Nemotron 3.5 Super VL API Provider Benchmarking & Analysis
This analysis is intended to support you in choosing the best API provider of Nemotron 3.5 Super VL for your use-case.
Lowest Time per Task
Baseten
DeepInfra
Together AI (NVFP4)
PrimaLabs (NVFP4)
CoreWeave (NVFP4)Time per Intelligence Index task (minutes)
Total 8 providers
Lowest Cost per Task
BasetenDeepInfraPrimaLabs (NVFP4)CoreWeave (NVFP4)
CrusoeCost per Intelligence Index task
Total 8 providers
Nemotron 3.5 Super VL is available through 8 API providers, each offering different performance characteristics and pricing. Below is a comparison of the key metrics across providers.
- For time per task, Baseten (2.7 min), DeepInfra (3.5 min), and Together AI (NVFP4) (3.5 min) finish an Intelligence Index task fastest.
- For cost per task, Baseten ($0.31), DeepInfra ($0.35), and PrimaLabs (NVFP4) ($0.45) are the cheapest per Intelligence Index task. Cost varies up to 3.0x across providers.
- Baseten is both the quickest and the cheapest per task.
Pricing
Cost per Intelligence Index Task: Nemotron 3.5 Super VL
Pricing: Cache Hit, Input, and Output: Nemotron 3.5 Super VL
Output Speed vs. Cost per Task: Nemotron 3.5 Super VL
Speed
Average of the single-request and multi-turn agentic workloads measured
Time per Intelligence Index Task: Nemotron 3.5 Super VL
Latency
Average of the single-request and multi-turn agentic workloads measured
Time to First Answer Token: Nemotron 3.5 Super VL
Reliability
Share of requests the endpoint failed, across all the single-request and multi-turn agentic workloads measured
Endpoint Error Rate: Nemotron 3.5 Super VL
Caching
Cache Hit Rate: Nemotron 3.5 Super VL
Cost per Task vs. Cache Hit Rate: Nemotron 3.5 Super VL
Key Comparison Metrics & API Features
Frequently Asked Questions
Common questions about Nemotron 3.5 Super VL providers
Nemotron 3.5 Super VL is available through 8 API providers: PrimaLabs (NVFP4), DeepInfra, Baseten, Nebius, CoreWeave (NVFP4), DigitalOcean, Crusoe, and Together AI (NVFP4). Each provider offers different performance characteristics and pricing.
Nemotron 3.5 Super VL is currently available through 8 API providers that we benchmark and track.
By time per task, the fastest providers for Nemotron 3.5 Super VL are Baseten (2.7 min), DeepInfra (3.5 min), and Together AI (NVFP4) (3.5 min). Time per task divides the model's output tokens per Intelligence Index task by each provider's end-to-end output speed.
The providers with the lowest time to first answer token for Nemotron 3.5 Super VL are DeepInfra (6.41s), Baseten (6.61s), and PrimaLabs (NVFP4) (8.74s). Lower latency means faster initial response time.
The most affordable providers for Nemotron 3.5 Super VL by blended price are DeepInfra ($0.09 per 1M tokens), Together AI (NVFP4) ($0.09 per 1M tokens), and Crusoe ($0.12 per 1M tokens). Blended price uses a 7:2:1 cache hit/input/output token ratio.
The providers with the lowest input token pricing for Nemotron 3.5 Super VL are Crusoe ($0.10 per 1M input tokens), DeepInfra ($0.15 per 1M input tokens), and Together AI (NVFP4) ($0.15 per 1M input tokens).
Prices for Nemotron 3.5 Super VL vary up to 2.5x across providers. The most affordable is DeepInfra at $0.09 per 1M tokens, while PrimaLabs (NVFP4) charges $0.24 per 1M tokens.
All 8 providers of Nemotron 3.5 Super VL support JSON mode for structured output.
All 8 providers of Nemotron 3.5 Super VL support function calling (tool use).
When choosing a provider for Nemotron 3.5 Super VL, consider: time per task (how quickly the provider completes an Intelligence Index task), latency (for interactive applications requiring quick first responses), pricing (for cost-sensitive workloads), and API features like JSON mode or function calling.
Yes, provider performance can vary over time due to infrastructure changes, load balancing, and updates. We continuously benchmark all providers and display historical performance trends in the "Over Time" charts.
For information about Nemotron 3.5 Super VL's intelligence, capabilities, modalities, and how it compares to other models, see the model overview page. View model overview