What DeepInfra does
DeepInfra is a hosted inference platform for text generation, embeddings, reranking, speech, image, and other models through native and OpenAI-compatible APIs.
DeepInfra provides one account and API surface for a broad catalog of open and specialized models. That is useful for comparing text generators, embeddings, rerankers, speech, and image systems without operating GPUs. Model cards and the models API expose capability and pricing details, but request formats, context, quantization, and reliability still vary by model.
There is no honest universal price. Each model publishes its own unit, such as input and output tokens, characters, images, seconds, or deployment uptime. Dedicated endpoints, fine-tuning or custom deployments, storage, minimums, retries, and changed model rates can affect the bill. Use the current model page and returned usage data to estimate a production-shaped workload.
A hosted API sends data beyond the application boundary. Review the current privacy policy, terms, retention, region, subprocessors, and enterprise controls for the exact service; avoid secrets and unnecessary personal data. Open-model licenses and safety behavior differ, and a catalog entry can be replaced or deprecated. Pin identifiers, monitor notices, rate-limit requests, test abuse and quality, and keep a fallback before relying on a model.
How DeepInfra works
An application authenticates to DeepInfra, selects a published model ID, and sends text, images, audio, or other supported inputs through the matching API. Shared serverless infrastructure loads or routes the model, performs inference, and returns generated output, vectors, scores, media, and usage metadata; OpenAI-compatible endpoints simplify some text integrations. Dedicated deployments reserve capacity for selected models. DeepInfra operates inference, while the application remains responsible for model licensing, prompt construction, safety controls, output validation, and human review.
How to set up DeepInfra
Select by task and license
Compare current model cards for modality, context, license, price, deprecation state, safety behavior, and regional or contractual requirements.
Create scoped credentials
Keep the token in a server-side secret manager, separate development and production, and set budgets, alerts, and request limits where available.
Integrate one endpoint
Use the native or OpenAI-compatible API, pin the model ID, validate input size and output structure, and implement timeouts and retry backoff.
Evaluate representative traffic
Measure quality, factuality, latency, availability and complete cost across typical, long, multilingual, adversarial, and failure cases.
Release with governance
Minimize transmitted data, log safely, monitor usage and model changes, filter abuse, provide fallbacks, and route consequential outputs to qualified reviewers.
DeepInfra FAQs
How much does DeepInfra cost?
Pricing is model-specific and may use tokens, characters, images, time, or endpoint uptime. Check the current model page or models API for the selected workload.
Does DeepInfra support OpenAI-compatible requests?
Yes, for supported text and related endpoints. Model-specific parameters and behavior can differ, so test compatibility rather than assuming an exact replacement.
Does DeepInfra include open-source models?
Its catalog includes many open models, but each model has its own license, acceptable-use conditions, context, quantization, and limitations.
Can I reserve a model deployment?
DeepInfra offers dedicated deployment options for supported models. Hardware, uptime, capacity, regions, and contract terms determine price and availability.
Are outputs guaranteed accurate?
No. Hosted inference runs the selected model; it does not guarantee factuality, safety, fairness, rights clearance, or fitness for a consequential decision.
Listing reviewed 2026-08-02. Product details and pricing can change; verify important terms on the provider's website.
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