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Modal vs Inference.net
Inference.net sells cheap batch on spare GPU capacity and a path from traces to custom models. Modal sells per-second GPU containers for any code. Managed pipeline versus build-your-own.
By The Subconscious Team · Updated
Modal vs Inference.net: key differences
Inference.net packages a workflow; Modal packages compute. Inference.net's Batch API takes up to 1M requests per file with windows of 24 hours to 7 days, priced low because it runs on otherwise idle GPU time. Its Gateway routes traffic to open, closed or custom models under one key, captures requests as eval and training data, and then fine-tunes and deploys a task-specific model on a dedicated GPU. Modal gives developers GPUs from a Python decorator and bills per second, with no models or datasets built in.
Teams that want to replace a narrow GPT-class workload with a cheaper fine-tuned model get more help from Inference.net, since it handles collection, training and deployment. Modal suits teams that already have a model and serving code, or need non-LLM jobs like OCR and transcription. Inference.net's spare capacity fits batch better than strict real-time work, and independent benchmarks are scarce. Modal serves real-time endpoints but charges for warm containers to avoid cold starts.
What Modal and Inference.net do
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 profileInference.net
Inference.net started as a buyer of last resort for idle GPU time. Its scheduler aggregates small unused chunks of capacity across data centers and runs models on them, and it passes the steep discounts it gets from those data centers on to customers. That origin still shows in its OpenAI-compatible Batch API, which takes up to 1M requests per file with completion windows from 24 hours to 7 days and far higher headroom than synchronous limits.
Example models: open catalog models plus customer fine-tunes served on dedicated GPUs
Full Inference.net profileShould you choose Modal or Inference.net?
Modal
Choose Modal for
- Real-time endpoints for models you already have.
- Custom GPU code beyond LLM inference.
- Bursty workloads that scale to zero.
Inference.net
Choose Inference.net for
- Very large offline batch jobs at low cost.
- Turning production traces into a distilled model.
- One gateway key across open, closed and custom models.
Modal vs Inference.net at a glance
| Attribute | Modal | Inference.net |
|---|---|---|
| Model access | Bring your own weights | Open, closed and custom |
| Flagship models | None hosted | Customer fine-tunes |
| Speed | ~1s container boot | Batch windows of 24h to 7 days |
| Price | Per second; H100 $3.95/hr list | Discounted spare GPU capacity |
| Customization | Run any training code | Distill traces into custom models |
| Deployment | Serverless GPU containers | Batch API, gateway, dedicated GPUs |
| Long context | Depends on the model you deploy | Varies by model |
Frequently asked questions
What is the difference between Modal and Inference.net?
Inference.net sells cheap batch on spare GPU capacity and a path from traces to custom models. Modal sells per-second GPU containers for any code. Managed pipeline versus build-your-own.
When should I choose Modal over Inference.net?
Real-time endpoints for models you already have; Custom GPU code beyond LLM inference; Bursty workloads that scale to zero.
When should I choose Inference.net over Modal?
Very large offline batch jobs at low cost; Turning production traces into a distilled model; One gateway key across open, closed and custom models.
Is Modal or Inference.net cheaper?
Modal: Per second; H100 $3.95/hr list. Inference.net: Discounted spare GPU capacity. The cheaper choice depends on the model and workload.
Which has more context, Modal or Inference.net?
Modal: Depends on the model you deploy. Inference.net: Varies by model.
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