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Same-model provider benchmark
Compare Google Vertex and SambaNova on 4 exact shared text models. ProviderBench keeps speed, price, and catalog coverage separate so naturally faster model catalogs cannot distort the result.
49 indexed models
United States
europe-west1 · Belgium
europe-west4 · NetherlandsGlobalus-central1 · United Statesus-east5 · United Statesus-south1 · United Statesus-west2 · United States6 indexed models
United StatesAt a glance
There is no overall score. Each winner answers one specific question using only directly comparable data.
Fastest on shared models
1.08× typical advantage
3 exact models with complete recent speed data
Lowest token cost
$0.7 / 1M
4 exact models using a 1K-input/500-output mix
Most models available
49 models
Complete catalog coverage across all indexed modalities
| Metric | Google Vertex | SambaNova |
|---|---|---|
| Typical 500-token response | 6.51 s | 7.41 s |
| Typical response start | 0.42 s | 1.18 s |
| Typical output speed | 80.0 tok/s | 100.0 tok/s |
| Blended token price | $0.7 / 1M | $1.3608 / 1M |
| Typical route uptime | 99.89% | 96.92% |
Visual comparison
Google VertexEstimated seconds using recent median response-start and output-speed data. Lower is better.
Google Vertex has the lower typical same-model response ratio across 3 measured models.
USD per 1 million tokens using a 1,000-input/500-output mix. Lower is better.
Google Vertex has the lower typical price ratio across 4 priced shared models.
| Model | Google Vertex | SambaNova |
|---|---|---|
 deepseek/deepseek-v3.2 | Google Vertex
| SambaNova
|
DeepSeek V3.1Winner · Google Vertex deepseek/deepseek-chat-v3.1 | Google Vertex
| SambaNova
|
 gpt-oss-120bWinner · Google Vertex openai/gpt-oss-120b | Google Vertex
| SambaNova
|
 Llama 3.3 70B InstructWinner · SambaNova meta-llama/llama-3.3-70b-instruct | Google Vertex
| SambaNova
|
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 SambaNova analysis
Google Vertex and SambaNova share 4 indexed text models, including DeepSeek V3.2, DeepSeek V3.1, gpt-oss-120b, Llama 3.3 70B Instruct. Google Vertex has the stronger typical response-time result on the directly measured set.
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.
4 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.
Google Vertex has 49 indexed models and lists 7 published server regions; SambaNova has 6 models and lists no regions. Verify data residency, privacy terms, limits, and production latency directly before choosing.
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