pith:EYGETUQ3
Terminus-4B: Can a Smaller Model Replace Frontier LLMs at Agentic Execution Tasks?
A 4B model can match frontier LLMs at agentic terminal execution tasks
arxiv:2605.03195 v2 · 2026-05-04 · cs.AI · cs.SE
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Claims
Terminus-4B is able to reduce the token usage of the main agent by up to ~30% compared to the No Subagent baseline with no impact to agent performance on benchmarks like SWE-Bench Pro and our internal SWE-Bench C# benchmark... Furthermore, Terminus-4B improves key metrics showing the main agent relying on the outputs of the subagent and doing fewer terminal execution tasks by itself. We see that our model not only closes the gap between the Vanilla Qwen model and frontier models like Claude Sonnet / Opus / GPT-5.3-Codex, but often even exceeds their performance.
That the rubric-based LLM-as-judge reward produces training signals that generalize beyond the specific benchmarks and do not embed biases from the judge model itself.
A fine-tuned 4B model matches or exceeds frontier LLMs in terminal execution subagent tasks for coding agents, reducing main agent token usage by 30% with no performance loss.
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| First computed | 2026-07-09T00:19:14.001205Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
260c49d21bf1c8366d1384fde244b83f60daf6bc5e7c31f4090949de478dc2c6
Aliases
· · · · ·Agent API
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/EYGETUQ36HEDM3ITQT66ERFYH5 \
| jq -c '.canonical_record' \
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Canonical record JSON
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