DeepInfra
DeepInfra: low-cost, low-latency cloud inference API for 100+ open models
DeepInfra is the cheapest way to run the latest open models in production, period. DeepSeek-V4-Flash-0731 at $0.08/M input is unbeatable for high-volume, long-context workloads, and the zero-retention policy plus SOC 2/ISO 27001 certs ease compliance. The lack of fine-tuning and US-only data centers are real constraints, but for pure inference cost and breadth, it's a top pick.
Verified 8d ago · liveness 78/100 · cite: rightaichoice.com/tools/deepinfra
- Startups needing cheap, scalable LLM inference for production
- Developers building agentic workflows or RAG pipelines with long context
- Enterprises with strict privacy requirements (zero retention, SOC 2)
- Teams experimenting with the latest open models without managing GPUs
- Teams needing fine-tuning or model training (not supported)
- Organizations requiring data residency outside the US
- Users wanting a massive community model hub like Hugging Face
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Skip DeepInfra if you need fine-tuning or model training, require data residency outside the US, want access to every open-source model (catalog is curated), or need an integrated MLOps toolchain with CI/CD.
Some models are billed by execution time (not per token), so costs can spike for long-running inference tasks if you're not monitoring GPU usage.
DeepInfra's pay-as-you-go pricing fits startups and developers with variable workloads best. For high-volume inference, it's often cheaper than API providers like Together AI or Fireworks AI, and competitive with GPU clouds for managed inference. For enterprises, custom contracts and support are available, but the value is strongest for those who can take advantage of cached input discounts.
In short
DeepInfra — DeepInfra: low-cost, low-latency cloud inference API for 100+ open models. Best for Startups needing cheap, scalable LLM inference for production, Developers building agentic workflows or RAG pipelines with long context, Enterprises with strict privacy requirements (zero retention, SOC 2). Free to use.
What's new in DeepInfra
Checked 5 days agoAcross the latest 2 updates: 2 feature updates.
NVIDIA Nemotron 3.5 Lightning Is Live on DeepInfra
Day-zero access to Nemotron 3.5 Lightning, a 30B hybrid MoE with 3B active and 1M context, claiming 4x throughput.
Kimi K3 Now Available on DeepInfra
Moonshot AI's 2.8T-parameter open-weight multimodal model now available on DeepInfra with 1M-token context.
Viability Score
How well maintained and how widely used is DeepInfra? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: September 2026
How we score →Key Features
- 100+ open and proprietary models via a single API
- OpenAI SDK-compatible API
- Anthropic SDK support
- Per-token pricing for language models
- Execution-time billing for non-text models
- Cached input pricing (up to 80% discount)
- Up to 1M-token context windows on flagship models
- Vision & OCR with Qwen-VL, Step 3.7 Flash
- Embeddings and reranker models for RAG
- Text-to-image generation (FLUX, Stable Diffusion)
- Text-to-video generation
- Text-to-speech and speech recognition (Whisper)
- World model inference (NVIDIA Cosmos)
- Zero data retention policy
- SOC 2 and ISO 27001 certified
About DeepInfra
DeepInfra is a cloud inference platform that gives developers a single, low-cost API to run 100+ open and proprietary AI models. It covers text generation, embeddings, rerankers, automatic speech recognition, text-to-speech, text-to-image, text-to-music, text-to-video, and world models for physical AI. The platform is built for startups, enterprises, and researchers who need production-grade inference without long-term contracts or per-seat commitments. With pay-as-you-go pricing — per-token for language models and execution-time billing for most other models — you only pay for what you actually use. DeepInfra runs its own inference-optimized hardware in US-based data centers, delivering low-latency performance and high throughput. A standout value is DeepSeek-V4-Flash-0731 at $0.08 per 1M input tokens (or $0.016 per 1M cached), a price that undercuts most rivals for high-volume, long-context workloads. Cached input tokens get deep discounts on eligible models, cutting costs for repeated calls. The platform also supports up to 1M-token context windows on flagship models like DeepSeek-V4, GLM-5.2, Kimi-K3, and NVIDIA Nemotron 3 Ultra. DeepInfra is SOC 2 and ISO 27001 certified with a strict zero-data-retention policy, so your inputs, outputs, and user data stay private. The catalog keeps growing: recent additions include NVIDIA Nemotron 3.5 Lightning (30B hybrid MoE, 3B active, 1M context), Kimi K3 (2.8T-parameter multimodal reasoning), and DeepSeek-V4-Pro-0813 with enhanced agentic capabilities. All models are accessible via OpenAI SDK-compatible and Anthropic SDK-compatible APIs, plus integrations with LangChain, LlamaIndex, and more. Backed by a $107M Series B (May 2026) co-led by 500 Global and Georges Harik, with NVIDIA participating, DeepInfra is scaling to handle trillions of tokens. Compared to generic GPU cloud rentals or other inference APIs, DeepInfra offers a fully managed experience with a broad model catalog, simple APIs, and hands-on technical
Behind the Verdict
DeepInfra is the price leader in cloud inference, and that's its whole game. If you're shipping an agentic coding tool, a RAG pipeline, or any high-volume LLM workload, the per-token costs here are hard to beat. DeepSeek-V4-Flash-0731 at $0.08/M input and $0.18/M output is the headline, but even the bigger models like DeepSeek-V4-Pro at $1.30/$2.60 and Kimi-K3 at $2.85/$14.25 are discounted against most rivals. Cached input pricing — as low as $0.016/M on Flash — makes repeated, multi-turn calls dramatically cheaper. Where DeepInfra shines is speed-to-production. You get a single API that's OpenAI SDK-compatible, so swapping from OpenAI or any other provider is a matter of changing a base URL. Add the Anthropic SDK support, and your existing agent frameworks work with minimal changes. The model catalog is enormous — 100+ options across text, vision, speech, image, video, and even world models like NVIDIA Cosmos — so you're rarely forced to use a model you don't want. But it's not for everyone. There's no fine-tuning or training; this is pure inference. If you need to customize a model on your own data, you'll need a different platform or to rent GPUs elsewhere (DeepInfra does rent DGX B300s at $4.89/instance-hour, but that's raw hardware). Data residency is US-only, which rules out EU or APAC compliance scenarios. And while the catalog is broad, it's not a community hub — you won't find niche or community-hosted models like on Hugging Face. Compared to the closest alternative, Together AI, DeepInfra often edges it on price for the same open models, and the zero-retention policy is a privacy plus. Fireworks AI is another competitor, but DeepInfra's token throughput and caching discounts make it a stronger pick for cost-obsessed teams. For deep research, agentic
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Real-world workflow fit
Concrete scenarios for the personas DeepInfra actually fits — and what changes day-one when you adopt it.
You want to prototype a chatbot using an open-source model like DeepSeek without managing GPUs.
Outcome: You sign up, get an API key, and point your OpenAI SDK to DeepInfra's base URL. Within minutes you're making calls to DeepSeek-V4-Flash at $0.08/M input, and you can stream responses easily. You only pay for tokens used, so the cost stays low during development.
Your startup needs to build a search and retrieval system over private documents, requiring embeddings and rerankers.
Outcome: You use DeepInfra's embedding models and rerankers to index and query your documents. The zero-retention policy assures your data stays private, and cached input discounts help reduce costs for repeated queries. The OpenAI-compatible API integrates easily with LangChain or LlamaIndex, getting you to production fast.
Use Cases
- Build a chatbot using any open-source LLM via drop-in OpenAI SDK
- Run vision and OCR on documents with Qwen3-VL or Gemini models
- Deploy a custom fine-tuned LLM on a private GPU instance with autoscaling
- Generate images at scale using FLUX or Stable Diffusion APIs
- Create a RAG pipeline using embeddings and reranker models
- Power multi-agent systems with low-cost MoE models like Nemotron 3 Super
Models Under the Hood
as of 2026-08-30
Limitations
- DeepInfra is a cloud inference API platform, not a training service, so fine-tuning and model training are not offered.
- Pricing varies by model: language models are typically billed per token, while other models are billed by execution time.
- Some models offer cached input discounts and context windows up to 1024k, but availability and pricing may change over time.
- The platform focuses on open-source model hosting, and the catalog is curated to supported models.
as of 2026-08-24
Verification history
We have re-verified DeepInfra 17 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
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Showing the 6 most recent of 17 verification passes.
Free to cite with attribution — this page re-verifies continuously.
Where the pricing makes sense
The company stage and team size where DeepInfra's pricing actually pencils out — and where peers do it cheaper.
DeepInfra's pay-as-you-go pricing fits startups and developers with variable workloads best. For high-volume inference, it's often cheaper than API providers like Together AI or Fireworks AI, and competitive with GPU clouds for managed inference. For enterprises, custom contracts and support are available, but the value is strongest for those who can take advantage of cached input discounts.
Setup time & first value
How long it actually takes to get something useful out of DeepInfra — broken out by persona, not the marketing-page minute.
For a developer already familiar with OpenAI SDK, you can be making your first API call in under 5 minutes: sign up, get an API key, and change the base URL. For a full RAG pipeline or private deployment, expect a few hours to integrate and tune. GPU cluster rental may take a day to set up and configure.
Switching to or from DeepInfra
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From OpenAI: Change your base_url to https://api.deepinfra.com/v1/openai and your API key; your code works without changes.
- ↗To another OpenAI-compatible provider: Change your base_url and API key to the new provider's endpoint; your code should remain compatible.
Integrations
Resources & Guides
- Documentationdeepinfra.com
What is DeepInfra
AI inference cloud — OpenAI-compatible API, 100s of open-source models, private GPU deployments, and GPU rental.
- Resourcedeepinfra.com
Blog | Fast & Reliable AI Inference
Discover the latest machine learning models and infrastructure! Learn how to enhance your AI applications, and more!
- Quickstartdeepinfra.com
What is DeepInfra
AI inference cloud — OpenAI-compatible API, 100s of open-source models, private GPU deployments, and GPU rental.
- Documentationdeepinfra.com
What is DeepInfra
AI inference cloud — OpenAI-compatible API, 100s of open-source models, private GPU deployments, and GPU rental.
- Documentationdeepinfra.com
What is DeepInfra
AI inference cloud — OpenAI-compatible API, 100s of open-source models, private GPU deployments, and GPU rental.
- Documentationdeepinfra.com
What is DeepInfra
AI inference cloud — OpenAI-compatible API, 100s of open-source models, private GPU deployments, and GPU rental.
- Documentationdeepinfra.com
What is DeepInfra
AI inference cloud — OpenAI-compatible API, 100s of open-source models, private GPU deployments, and GPU rental.
- Documentationdeepinfra.com
What is DeepInfra
AI inference cloud — OpenAI-compatible API, 100s of open-source models, private GPU deployments, and GPU rental.
- Documentationdeepinfra.com
GPU Instances
Rent dedicated B200 GPU instances with SSH access for training, fine-tuning, and custom workloads.
- Documentationdeepinfra.com
Anthropic SDK & Claude Code
Use DeepInfra models with the Anthropic Messages API, Claude Code, and the Anthropic SDK.
Tutorials & Learning
Official links
Tools that pair well with DeepInfra
Common stack mates teams adopt alongside DeepInfra, with the specific reason each pairing earns its keep.
Alternatives to DeepInfra
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