Nebius Token Factory is an inference API for open-weight language models, with fine-tuning and dedicated endpoints, from Nasdaq-listed Nebius. Billed per token.
Nebius Token Factory gives developers hosted access to open-weight model families such as DeepSeek, Qwen, Kimi, Nemotron, GLM and gpt-oss through one API. Requests follow the OpenAI format, so an existing app changes its base URL and key to switch over. Nebius Group N.V., the Amsterdam AI cloud company listed on Nasdaq, builds and runs it. Token Factory keeps its own site, sign-up, documentation and billing, apart from Nebius AI Cloud. The Model catalog shows each model's context window, licence, processing region and per-token rate. Inference covers serverless endpoints, dedicated endpoints on isolated GPUs, a Playground, Prompt presets and Observability. Calls can use functions, follow a supplied JSON schema, read images and set a reasoning effort, and separate endpoints return embeddings and rerank scores. Post-training runs supervised fine-tuning with LoRA or full weights, plus custom speculator training. Data Lab keeps datasets and chat completion logs for reuse, and Sandboxes give software-engineering agents isolated environments to work in. Token Factory suits developers and machine learning engineers who want open models in production without operating GPU clusters themselves. Startups usually begin on serverless endpoints, paying per token at a rate set for each model, with input and output counted separately. Teams that need predictable latency, isolation or a fixed region move to dedicated endpoints, charged while their replicas run. Larger companies sign an Enterprise agreement through sales for higher rate limits and reserved GPU capacity. Typical jobs are chat and coding assistants, retrieval over company documents, and pulling structured fields out of text and screenshots. A team can keep the OpenAI SDK it already uses and wire retrieval through LangChain against the same endpoint. Each catalog model links to its weights on Hugging Face, so a model tried here stays portable to other hosts. Coding teams pair Sandboxes with Mini-SWE-Agent when an agent needs its own place to run code. Token Factory fits teams that choose a model per task and expect to fine-tune it or move it to dedicated capacity later.
Pricing
View plans-
Serverless pay-as-you-go
Custom pricing
- From $0.06 per 1M input tokens, usage billing in USD, input and output priced per model, card debited in real time
- From $0.06 input and $0.24 output per 1M tokens on Nemotron-3-Nano-30B-A3B and Nemotron-3.5-Lightning
- DeepSeek-V4-Flash-0731 at $0.14 input and $0.28 output; gpt-oss-120b at $0.15 and $0.60
- Qwen3-235B-A22B-Instruct-2507 at $0.20 input and $0.60 output; GLM-5.3 at $1.40 and $4.40
- Kimi-K3 at $3.00 input and $15.00 output per 1M tokens, the highest listed rate
- Qwen3-Embedding-8B embeddings at $0.01 per 1M input tokens
- $1 trial credit on first sign-up, valid 30 days; a bank card is required at sign-up
- 25 public models: 18 text, 6 vision and 1 embedding
- Processing region is Global and can change without notice; a fixed region needs a dedicated endpoint
- Rate limits start at a default cap and rise 20% when usage stays at 80% or more of it; HTTP 429 above the limit
- Serverless models retire on set dates with no automatic rerouting
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Dedicated endpoints
Custom pricing
- Billed while at least one replica runs; rate per replica set in the account or by contract
- Isolated GPU deployment in a region you choose, with GPU type, replica count and autoscaling
- No formal SLA on self-service dedicated endpoints unless a contract covers it
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Enterprise tier
Custom pricing
- Sold through sales on contract
- Higher rate limits than the self-service default
- Reserved dedicated GPU capacity
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Post-training
Custom pricing
- Supervised fine-tuning and custom speculator training, billed per token for text-to-text models
- LoRA and full fine-tuning on supported open models
Features
- Included: Published context window size
- Included: Image input support
- Not included: Audio input support
- Included: Function and tool calling
- Included: JSON schema output mode
- Included: Extended reasoning mode
- Not included: Prompt caching discount
- Not included: Batch inference API
- Included: Fine-tuning offered
- Included: Open weights release
- Included: Zero data retention option
- Included: Regional data residency
- Not included: Published safety evaluations
- Included: Free tier or trial credits
- Included: Enterprise agreement available
- Not included: Published deprecation policy
- Not included: Published benchmark results
- Included: Embeddings endpoint
Additional Features
- Serverless endpoints for open-weight models
- Dedicated endpoints on isolated GPUs with autoscaling replicas
- OpenAI-compatible chat completions API
- Model catalog with context window, licence and region per model
- Playground for trying models
- Prompt presets
- Inference Observability with API integrations
- Supervised fine-tuning with LoRA or full weights
Best for
- Developers moving an app from a closed model API to open-weight models
- Teams that fine-tune an open model and serve it from the same account
- Startups prototyping on pay-as-you-go endpoints before reserving capacity
- Production workloads that need a fixed region and isolated GPUs
- Companies that want chat completion logs kept out of storage
- Teams building coding agents that need isolated execution environments
- Enterprises buying reserved GPU capacity and higher rate limits on contract
- Text, image-understanding and embedding workloads
Use cases
- Serving a chat assistant on an open-weight model
- Powering a coding assistant
- Retrieval over company documents with embeddings and rerank
- Fine-tuning a model on company data, then deploying it
- Extracting structured JSON from documents
- Letting a model call internal tools and APIs
- Reading screenshots and images with vision models
- Running software-engineering agents in Sandboxes
- Pointing an existing OpenAI SDK app at open models
- Comparing models in the Playground before choosing one
- Watching inference traffic through observability integrations
Screenshots & Videos
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