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fal.ai vs Modal: Token Pricing, Speed & Intelligence

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

fal.ai

Sub-second image generation — FLUX 1.1 Pro Ultra, video, audio, and B200/H200 GPU compute

fal.ai is a serverless inference platform specialising in image, video, and audio generation models. Known for sub-second cold starts and competitive pricing on FLUX 1.1 Pro Ultra, Kling v2.1, and Stable Diffusion. The 2026 platform has expanded to include B200 GPU compute alongside H200, and added real-time video generation with streaming output. A leading choice for production AI creative tools.

Image generationVideo generationAudio modelsReal-time AI appsCreative toolsGPU compute
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

fal.ai
Modal
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

fal.ai

Sub-second cold starts for FLUX and Stable Diffusion — very fast image generation
FLUX 1.1 Pro Ultra and Kling v2.1 in the 2026 catalog
B200 and H200 GPU compute for custom deployments
Real-time video generation with streaming output
Serverless — no infrastructure management
Competitive pricing on FLUX models vs Replicate
Primarily focused on image/video/audio — less suited for text LLMs
Smaller text model catalog than dedicated LLM providers
Less enterprise support than larger platforms

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

fal.ai

The fastest serverless platform for image and video generation — sub-second cold starts on FLUX 1.1 Pro Ultra and Kling v2.1, with B200/H200 GPU compute for custom 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

fal.ai FAQs

What models does fal.ai support in 2026?

fal.ai hosts FLUX 1.1 Pro Ultra, FLUX.1 Dev/Schnell, Kling v2.1 (video), Stable Diffusion XL, Whisper, and many other image, video, and audio models. It also supports text models via its serverless GPU platform.

How fast is fal.ai for image generation?

fal.ai delivers sub-second cold starts for popular models like FLUX — typically under 500ms for FLUX.1 Schnell. This makes it a strong option for real-time image generation in production applications.

Does fal.ai offer GPU compute?

Yes. fal.ai offers B200 and H200 GPU compute for custom model deployments alongside its managed inference API, suitable for teams that need both managed inference and raw GPU access.

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

fal.ai

Provider page
Website
PricingDocs

Modal

Provider page
Website
PricingDocs

fal.ai — Sub-second image generation — FLUX 1.1 Pro Ultra, video, audio, and B200/H200 GPU compute

fal.ai is a serverless inference platform specialising in image, video, and audio generation models. Known for sub-second cold starts and competitive pricing on FLUX 1.1 Pro Ultra, Kling v2.1, and Stable Diffusion. The 2026 platform has expanded to include B200 GPU compute alongside H200, and added real-time video generation with streaming output. A leading choice for production AI creative tools.

The fastest serverless platform for image and video generation — sub-second cold starts on FLUX 1.1 Pro Ultra and Kling v2.1, with B200/H200 GPU compute for custom 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

fal.ai

  • Sub-second cold starts for FLUX and Stable Diffusion — very fast image generation
  • FLUX 1.1 Pro Ultra and Kling v2.1 in the 2026 catalog
  • B200 and H200 GPU compute for custom deployments
  • Primarily focused on image/video/audio — less suited for text LLMs
  • Smaller text model catalog than dedicated LLM 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

fal.ai

  • Primarily focused on image/video/audio — less suited for text LLMs
  • Smaller text model catalog than dedicated LLM providers
  • Less enterprise support than larger platforms

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

fal.ai is a inference api, founded in 2022. 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 fal.ai 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.