Flagship coding-agent performance from small local models.
Villani Code is a local-first coding-agent runtime designed to make smaller open models do real repository work: navigate files, run commands, make patches, survive verification, and keep working through messy terminal environments.
The thesis is simple: small models do not just need better weights. They need a better runtime.
Villani Code achieved a 196/445 lower-bound score on the full Terminal-Bench 2.0 suite using Qwen3.6 27B.
That is 44.0% across 89 tasks with 5 attempts per task.
| System | Model | Terminal-Bench 2.0 accuracy |
|---|---|---|
| Codex CLI | GPT-5-Codex | 44.3% |
| Villani Code | Qwen3.6 27B | 44.0% |
| Mini-SWE-Agent | GPT-5-Codex | 41.3% |
| Claude Code | Claude Sonnet 4.5 | 40.1% |
| Dakou Agent | Qwen 3 Coder 480B | 27.2% |
| little-coder | Qwen3.6-35B-A3B | 24.6% |
| Bash Agent | TermiGen-32B | 19.3% |
| little-coder | Qwen3.5-9B | 9.2% |
Villani Code lands within 0.3 percentage points of Codex CLI + GPT-5-Codex and ahead of Claude Code + Claude Sonnet 4.5, while running a much smaller local Qwen model.
The full visual report is available here:
Villani Code Terminal-Bench 2.0 Qwen3.6 27B Report
Run status: self-run lower-bound benchmark result, not yet Terminal-Bench team verified.
Most coding-agent performance is attributed to the foundation model.
Villani Code shows the runtime can move the frontier too.
The runner matters. Tool handling matters. Failure recovery matters. State management matters. The execution loop matters. The boring engineering around the model matters.
A smaller local model should not be dismissed as weak just because it is small. In the right runtime, it can perform in the same band as much larger flagship coding-agent stacks.
Villani Code was also tested against Claude Code using the same model: Qwen3.5 9B.
Same model. Same tasks. Different agent runtime.
Villani Code won.
| Runner | Score | Success rate |
|---|---|---|
| Villani Code + Qwen3.5 9B | 38/60 | 63.3% |
| Claude Code + Qwen3.5 9B | 26/60 | 43.3% |
Villani Code delivered a 46% relative performance improvement over Claude Code.
This comparison covers 12 overlapping Terminal-Bench tasks, with 5 runs per task, for 60 runs per agent.
Villani Code won 6 tasks, tied 6 tasks, and lost 0.
Villani Code is a terminal-first coding agent for:
- bounded bug fixes
- repo navigation and localization
- command-driven debugging
- test-guided patching
- local inference setups
- privacy-sensitive codebases
- smaller open model backends
It is built for the environment where most coding agents start to fall apart: smaller models, hard verification, constrained context, terminal noise, failed commands, and real repositories.
The latest Villani Code upgrade includes:
- new execution loop
- better local model integration
- cleaner tool handling
- improved failure recovery
- task-scoped memory system
- better state tracking across long-running coding tasks
The benchmark comparison evaluates the upgraded runtime as a whole.
Install with TUI support:
pip install .[tui]Headless CLI only:
pip install .Development dependencies:
pip install .[dev]Interactive session:
villani-code interactive --base-url http://127.0.0.1:1234 --model your-model --repo /path/to/repoOne-shot task:
villani-code run "Add retry handling to API client and update tests." --base-url http://127.0.0.1:1234 --model your-model --repo /path/to/repoAutonomous pass:
villani-code --villani-mode --base-url http://127.0.0.1:1234 --model your-model --repo /path/to/repo