
- Modality
- text
- Primary category
- agents
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- overall
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about SWE Atlas - Codebase QnA.
Which model scores highest on SWE Atlas - Codebase QnA?
Muse Spark 1.3 is currently ranked first with 59.40%.
What are the top three models on SWE Atlas - Codebase QnA?
The current leaders are Muse Spark 1.3 (59.40%), Laguna S 2.1 (46.20%), and MiniMax M3 (37.90%).
Which SWE Atlas - Codebase QnA model has the lowest official input price?
MiniMax M3 has the lowest matched official input price at $0.30 input / $1.2 output per 1M tokens.
Which models are fastest among SWE Atlas - Codebase QnA results?
The fastest matched records are Muse Spark 1.3 (8.44 tok/s via Meta Model API) and MiniMax M3 (6.61 tok/s via MiniMax).
Does the highest score result prove overall model quality?
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.