Chutes vs Modal: Token Pricing, Speed & Intelligence

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

Chutes

Open-weight model inference on TEE GPUs

Chutes (chutes.ai) is an inference platform for open-weight models. Workloads run inside Trusted Execution Environments (TEEs) on GPU hardware, with cryptographic attestation of model and input confidentiality. The API is OpenAI-compatible and pricing is per token with no minimum commitment.

Open-weight inferencePrivacy-sensitive workloadsServerless LLM

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

Chutes

TEE-backed inference with cryptographic attestation

OpenAI-compatible API

Serverless, per-token pricing

Supports open-weight models including Llama, Mistral, Qwen, and DeepSeek

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

Chutes

Open-weight inference platform running workloads inside TEEs with cryptographic attestation.

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

Chutes FAQs

What is Chutes?

Chutes is an inference platform for open-weight models. Workloads run inside Trusted Execution Environments (TEEs) on GPU hardware. See chutes.ai for details.

What does TEE inference mean on Chutes?

TEE (Trusted Execution Environment) inference runs model workloads inside a hardware-isolated enclave. Chutes provides cryptographic attestation of this isolation. See their documentation at docs.chutes.ai.

What models does Chutes offer?

Chutes hosts open-weight models including families from Llama, Mistral, Qwen, and DeepSeek. See chutes.ai for the current catalog.

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

Chutes

Provider page

Website

Pricing Docs

Modal

Provider page

Website

Pricing Docs

Chutes — Open-weight model inference on TEE GPUs

Open-weight inference platform running workloads inside TEEs with cryptographic attestation.

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

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

Chutes

TEE-backed inference with cryptographic attestation
OpenAI-compatible API
Serverless, per-token pricing

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

Chutes

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

Chutes is a open source host, founded in 2024. Modal is a inference api. The category difference means these providers serve partially overlapping use cases — compare the model lists and pricing tables above to find the best fit for your specific workload.

How to choose between them

Choose Chutes if you need tee-backed inference with cryptographic attestation. Choose Modal if you need managed hardware and autoscaling — no infrastructure to operate. For high-volume production workloads, run a cost comparison using the token pricing table above with your actual prompt/completion token ratio — the cheapest provider depends heavily on your input-to-output token ratio.