gemini-3.7-flash vs ling-3.0-flash for multi-step reasoning
As of August 24, 2026, gemini-3.7-flash measures 1.000 on multi-step reasoning vs 0.960 for ling-3.0-flash (+0.040), at 18.6× the price ($0.2938 vs $0.0158 per 1K requests).
same suite, same items, same scoring — frontier v4, measured 2026-08-24 · method
| model | vendor | measured quality | $ / 1K requests | p95 latency |
|---|---|---|---|---|
| gemini-3.7-flash | 1.000 | $0.2938 | 3242 ms | |
| ling-3.0-flash | inclusionai | 0.960 | $0.0158 | 12194 ms |
Multi-step reasoning is the workload frontier pricing was built on — and the one where the "do I need it" question has a measurable answer. The suite scores multi-step problems with deterministic ends, so a model’s reasoning is graded on reaching the right result, not on showing appealing work.
These two are part of a larger measured frontier — when do you need a reasoning model shows every measured option for this workload, and other workloads rank these models differently: a model that wins here can lose on another kind of work, which is the whole argument for routing per workload rather than picking one model for everything.
Potion routes each request to the cheapest option measured at your quality bar — including picks this public page does not name. Get an API key or read the docs.