We raised $5.1M for long-running agents.
Subconscious
vs

Hugging Face Inference Providers vs Modal

Hugging Face serves ready open models through a routed API billed per token. Modal hosts nothing by default; you bring weights and pay for GPUs by the second.

By The Subconscious Team · Updated

Hugging Face Inference Providers vs Modal: key differences

These answer different questions. Hugging Face Inference Providers is for calling a model that already runs somewhere. One token reaches 132 chat models, from GLM 5.3 and Kimi K3 to gpt-oss-120b, across 17 partner hosts at their per-token rates with no markup. There is nothing to deploy and no fine-tuning. Modal is serverless compute. A developer decorates a Python function with the GPU it needs, and Modal builds the container, autoscales it and scales it to zero, billing per second from $0.59 an hour for a T4 to $3.95 for an H100 at list. It has no model catalog, so any model, fine-tune or serving stack is fair game, and context depends on what you deploy.

Hugging Face does have a dedicated option closer to Modal: Inference Endpoints, per-minute billing on AWS, GCP or Azure with vLLM, SGLang, TGI or llama.cpp, from $0.50 an hour for a T4. Modal's lead is flexibility. One platform covers inference, fine-tuning, batch jobs and agent sandboxes, and its free Starter plan renews $30 of credits a month, well above Hugging Face's $0.10 for free accounts and $2 for PRO. Modal's costs need watching, though. Non-preemptible US production runs about 3.75x list, and keeping containers warm to avoid weight-loading cold starts turns serverless into always-on. For a popular open model, the router is less work. For private weights, embeddings or OCR, Modal fits better.

What Hugging Face Inference Providers and Modal do

Hugging Face Inference Providers

Inference Providers is a router run by Hugging Face that sits in front of partner inference clouds. The current partner list covers Baseten, Cerebras, Cohere, DeepInfra, fal, Featherless AI, Fireworks, Groq, Novita, Nscale, OVHcloud, Public AI, Replicate, Scaleway, Together, WaveSpeedAI and Z.ai, plus Hugging Face's own HF Inference, which now mostly serves CPU workloads like embeddings and classification. Chat traffic goes through an OpenAI-compatible endpoint at router.huggingface.co/v1, and the Python and JavaScript clients add text-to-image, video, speech and embeddings. The router lists 132 chat models today, from GLM 5.3 and Kimi K3 to gpt-oss-120b on eleven providers.

Example models: GLM 5.3, Kimi K3, gpt-oss-120b

Full Hugging Face Inference Providers profile

Modal

Modal is serverless compute with GPUs attached. A developer decorates a Python function with the hardware it needs, such as gpu="H100", and Modal builds the container, schedules it, autoscales it and scales it back to zero. Billing runs per second with no minimum increment, from $0.59 an hour for a T4 to $3.95 for an H100 at list. Containers can hold up to 8 GPUs across T4 through B300.

Example models: none hosted by default; teams deploy their own, such as open LLMs on vLLM or Whisper

Full Modal profile

Should you choose Hugging Face Inference Providers or Modal?

Hugging Face Inference Providers

Choose Hugging Face Inference Providers for

  • Calling popular open models with no deployment
  • Per-token billing on light or uneven chat traffic
  • Comparing hosts for the same model

Modal

Choose Modal for

  • Private fine-tunes and custom models
  • Bursty GPU jobs like embeddings and transcription
  • Training, batch and sandboxes on one platform

Hugging Face Inference Providers vs Modal at a glance

AttributeHugging Face Inference ProvidersModal
Model accessOpen weightsBring your own weights
Flagship modelsGLM 5.3, Kimi K3, DeepSeek V4.1 FlashNone hosted
SpeedRoutes to fastest provider by default~1s container boot
PriceProvider rates, no markupPer second; H100 $3.95/hr list
CustomizationN/ARun any training code
DeploymentServerless router; dedicated EndpointsServerless GPU containers
Long contextUp to 1M, provider-dependentDepends on the model you deploy

Frequently asked questions

What is the difference between Hugging Face Inference Providers and Modal?

Hugging Face serves ready open models through a routed API billed per token. Modal hosts nothing by default; you bring weights and pay for GPUs by the second.

When should I choose Hugging Face Inference Providers over Modal?

Calling popular open models with no deployment; Per-token billing on light or uneven chat traffic; Comparing hosts for the same model.

When should I choose Modal over Hugging Face Inference Providers?

Private fine-tunes and custom models; Bursty GPU jobs like embeddings and transcription; Training, batch and sandboxes on one platform.

Is Hugging Face Inference Providers or Modal cheaper?

Hugging Face Inference Providers: Provider rates, no markup. Modal: Per second; H100 $3.95/hr list. The cheaper choice depends on the model and workload.

Which has more context, Hugging Face Inference Providers or Modal?

Hugging Face Inference Providers: Up to 1M, provider-dependent. Modal: Depends on the model you deploy.

Related comparisons

Running long-horizon agents?

If your agents run past 200K tokens, compare both against Subconscious. Our inference stack treats a long-horizon trace as the primary workload, so speed, cost, and accuracy hold up deep into the trace.

Subconscious vs Hugging Face Inference ProvidersSubconscious vs Modal