aiqbench analysis
TomasuLLM addresses latency bottlenecks in coding agents by implementing out-of-order speculative execution for long-running tool calls, effectively hiding idle time without compromising correctness. By running future actions in isolated sandboxes and validating them against committed state before finalizing results, the system achieves consistent performance gains across complex software engineering benchmarks. This approach mirrors hardware-level optimizations to improve the efficiency of AI-driven development workflows.
TomasuLLM: Out-of-Order Speculative Execution for LLM Agents
arXiv:2609.38201v1 Announce Type: new Abstract: Long-running tools can dominate coding-agent latency: compilers, test suites, and repository commands take seconds to minutes while the agent idles. This observation stall presents the same tension that drove out-of-order processors -- asequential interface hides work that can be predicted and started early, but a speculative result may become visible only after it and every earlier step have been validated. We present TomasuLLM, a runtime that executes agent tool calls out of trajectory order while preserving task-execution correctness. It drafts future actions, runs them in isolated copy-on-write sandboxes, traces their dependencies and effects, and commits results in trajectory order only after validation against committed state. Across three benchmarks spanning sub-second to minutes-long tool calls, TomasuLLM improves the reported benchmark means and scales with tool latency: 1.31x on 100 SWE-bench Verified tasks, 1.35x on 28 Terminal-Bench 2.0 tasks, and 1.27x matched progress on 18 SWE-Marathon sessions. Across 4,010 audited commit-validation records, it produces zero false accepts.
Abstract:Long-running tools can dominate coding-agent latency: compilers, test suites, and repository commands take seconds to minutes while the agent idles. This observation stall presents the same tension that drove out-of-order processors -- asequential interface hides work that can be predicted and started early, but a speculative result may become visible only after it and every earlier step have been validated. We present TomasuLLM, a runtime that executes agent tool calls out of trajectory order while preserving task-execution correctness. It drafts future actions, runs them in isolated copy-on-write sandboxes, traces their dependencies and effects, and commits results in trajectory order only after validation against committed state. Across three benchmarks spanning sub-second to minutes-long tool calls, TomasuLLM improves the reported benchmark means and scales with tool latency: 1.31x on 100 SWE-bench Verified tasks, 1.35x on 28 Terminal-Bench 2.0 tasks, and 1.27x matched progress on 18 SWE-Marathon sessions. Across 4,010 audited commit-validation records, it produces zero false accepts.
Computation and Language (cs.CL); Operating Systems (cs.OS); Software Engineering (cs.SE)
arXiv:2609.38201 [cs.CL]
(or arXiv:2609.38201v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2609.38201 Focus to learn more arXiv-issued DOI via DataCite
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Full text under the publisher's open licence · 254 words
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