ModelSpec is an analysis of alternatives for AI models: it decides which models fit a job from your requirements, sourced benchmarks and real cost, and shows its work.

Coding, fastest

Find an active coding model whose offering streams output fastest, among models within 1.0 of the strongest coding estimate.

Worked example as of 2026-09-23, from the public data image.

The fastest of the strong; only models within 1.0 of the strongest coding estimate compete, and speed decides among them.

Requirements

• model.class = text-generator: Coding work needs a model that generates text and code.
• model.lifecycle = active: An active model is still supported by its lab or provider.
• software_engineering >= best(1.0): Keep only models whose coding estimate is within 1.0 of the strongest eligible model's; speed decides among them. A gap of 1.0 can be measurable but is not decisive.

Preferences

• offering.speed.throughput: Among the models the floor keeps, prefer the offering that produces output tokens fastest.

Worked answer

Decision status: no_feasible.

No recommendation: the public image has no answer with enough evidence.

Unknown requirements

Some candidates may qualify. Missing facts:

• offering.speed.throughput
• software_engineering

Missing evidence and possible changes

• no model that meets the requirements has a value for offering.speed.throughput

Decision dec_f4d8c4568df20d05224cc431 on public snapshot snap_05a963d2477ac2fb.

What this template teaches

Strength is a floor relative to the strongest eligible model, so speed can never buy it back. Speed is a Prefer, not a gate. An offering without a measured speed may qualify but is not ranked, so this tier answers only once speeds are published.

The live board uses current data. Its answer can change as evidence changes.

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Use-case examples · How we decide