FDE-Bench: leaderboard
FDE-Bench (Ding et al., 2026) evaluates LLM agents on deployment configuration across 136 tasks spanning Docker images, Compose stacks and Kubernetes, in greenfield and repair modes. Agents share one four-tool scaffold; submitted Dockerfiles, manifests and monitoring configuration are rebuilt and redeployed in a clean sandbox and pass only if the build, readiness, behavior and specification-conformance check layers all pass, with no LLM judge. Resolved rate in percent; higher is better.
Metric: Resolved rate (%; share of the 136 deployment-configuration tasks, 66 greenfield and 70 repair, whose redeployed artifacts pass all four gated check layers; one episode per task, same four-tool scaffold (bash, write_file, read_file, submit), task-specific step, time and token caps; submitted artifacts are rebuilt and redeployed in a pristine sandbox and graded by four gated programmatic check layers (build, readiness, behavior, spec conformance); resolved only if all four pass). Source: arxiv.org. Saturation forecast: Around February 2027. 7 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Gemini 3.6 Flash | 75 | #72 |
| 2 | Claude Sonnet 5 (High) | 72.8 | #108 (Claude Sonnet 5) |
| 3 | DeepSeek V4 Pro | 69.9 | #181 |
| 4 | GPT-5.6 Terra | 69.9 | #60 |
| 5 | DeepSeek V4 Flash | 66.2 | #254 |
| 6 | GPT-5.6 Luna | 63.2 | #117 |
| 7 | Gemini 3.5 Flash Lite | 52.9 | #300 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=fde-bench · How It Works · Data refreshed daily, snapshot 2026-11-12.