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DeepInfra is a hosted inference provider with broad model access and usage-based pricing. Replacing it can mean switching to another hosted API, running models locally or managing GPU infrastructure yourself. The right fit depends on more than a model’s input and output rates: routing, cache pricing, model limits and tool behavior can affect production cost and reliability. We’d compare providers against the exact models and request patterns in your application, then verify limits and migration requirements before moving traffic.
01Why people leave DeepInfra
Cache costs can change the bill
One OpenRouter thread reported higher costs after autorouting selected DeepInfra; the provider said it corrected a pricing typo. Check cache rates and routing before switching.
Routing affects repeatability
Commenters recommended limiting provider choice to protect cache hits. If consistent routing matters, check whether you can select or exclude providers.
Endpoint behavior can differ
A Reddit comparison reported different agent and tool behavior across DeepSeek endpoints. Test your harness and configuration as well as the model.
02The alternatives, ranked by fit
- OpenAI-compatible inference
GroqCloudGroqCloudGroqCloud is a hosted inference API with OpenAI compatibility, making it a candidate if you want to keep an OpenAI-style integration rather than move to GPU operations. The service has a free plan, but model limits and usage costs affect production fit. Verify the specific model and API features your code depends on before routing traffic.
Trade-off: Model availability, limits and usage costs shape fit; compatibility does not guarantee identical behavior.
7.5/10from
Freefree plan - Local inference
OllamaOllamaOllama is an open-source, self-hostable model runtime with an API for local inference. It fits privacy-sensitive, offline and prototyping workflows where you want to run open-weight models without depending on a hosted inference provider. You take on runtime and hardware operations, and the runtime offers less low-level control than some developers need.
Trade-off: You manage deployment and hardware, with less low-level control than some runtimes offer.
7.6/10from
$16.67/mofree plan - Custom GPU deployments
RunpodRunpodRunpod offers on-demand GPU capacity and custom containers, so teams can control more of their inference environment than with a hosted model API. Its listed starting price is $0.27, and it publishes hourly rates. Compare the full workload cost and plan for production reliability; this route also means owning more deployment work.
Trade-off: More deployment control means more operational responsibility and reliability checks.
7.2/10from
$0.27/mo - Open-model serving
Together AITogether AITogether AI targets teams serving open models, running batch inference or needing GPU capacity. It has a free plan, but the provider’s model pricing and capacity terms matter when estimating production spend. It is a fit to evaluate when you want hosted infrastructure for open models; check API compatibility and portability before moving an integration.
Trade-off: Confirm model pricing, capacity terms and portability before committing.
7.4/10from
Freefree plan - Multimodal inference
SiliconFlowSiliconFlowSiliconFlow is a hosted, pay-per-use API for model choice and multimodal inference, with OpenAI-compatible APIs. That gives teams an option to evaluate without shifting directly to self-managed GPUs. Check the models and request features your application uses, then compare actual usage costs; operational details still need vendor confirmation.
Trade-off: Confirm operational details and model-specific costs before production use.
7.4/10from
Custom - Low-latency inference
Cerebras InferenceCerebras InferenceCerebras Inference offers an OpenAI API-compatible path for teams prioritizing low-latency inference, with in-region deployment among its target use cases. It is worth evaluating if latency or deployment location is a reason to leave. Confirm production pricing and limits with the vendor, and validate that the API supports your application’s request patterns.
Trade-off: Production cost and limits need vendor confirmation.
6.4/10from
Custom - Model experimentation
ReplicateReplicateReplicate provides a hosted API for trying multiple models and deploying custom models, which suits prototypes or applications with variable inference demand. It has a free plan, but costs depend on each model and run, so a single headline rate will not estimate your bill. Compare the models and usage patterns you expect in production.
Trade-off: Costs vary by model and run; check each model’s pricing.
6.9/10from
Freefree plan
03Side by side
| Tool | Score | From | Free plan | Best for |
|---|---|---|---|---|
 DeepInfra DeepInfra (current) | 7.4 | Custom | No | Teams comparing hosted models |
| GroqCloud GroqCloud | 7.5 | Free | Yes | OpenAI-compatible inference integrations |
| Ollama Ollama | 7.6 | $16.67/mo | Yes | Developers building local inference into apps |
| Runpod Runpod | 7.2 | $0.27/mo | No | Teams needing on-demand GPU capacity |
| Together AI Together AI | 7.4 | Free | Yes | Teams serving open models |
| SiliconFlow SiliconFlow | 7.4 | Custom | No | Teams comparing hosted model providers |
| Cerebras Inference Cerebras Inference | 6.4 | Custom | No | Teams prioritizing low-latency inference |
| Replicate Replicate | 6.9 | Free | Yes | Teams prototyping with multiple models |
Questions people ask
Which DeepInfra alternative is cheapest?
There is no reliable winner without comparing the models and request patterns you use. Include input, output and cache pricing, as well as routing behavior, in the estimate. Runpod lists a starting price of $0.27, but GPU infrastructure is a different cost model from per-use hosted inference.
Can I switch to another OpenAI-compatible API?
GroqCloud, SiliconFlow and Cerebras Inference are described as OpenAI-compatible. That can provide a familiar integration shape, but it does not establish that every model, request feature or response behaves identically. Check the target API’s supported models and validate your application’s tool use and other required features.
Which alternatives can I self-host?
Ollama is open source and self-hostable, and its local runtime and API suit local inference workflows. Runpod supports custom containers, while SaladCloud is also listed as self-hostable. These options shift more deployment and operations work to your team than using a hosted inference API.