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Baseten vs FastInfra: Token Pricing, Speed & Intelligence

Full comparison of Baseten and FastInfra — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.

Baseten

Production ML infrastructure — deploy any model with custom serving, autoscaling, and GPU selection

Baseten is a production ML infrastructure platform for deploying custom and open-weight models with full control over serving configuration, GPU selection, autoscaling, and cold-start behavior. Unlike managed inference APIs, Baseten lets you bring your own model weights, custom preprocessing, and serving logic. It supports Truss (Baseten's open-source model packaging format), vLLM, TensorRT-LLM, and custom Python serving code. Ideal for teams that need more control than a managed API but less overhead than raw Kubernetes.

Custom model deploymentFine-tuned modelsML infrastructureProduction servingOpen-weight models
Open-weight hostHosts open weights

FastInfra

Inference platform + GPU pods — 785+ models, Amazon Nova, H200 capacity

FastInfra is a hybrid inference platform combining a model router (785+ models) with its own H200 GPU capacity. It offers Amazon Nova Lite and Nova Micro at very competitive rates, with prepaid credits from $5. Part inference router, part dedicated GPU cloud.

Cost-sensitive workloadsBroad model accessAmazon Nova inference
Open-weight hostHosts open weights

Key metric comparison

Cheapest input ($/1M)

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$0.04

Cheapest output ($/1M)

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$0.15

Peak throughput

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—

Best latency (TTFT)

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—

Intelligence score

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Context window

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300K

Live token pricing

Basetenlive pricing

No live pricing data available.

FastInfralive pricing

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ModelInputOutput
Amazon Nova Lite$0.06EST Oct 2026$0.25
Amazon Nova Micro$0.04EST Oct 2026$0.15

Strengths and weaknesses

Baseten

Full control over model serving: custom preprocessing, postprocessing, and business logic
Bring your own weights — deploy any HuggingFace model or custom fine-tune
GPU selection: H100, A100, A10G, T4 with per-second billing
Autoscaling including scale-to-zero for cost efficiency
Truss open-source packaging format for reproducible model deployments
More setup required than managed APIs — not a drop-in OpenAI replacement
Cold starts on scale-to-zero deployments (configurable warm pool available)
Pricing is higher than shared inference APIs for low-volume workloads

FastInfra

785+ models via router — broad catalog coverage
Own H200 GPU capacity for low-latency inference
Very competitive Amazon Nova Lite ($0.06/$0.25) and Nova Micro ($0.04/$0.15) rates
Prepaid from $5 — low barrier to entry
Newer provider — limited ecosystem integrations and third-party reviews
Hybrid router/own-capacity model means latency may vary by model
Limited benchmark transparency

Key differentiators

Baseten

The production ML platform that gives you managed-API convenience with custom-serving flexibility — deploy any model with your own preprocessing logic, GPU selection, and autoscaling without managing Kubernetes.

FastInfra

Hybrid inference platform with 785+ models via router and own H200 capacity, offering Amazon Nova at very competitive rates.

Frequently asked questions

Baseten FAQs

What is Baseten?

Baseten is a production ML infrastructure platform for deploying AI models with custom serving logic, GPU selection, and autoscaling. It supports any open-weight model or custom fine-tune via the Truss packaging format.

How does Baseten differ from Together AI or Replicate?

Baseten gives you full control over the serving stack — custom preprocessing, postprocessing, GPU selection, and autoscaling behavior. Together AI and Replicate are managed APIs with fixed serving; Baseten is for teams that need custom model serving logic.

What GPUs does Baseten support?

Baseten supports H100 SXM, H100 PCIe, A100 80GB, A10G, and T4 GPUs with per-second billing. You select the GPU type per deployment based on your model's memory and throughput requirements.

FastInfra FAQs

What is FastInfra?

FastInfra is a hybrid inference platform combining a 785+ model router with its own H200 GPU capacity. It offers Amazon Nova Lite ($0.06/$0.25 per 1M tokens) and Nova Micro ($0.04/$0.15), with prepaid credits from $5. See fastinfra.ai/pricing for current rates.

Does FastInfra have its own GPU capacity?

Yes. FastInfra operates its own H200 GPU infrastructure alongside a model router, so some models run on dedicated capacity rather than being routed to third-party providers.

Provider resources

Key strengths compared

Baseten

  • Full control over model serving: custom preprocessing, postprocessing, and business logic
  • Bring your own weights — deploy any HuggingFace model or custom fine-tune
  • GPU selection: H100, A100, A10G, T4 with per-second billing
  • More setup required than managed APIs — not a drop-in OpenAI replacement
  • Cold starts on scale-to-zero deployments (configurable warm pool available)

FastInfra

  • 785+ models via router — broad catalog coverage
  • Own H200 GPU capacity for low-latency inference
  • Very competitive Amazon Nova Lite ($0.06/$0.25) and Nova Micro ($0.04/$0.15) rates
  • Newer provider — limited ecosystem integrations and third-party reviews
  • Hybrid router/own-capacity model means latency may vary by model

Key weaknesses compared

Baseten

  • More setup required than managed APIs — not a drop-in OpenAI replacement
  • Cold starts on scale-to-zero deployments (configurable warm pool available)
  • Pricing is higher than shared inference APIs for low-volume workloads

FastInfra

  • Newer provider — limited ecosystem integrations and third-party reviews
  • Hybrid router/own-capacity model means latency may vary by model
  • Limited benchmark transparency

Provider category context

Baseten is a inference api, founded in 2019. FastInfra is a inference api, founded in 2024. Both are inference api providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.

How to choose between them

Both Baseten and FastInfra host open-weight models. The key differentiators are latency, throughput, and which specific model versions each provider offers. Check the speed metrics above — inference API providers often differ significantly on tokens-per-second for the same model. Pricing is typically competitive between them; availability of specific model versions (e.g., Llama 3.1 405B, DeepSeek V3) may be the deciding factor.