The result
We submitted the Backboard CLI to the official Terminal-Bench 2.1 leaderboard this week. The numbers:
- Accuracy: 85.4% ± 0.8%
- Pass@5: 0.888
- Coverage: 89 tasks × 5 attempts = 445 trials, all included
- Model: Claude Opus 4.8 via AWS Bedrock
- Total cost of the full run: $280.72 The submission is above every published entry on the leaderboard. The current top published results are Claude Code with Fable 5 at 83.8% ± 1.2% and Codex with GPT-5.5 at 83.1% ± 1.1%. Our PR is open and pending review, and every trial log is public.
Why this matters
Terminal-Bench 2.1 measures what developers actually do: real multi-step tasks in a real terminal. Build failures, dependency messes, debugging under constraints. It's one of the most credible agentic coding benchmarks running.
The leaderboard's top entries are agents built by the same labs that built the underlying models. Claude Code is Anthropic's agent on Anthropic's model. Codex is OpenAI's agent on OpenAI's model.
The Backboard CLI outscored both. On a model we don't make.
That's the point. The harness does the work. How an agent decomposes tasks, delegates to bounded child contexts, and manages what enters the context window determines how much capability you get out of a model. Our CLI is built on a recursive coding engine designed around exactly that, which means performance isn't chained to any single frontier model. Same harness, different model, and it still performs. We've run the same harness on GLM 5.2, a fully open-source model, and scored 72% on this benchmark. That matters if you care about cost, or about running coding agents on infrastructure you control.
How we ran it
No cherry-picking, no re-minting, no overrides:
- Five sequential jobs under one identical agent config
- Pinned dataset (SHA-256 verified), default settings
- All 445 trials included in the reported number
- Errored trials counted as zero reward
- Full logs uploaded and public Benchmarks only mean something if you can check them. Check ours: PR #200.
We're open-sourcing the CLI
The Backboard CLI is going open source. Soon.
We build model-agnostic infrastructure. The whole thesis is that you shouldn't be locked into one lab, one model, or one vendor's agent. Open-sourcing the CLI is that thesis in practice: take the harness, point it at the model you want, run it where you want.
Watch this space, or follow us for the release announcement.
Try it today
You don't have to wait for the repo. The CLI is available now at backboard.io/cli.
Backboard is a Canadian company building full-stack, model-agnostic AI infrastructure: memory ranked #1 on LoCoMo and LongMemEval, routing across 17,000+ models, agentic hybrid RAG, and stateful threads behind one API key. The CLI is one surface of that platform.
Use any model. Keep your options open. Ship faster.
Sources: Terminal-Bench 2.1 leaderboard | Leaderboard submission PR #200
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