Modal vs Replicate: Token Pricing, Speed & Intelligence
Full comparison of Modal and Replicate — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.
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.
Replicate
Run any open-source AI model via API — FLUX 1.1 Pro, Llama 4, video, audio, and custom models
Replicate is a platform for running open-source AI models via a simple API. It hosts thousands of community models including FLUX 1.1 Pro, Llama 4, Stable Diffusion, Whisper, and video generation models. Pay per prediction with no infrastructure to manage. The 2026 catalog has expanded significantly with FLUX 1.1 Pro Ultra, Kling v2.1, and Llama 4 Scout/Maverick. Custom model deployment via Cog remains a core differentiator.
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Live token pricing
Strengths and weaknesses
Modal
Replicate
Key differentiators
Modal Shared Endpoints provide managed per-token inference on a fixed 10-model catalog with published cached-input pricing and no infrastructure to manage.
A broad catalog of community AI models — if a model exists on Hugging Face, it's likely on Replicate. Strong coverage for image, video, and audio model access, plus custom model deployment via Cog.
Frequently asked questions
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.
Replicate FAQs
What new models did Replicate add in 2026?
Replicate added FLUX 1.1 Pro Ultra, Kling v2.1 (video generation), Llama 4 Scout and Maverick, and many other models in 2026. The catalog is continuously updated as new community models are released.
How does Replicate pricing work?
Replicate charges per prediction based on compute time used. Pricing varies by model and GPU type. Text models are billed per token; image models per image; video models per second of output. Some models are free with rate limits.
Can I deploy my own model on Replicate?
Yes. Replicate lets you package and deploy custom models using Cog, their open-source model packaging tool. Once deployed, your model gets a public API endpoint with automatic scaling.
Provider resources
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.
Replicate — Run any open-source AI model via API — FLUX 1.1 Pro, Llama 4, video, audio, and custom models
Replicate is a platform for running open-source AI models via a simple API. It hosts thousands of community models including FLUX 1.1 Pro, Llama 4, Stable Diffusion, Whisper, and video generation models. Pay per prediction with no infrastructure to manage. The 2026 catalog has expanded significantly with FLUX 1.1 Pro Ultra, Kling v2.1, and Llama 4 Scout/Maverick. Custom model deployment via Cog remains a core differentiator.
A broad catalog of community AI models — if a model exists on Hugging Face, it's likely on Replicate. Strong coverage for image, video, and audio model access, plus custom model deployment via Cog.
Key strengths compared
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
Replicate
- Broad catalog of community AI models — text, image, video, audio
- FLUX 1.1 Pro Ultra and Kling v2.1 in the 2026 catalog
- Llama 4 Scout and Maverick available
- Higher per-token cost than dedicated text inference APIs
- Cold start latency on less popular models
Key weaknesses compared
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
Replicate
- Higher per-token cost than dedicated text inference APIs
- Cold start latency on less popular models
- Less suitable for high-throughput text inference
Provider category context
Modal is a inference api. Replicate is a inference api, founded in 2021. 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 Modal and Replicate 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.