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VultronRetrieverPrime is the flagship of the VultronRetriever family, a late-interaction (ColBERT-style) retriever that scores document pages directly from their rendered image: layout, tables, charts and text, across six languages. It ranks first on the full ViDoRe V3 board with 320-dimensional multi-vectors, an 8–12× smaller index than the 2560–4096-dim models below it. The family has three tiers on one 320-dim recipe: the 8B Prime (this model) for maximum accuracy, the 4.5B Core for the accuracy/footprint mid-point, and the 0.8B Flash for latency- and footprint-sensitive serving. Trained and evaluated on Vultr Cloud. Ranked by **ViDoRe V3** (mean nDCG@10), the headline benchmark; V1 and V2 are shown alongside. Our three tiers are in bold; models with a partial or missing V3 sit at the bottom.
Adjust provider, category or input/output filters. New models are added continuously.
Adjust monthly token usage to compare estimated API costs.
Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.
Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.
Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.
Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.