Benchmark profile
Artificial Analysis Coding Agent Index (AA Coding Agents)
A display-only Artificial Analysis leaderboard for coding-agent systems, combining agent harnesses, host models, and execution settings across software-engineering benchmarks.
How BenchLM shows AA Coding Agents
BenchLM mirrors the Artificial Analysis Coding Agent Index v1.1 page as a display-only agent leaderboard. The source compares coding-agent variants across DeepSWE, Terminal-Bench v2, SWE-Atlas-QnA and reports the average pass@1 index alongside cost, token, and execution-time metadata.
AA Coding Agents is separate from BenchLM model-only rankings. Its rows combine an agent harness, a host model, execution settings, and provider routing, so BenchLM treats the index as external system evidence rather than a weighted base-model benchmark. Component benchmark availability can vary by row in the source payload.
Index score on AA Coding Agents — June 2026 page snapshot
BenchLM mirrors the published index score view for AA Coding Agents. Claude Code - Opus 5 (max) leads the public snapshot at 65.5% , followed by Codex - GPT-5.6 Sol (xhigh) (65.1%) and Codex - GPT-5.6 Sol (high) (64.1%). BenchLM does not use these results to rank models overall.
Claude Code - Opus 5 (max)
Anthropic
42d261a806e9a96a4769ed568662ad9c
Codex - GPT-5.6 Sol (xhigh)
OpenAI
c2e237678933a2d30d1b1dd67ee5fcf0
Codex - GPT-5.6 Sol (high)
OpenAI
c8b8aff9f05b372655e2c62efe4b27d0
Index score table (42 models)
ScoreThe published AA Coding Agents snapshot places Claude Code - Opus 5 (max) first at 65.5%. The third row is 1.4 points behind. The broader top-10 range is 6.8 points, so many of the published results sit in a relatively narrow band.
42 models have been evaluated on AA Coding Agents. The benchmark falls in the Coding category. This category carries a 20% weight in BenchLM.ai's overall scoring system. AA Coding Agents is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
About AA Coding Agents
Year
2026
Tasks
Composite over DeepSWE, Terminal-Bench v2, and SWE-Atlas-QnA
Format
Average pass@1 index
Difficulty
Real-world coding-agent workflows
BenchLM mirrors the Artificial Analysis Coding Agent Index v1.1 page as a display-only external leaderboard. The source combines DeepSWE, Terminal-Bench v2, and SWE-Atlas-QnA component scores and publishes cost, token, and execution-time metadata. Rows are coding-agent systems rather than pure base-model results.
BenchLM freshness & provenance
Version
AA Coding Agents 2026
Refresh cadence
Quarterly
Staleness state
Current
Question availability
Public benchmark set
BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.
FAQ
What does AA Coding Agents measure?
A display-only Artificial Analysis leaderboard for coding-agent systems, combining agent harnesses, host models, and execution settings across software-engineering benchmarks.
Which model leads the published AA Coding Agents snapshot?
Claude Code - Opus 5 (max) currently leads the published AA Coding Agents snapshot with 65.5% index score. BenchLM shows this benchmark for display only and does not use it in overall rankings.
How many models are evaluated on AA Coding Agents?
42 AI models are included in BenchLM's mirrored AA Coding Agents snapshot, based on the public leaderboard captured on June 2026 page snapshot.
Know when it’s worth switching models
The model to choose, the cheaper alternative, and the release we would wait on.
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