Compare Google Vertex and Nebius on 3 exact shared text models. ProviderBench keeps speed, price, and catalog coverage separate so naturally faster model catalogs cannot distort the result.
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A per-model winner combines blended price and estimated 500-token response time with equal proportional weight. Ties and rows missing either measurement receive no badge. Comparison data calculated . Values use one deterministic route per provider and model; missing measurements remain visible as N/a.
Google Vertex vs Nebius analysis
How Google Vertex and Nebius compare for AI inference
Google Vertex and Nebius share 3 indexed text models, including gpt-oss-120b, Qwen3 235B A22B Instruct 2507, Llama 3.3 70B Instruct. Nebius has the stronger typical response-time result on the directly measured set.
Same-model speed evidence
3 shared models currently have complete response-start and output-speed measurements on both providers. The speed comparison uses per-model ratios before taking the median, so naturally faster model catalogs do not improve the result.
Token pricing on one workload
3 shared models have complete input and output prices on both providers. Prices use the same 1,000-input/500-output-token mix and are normalized to one million tokens for readability.
Catalog and deployment differences
Google Vertex has 49 indexed models and lists 7 published server regions; Nebius has 13 models and lists no regions. Verify data residency, privacy terms, limits, and production latency directly before choosing.
Related same-model benchmarks
Compare with other providers
Explore qualified alternatives with the most shared measured models. Recommendations include comparisons for both Google Vertex and Nebius.