ASPIRE-FSM could match or slightly outperform ASPIRE on individual workloads, but the full batch-aware scheduler was more consistent overall. ASPIRE improved on ASPIRE-FSM for both reasoning tasks on both 8B models, while Qwen3-1.7B LB-v2[30k-40k] was a printed counterexample (4.17× versus 4.18×). Overall means were 3.34×/2.08×/2.14× for ASPIRE versus 3.26×/1.94×/1.93× for ASPIRE-FSM.

ASPIRE-FSM could match or slightly outperform ASPIRE on individual workloads, but the full batch-aware scheduler was more consistent overall. ASPIRE improved on ASPIRE-FSM for both reasoning tasks on both 8B models, while Qwen3-1.7B LB-v2[30k-40k] was a printed counterexample (4.17× versus 4.18×). Overall means were 3.34×/2.08×/2.14× for ASPIRE versus 3.26×/1.94×/1.93× for ASPIRE-FSM. · CiteArk

Measurement results

0/16 assessed

0 supported0 disputed or conflicting16 not assessed

The complete result group stays with its claim. Assessed rows come first; their judgments do not replace the whole-claim conclusion. Expand a row for conditions, sources, and evidence history.

Each row is a measurement with its reported value, latest available observation, and cumulative evidence state.
Metric and conditions	Reported	Latest observation	Evidence judgment
model: Qwen3-8B · method: ASPIRE · dataset: AIME25	1.86 × AutoRegressive	—	Not assessed
model: Qwen3-8B · method: ASPIRE-FSM · dataset: AIME25	1.61 × AutoRegressive	—	Not assessed
model: Qwen3-8B · method: ASPIRE · dataset: CodeElo	1.7 × AutoRegressive	—	Not assessed
model: Qwen3-8B · method: ASPIRE-FSM · dataset: CodeElo	1.45 × AutoRegressive	—	Not assessed
model: DS-Llama-8B · method: ASPIRE · dataset: AIME25	1.8 × AutoRegressive	—	Not assessed
model: DS-Llama-8B · method: ASPIRE-FSM · dataset: AIME25	1.6 × AutoRegressive	—	Not assessed
model: DS-Llama-8B · method: ASPIRE · dataset: CodeElo	1.8 × AutoRegressive	—	Not assessed
model: DS-Llama-8B · method: ASPIRE-FSM · dataset: CodeElo	1.55 × AutoRegressive	—	Not assessed
model: Qwen3-1.7B · method: ASPIRE · dataset: LB-v2[30k-40k]	4.17 × AutoRegressive	—	Not assessed
model: Qwen3-1.7B · method: ASPIRE-FSM · dataset: LB-v2[30k-40k]	4.18 × AutoRegressive	—	Not assessed
model: Qwen3-1.7B · method: ASPIRE · dataset: overall	3.34 × AutoRegressive	—	Not assessed
model: Qwen3-1.7B · method: ASPIRE-FSM · dataset: overall	3.26 × AutoRegressive	—	Not assessed

Reported and observed measurements

Assessments (0)

Runs (0)

Measurement results