A question buyers ask AI

I'm trying to pick an LLM gateway or inference provider for serving open models, and latency, throughput, and cost per token all matter to me. How should I choose?

Measured in 1 answer, last on Nov 8, 2026. Only the passages that name a brand are shown.

Brands in the answers

BrandNamed inRecommended inPositiveAvg. position
Fireworks AI100%100%100%—
Together AI100%100%100%—
Groq100%100%100%—
DeepInfra100%100%100%—
Baseten100%100%100%—
Modal100%100%100%—
OpenRouter100%100%100%—
LiteLLM100%100%100%—
Portkey100%0%0%—
Novita AI100%0%0%—
Nebius100%0%0%—

Where each answer names a brand

Answer 1 · Nov 8, 2026 · 8 sources cited
Fireworks AIRecommendedSite citedpositive
“Strong candidate for production serving, particularly when reliability, model availability, and optimized inference matter.”
+ production reliability and model-serving capabilities

“Best evaluated for: production reliability and model-serving capabilities.”

Together AIRecommendedSite citedpositive
“Broad open-model ecosystem, useful for comparing model families and deployment options. A good baseline when you want flexibility.”
+ breadth of open models and flexible serving

“Best evaluated for: breadth of open models and flexible serving.”

Portkey
“Examples include OpenRouter, LiteLLM, and Portkey.”
GroqRecommendedSite citedpositive
“An interesting alternative for extremely fast inference on supported models. Its specialized hardware makes it worth including in latency-focused tests.”
+ low latency and high generation speed

“Best evaluated for: low latency and high generation speed.”

DeepInfraRecommendedSite citedpositive
“Worth testing as a cost-conscious alternative, especially for high-volume workloads where the actual price/performance ratio matters more than a premium service tier.”
+ cost-sensitive inference

“Best evaluated for: cost-sensitive inference.”

“I'd also include Nebius AI and Novita AI as additional benchmarks, especially if GPU economics and infrastructure flexibility are important.”
“I'd also include Nebius AI and Novita AI as additional benchmarks, especially if GPU economics and infrastructure flexibility are important.”
BasetenRecommendedSite citedpositive
“Particularly interesting if you need optimized deployments, predictable performance, or eventually want to move toward dedicated infrastructure.”
+ latency-sensitive production deployments

“Best evaluated for: latency-sensitive production deployments.”

ModalRecommendedSite citedpositive
“Interesting when you want more control over the serving stack and deployment environment, without immediately operating your own GPU fleet.”
+ customizable inference infrastructure

“Best evaluated for: customizable inference infrastructure.”

OpenRouterRecommendedSite citedpositive
“OpenRouter: Attractive if you want a managed, unified API across a large range of models and providers, without operating your own gateway.”
+ managed, unified API across a large range of models and providers

“Attractive if you want a managed, unified API across a large range of models and providers, without operating your own gateway.”

LiteLLMRecommendedSite citedpositive
“LiteLLM: Particularly attractive if you want to self-host your gateway, control routing logic, and avoid coupling your application to one provider.”
+ self-hosted gateway with routing control

“Particularly attractive if you want to self-host your gateway, control routing logic, and avoid coupling your application to one provider.”

Sources the answers cite

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