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Nebius Token Factory

Nebius uses the OpenAI chat-completions dialect but exposes a richer model listing. AnyInfer uses that listing to discover current context windows, quantization, feature support, and prices instead of shipping a catalog that will age.

streaming structured output (model-dependent) tool calls (model-dependent) reasoning channel discovery (pricing + context)

Setup

import anyinfer as ai

client = ai.Client(
    [
        ai.ProviderSettings.of(
            "nebius",
            api_key="env://NEBIUS_API_KEY",
        ),
    ]
)

result = client.generate(
    "Explain why the sky appears blue.",
    target="nebius:deepseek-ai/DeepSeek-V3",
    reasoning="medium",
)

Model ids use the provider's namespaced catalog. A suffix such as -fast is part of the model id and selects a separately priced flavor; AnyInfer does not rewrite it.

Discovery

The adapter asks for the verbose model list, so client.models("nebius") reports each model's context window, pricing, quantization, and feature flags with discovered provenance. If an endpoint does not support the verbose query, the adapter falls back to the ordinary listing and returns model ids without inventing metadata.

Reasoning

Normalized reasoning levels are sent as reasoning_effort. Reasoning fragments are surfaced as ReasoningDelta events on the event stream and remain separate from Generation.text. The upstream API also accepts reasoning levels outside AnyInfer's normalized four-level scale; send those explicitly through provider_options when needed.

Wire Contract

For the exact fields this adapter sends and reads, see contracts/nebius.md.

See Also