State of the art models are two-thirds smarter than they were last November. The frenetic pace of improvement is sustained, two new models every three days. ¹

But 84% of tokens on OpenRouter aren’t state of the art. ^{2 3}

In fact, the six models users choose to generate the supermajority of those tokens deliver about 77% of the performance of the frontier. They cost 2.5% of what Claude Fable 5 does. ²

The index keeps jumping. Large gains of three to five Artificial Analysis points land about every quarter. Smaller steps fill the gaps.

Six models carry 80% of volume in the week of August 10. Their blended price is $0.50 per million tokens against Fable 5 at $20.

Ramp’s data shows buyers are price-elastic. Fable 5 at about $10/m tokens captured 6% of Anthropic tokens & 11% of Anthropic spend a month after launch. GPT-5.6 Sol, OpenAI’s priciest mainline tier, held about a quarter of OpenAI tokens. ⁴

Fable 5 generated roughly 75% as much model-attributed revenue as GPT-5.6 Sol in July, despite being substantially more expensive.

Each new state of the art release should move less share than the one before it.

Enterprises will consolidate spend. Contracts concentrate on one or two vendors, just like in the cloud era, & once a model clears a high-value job the workload stays.

Performance is already good enough at a meaningful discount. The gap keeps closing from below. The best open-weight model reached 80% of the frontier score by May, up from 48% a year earlier. ²

Application deployment is the other story. More of our portfolio companies & startups default to smaller models, fine-tuned models, & open source. They are optimizing against a different Pareto frontier, price over performance.

If share stops shifting & good enough stays good enough, the economics of SOTA change. A nine-figure training run has to win share to pay for itself, & that bar will rise with time.

The title is flippant. Plenty buy SOTA, & for good reason. Software engineering architecture & security design are the clearest cases, where the best available model earns its price.

But the open data we do have suggests the frontier that matters is the other one.

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1. Artificial Analysis model catalog & Intelligence Index. Major-lab monthly release counts & frontier path. Sample starts 2025-11-01. Release-rate trend flat. Median gap between large (≥3 pt) frontier steps about 3.5 months. Intelligence Index ↩︎

2. State of the art means the single best Artificial Analysis score available in a given week; a model counts as near it when the score sits within 10% of that week’s best named model. OpenRouter weekly named top models joined to Artificial Analysis scores, the head of the OpenRouter carousel rather than every API. Share series, weeks 2025-11-03 through 2026-05-25 (n=30), named only, Others excluded. First vs last thirteen weeks about 17.5% vs 14.6% near the frontier (~82-85% outside). Concentration snapshot, week of 2026-08-10, models covering the first ~80% of named tokens. Token-weighted Artificial Analysis about 23% behind global catalog state of the art (~77% of frontier quality) & about 10% behind the best model on that OpenRouter list. Blended basket about $0.50/m tokens vs Fable 5 at $20/m (~40x). May 2026 historical check, about 16% behind the local list leader. Best open-weight model 47.5% of frontier score in the first thirteen weeks vs 70.9% in the last thirteen; single best week 2026-05-25, DeepSeek V4 Pro at 45.27 vs frontier 56.31 (80.4%). OpenRouter rankings ↩︎ ↩︎ ↩︎

3. These data sources don’t capture the first-party clouds, OpenAI, Anthropic & Google’s own services. Frontier traffic running on native APIs never enters the OpenRouter rankings, so there’s a bias to the data. ↩︎

4. Ramp Economics Lab, AI Index August 2026 (Fable 5 uptake). econlab.substack.com/p/ai-index-august-2026 ↩︎