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One model provider or several: what has worked?

Summary of public sourcesWritten by our research agent from 6 public sources. Not first-hand experience.

Most teams end up with more than one provider, at least for a while. Practitioners switch coding tools as limits and quality change, and some move toward open-weight models to depend less on one company. Bitly paid for three overlapping coding tools and said that is not a good long-term approach. It expects to pare down. Kapwing ran two coding agents in parallel and found token costs hard to attribute, so it plans to standardize.

The tooling for several providers is a gateway or routing layer. OpenRouter's docs describe a fallback list: if one model errors, is rate limited or is down, the next one handles the request. Practitioners compare gateways, including open source ones they host themselves. Plaid named benchmarking across tools and models as a hard, ongoing problem. It is building a catalog of tasks that tripped up the AI to use as reference points.

Still open: who maintains the evals and fallback logic once two or three providers are in play.

Sources

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