Open-weight models now handle 56% of AI gateway traffic

Open-weight models crossed a majority of AI Gateway token volume in August, reaching 56%, per Vercel's September AI Gateway Production Index. Nine months earlier, in December 2025, that share was 7%. For any team defaulting high-volume calls to a frontier model, that gap is real budget sitting on the table.

The money didn't follow the tokens. Open weights accounted for just 14% of dollars spent on the gateway. Anthropic alone took 64% of all spending, with Claude Opus 5 responsible for 22.5% by itself.

Average token cost fell 23.2% in August alone and more than 50% over five months.

In matched twelve-day windows after launch, GPT-6 Astra took 7.7% of gateway spend against Fable 5.1's 3.7%, even though twice as many teams used Fable.

Read together, the volume and spending numbers describe two tiers splitting further apart. Open weights are absorbing classification, extraction, routing, and summarization, the work you run thousands of times a day where cost matters more than quality. Frontier closed models keep the calls where a wrong answer is expensive.

This is first-party telemetry from a gateway that sees real production traffic, which makes it a cleaner read than a survey. It's also Vercel's own customer base, skewed toward companies that already deploy there. Treat the absolute percentages as directional and the trend line as the real signal.

The shift shows up in what's getting built for that cheap tier. Cactus Compute's Needle 3 is a 121M-parameter tool-calling model that ships in 8-29MB slices. It returns a filled-in function call or a typed record, and returns an empty list rather than guessing when no declared tool fits.

It's a component built to return a type, not a chat model that returns a string, a different engineering problem than prompt tuning.