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Baseten vs Modal: Token Pricing, Speed & Intelligence

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

Baseten

Inference infrastructure for production ML — GLM, DeepSeek V4, Kimi K3, Nemotron, Muse

Baseten is a production ML inference platform offering dedicated and serverless GPU deployments for open-weight models. The catalog includes GLM-5.3, GLM-5.2, DeepSeek V4.1 Flash, DeepSeek V4 Pro 0813, Kimi K3, Nemotron 3.5 Super VL, NVIDIA Nemotron 3 Ultra, GPT OSS 120B, and Muse Spark Open. Baseten is designed for teams that need reliable, low-latency inference with custom deployment options. Pricing is published at baseten.co/pricing.

ProductionOpen-sourceReasoningChinese NLPCost-efficiency
Open-weight hostHosts open weights

Modal

Managed inference API — 10 shared-endpoint models with per-token pricing

Modal Shared Endpoints serve a fixed catalog of models from Modal-managed pools. Modal manages the hardware and autoscaling, and usage is billed per token. Shared Endpoints have model-specific concurrency limits on concurrent in-flight requests. Prices are published rates from modal.com/docs/guide/supported-models.md, re-read 2026-10-31.

InferenceCost-efficiencyOpen-sourceChat
Open-weight hostHosts open weights

Key metric comparison

Cheapest input ($/1M)

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Cheapest output ($/1M)

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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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Live token pricing

Strengths and weaknesses

Baseten

Dedicated GPU deployments for production reliability and consistent latency
GLM-5.3, GLM-5.2, DeepSeek V4.1 Flash/Pro, Kimi K3, Nemotron, Muse Spark Open
Fast and Fast variants for throughput-optimised inference
Custom deployment options — bring your own model or use the catalog
Production-grade SLAs and monitoring
Smaller catalog than Together AI or Fireworks
Less documentation for new users than major providers
Dedicated deployments require more setup than pure serverless

Modal

Managed hardware and autoscaling — no infrastructure to operate
Published per-token rates including cached-input pricing
OpenAI-style per-token billing across all 10 models
Cached-input pricing available on every model in the catalog
Small fixed catalog of 10 models
Model-specific concurrency limits on shared pools
Prices are published rates re-read 2026-10-31, not continuously collected

Key differentiators

Baseten

Production ML inference infrastructure with dedicated GPU deployments — GLM-5.3, DeepSeek V4.1, Kimi K3, and Nemotron with Fast variants for throughput-optimised workloads.

Modal

Modal Shared Endpoints provide managed per-token inference on a fixed 10-model catalog with published cached-input pricing and no infrastructure to manage.

Frequently asked questions

Baseten FAQs

What is Baseten?

Baseten is a production ML inference platform offering dedicated and serverless GPU deployments for open-weight models including GLM-5.3, DeepSeek V4.1 Flash, Kimi K3, Nemotron, and Muse Spark Open. See baseten.co/pricing for current rates.

What models does Baseten offer?

Baseten's catalog includes GLM-5.3, GLM-5.3 Fast, GLM-5.3-Flash, GLM-5.2, GLM-5.2 Fast, DeepSeek V4.1 Flash, DeepSeek V4.1 Flash Fast, DeepSeek V4 Pro 0813, Kimi K3, Nemotron 3.5 Super VL, NVIDIA Nemotron 3 Ultra, GPT OSS 120B, and Muse Spark Open. See baseten.co/pricing for current rates.

How much does Baseten cost?

As of October 2026: GLM-5.3 $1.40/$4.40, GLM-5.3 Fast $2.10/$6.60, GLM-5.3-Flash $0.15/$0.50, DeepSeek V4.1 Flash $0.30/$1.20, DeepSeek V4 Pro 0813 $1.32/$3.96, Kimi K3 $3.00/$15.00, Nemotron 3.5 Super VL $0.20/$0.50, GPT OSS 120B $0.10/$0.50. See baseten.co/pricing for current rates.

Modal FAQs

What models does Modal offer on Shared Endpoints?

Modal Shared Endpoints currently serve 10 models: GLM 5.3 Flash NVFP4, DeepSeek V4.1 Flash 1017, DeepSeek V4.1 Flash, GLM 5.3 Flash, Muse Spark Open, GLM 5.3, Inkling NVFP4, Qwen3.8-Max, Qwen3.8-Max VL, and Kimi K3. Use the model table above for per-model pricing and capability details. Source: Modal's published Shared Endpoints catalog, re-read 2026-10-31.

How much does Modal charge per 1M tokens?

Modal Shared Endpoints input prices range from $0.15/1M (GLM 5.3 Flash NVFP4) to $3.00/1M (Kimi K3). All models include cached-input pricing. See the model table for full per-model rates.

Does Modal offer prompt caching?

Yes. All 10 models in the Modal Shared Endpoints catalog have published cached-input pricing, ranging from $0.005/1M (DeepSeek V4.1 Flash 1017) to $0.30/1M (Kimi K3). Depending on the model, the cached-input rate is 77.5% to 98% below the standard input rate. Source: Modal's published Shared Endpoints rates, re-read 2026-10-31.

Provider resources

Baseten — Inference infrastructure for production ML — GLM, DeepSeek V4, Kimi K3, Nemotron, Muse

Baseten is a production ML inference platform offering dedicated and serverless GPU deployments for open-weight models. The catalog includes GLM-5.3, GLM-5.2, DeepSeek V4.1 Flash, DeepSeek V4 Pro 0813, Kimi K3, Nemotron 3.5 Super VL, NVIDIA Nemotron 3 Ultra, GPT OSS 120B, and Muse Spark Open. Baseten is designed for teams that need reliable, low-latency inference with custom deployment options. Pricing is published at baseten.co/pricing.

Production ML inference infrastructure with dedicated GPU deployments — GLM-5.3, DeepSeek V4.1, Kimi K3, and Nemotron with Fast variants for throughput-optimised workloads.

Modal — Managed inference API — 10 shared-endpoint models with per-token pricing

Modal Shared Endpoints serve a fixed catalog of models from Modal-managed pools. Modal manages the hardware and autoscaling, and usage is billed per token. Shared Endpoints have model-specific concurrency limits on concurrent in-flight requests. Prices are published rates from modal.com/docs/guide/supported-models.md, re-read 2026-10-31.

Modal Shared Endpoints provide managed per-token inference on a fixed 10-model catalog with published cached-input pricing and no infrastructure to manage.

Key strengths compared

Baseten

  • Dedicated GPU deployments for production reliability and consistent latency
  • GLM-5.3, GLM-5.2, DeepSeek V4.1 Flash/Pro, Kimi K3, Nemotron, Muse Spark Open
  • Fast and Fast variants for throughput-optimised inference
  • Smaller catalog than Together AI or Fireworks
  • Less documentation for new users than major providers

Modal

  • Managed hardware and autoscaling — no infrastructure to operate
  • Published per-token rates including cached-input pricing
  • OpenAI-style per-token billing across all 10 models
  • Small fixed catalog of 10 models
  • Model-specific concurrency limits on shared pools

Key weaknesses compared

Baseten

  • Smaller catalog than Together AI or Fireworks
  • Less documentation for new users than major providers
  • Dedicated deployments require more setup than pure serverless

Modal

  • Small fixed catalog of 10 models
  • Model-specific concurrency limits on shared pools
  • Prices are published rates re-read 2026-10-31, not continuously collected

Provider category context

Baseten is a inference api, founded in 2019. Modal is a inference api. 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 Modal 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.