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x402.orth.sh Baseten Chat Completions
x402
x402.orth.sh Baseten Chat Completions is a paid API for AI agents from x402.orth.sh, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-12).
Send a conversation to a large language model and receive a text completion, with support for streaming, tool calling, structured outputs, and reasoning depth control.
Price / call$0.005
Success—
StatusUnknown
How this service works
Send a conversation to a model and get a completion back. Works exactly like the OpenAI chat completions endpoint. Pass messages and a model slug, get a response with the assistant's reply. Supports streaming for real-time token delivery, tool calling for function execution, structured outputs via response_format, and controllable reasoning depth on supported models. | ERROR: Unable to calculate price.
Output
Returns an OpenAI-compatible chat completion object containing one or more choices, each with a message (role: assistant, content: string), optional tool_calls for function invocations, finish_reason, and usage statistics (prompt tokens, completion tokens, total tokens). When streaming is enabled, returns server-sent events with delta chunks.
Example use cases
Reasoning over complex technical question
“I need you to think deeply about this architecture decision: send this message thread to the Kimi-K2-Thinking model with high reasoning effort and tell me which microservices design pattern best fits our use case based on our requirements.”
Structured JSON extraction from text
“Run this customer feedback through the GLM-4.7 model and return the result as structured JSON with fields for sentiment, key topics, and a summary — use response_format to enforce the schema.”
Agentic tool-calling loop
“Send this conversation to DeepSeek-V3.1 with my search tool definition attached, so the model can decide when to call it; give me back whatever the model replies including any tool_calls it makes.”
Technical details
Endpoint
POSThttps://x402.orth.sh/baseten/v1/chat/completions?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need access to models not available on OpenAI directly (DeepSeek, GLM, Kimi families) via a drop-in OpenAI-compatible interface, or when you want pay-per-call micropayment billing via the x402 protocol rather than a subscription. Especially useful when you need long-context reasoning models (up to 262k tokens) or controllable reasoning depth, and want to avoid vendor lock-in.
Side effects
- Unsupported model slug returns an error or empty response
- Exceeding the model's context window (e.g. 128k or 262k tokens) causes truncation or rejection
- Tool definition schema errors cause tool_calls to fail or be ignored
- Payment failure or x402 protocol error blocks the request before inference
- Rate limiting or quota exhaustion returns a 429 or equivalent error
- Structured output (response_format) incompatible with chosen model returns unformatted text
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| n | number | Number of completions to generate. Currently only supports 1. |
| bad | string | Words or phrases the model should avoid generating. Passed as a string. |
| echo | boolean | If true, prepends the last input message to the generated output. |
| seed | number | Integer for deterministic sampling. Same seed with same parameters should return the same result. Not guaranteed across model versions. |
| stop | string | Up to 4 sequences where the model will stop generating. Can be a string or array of strings. |
| user | string | A unique string identifying the end user. Useful for abuse monitoring and rate limiting. |
| min_p | number | Minimum probability threshold. Tokens below this probability relative to the most likely token are filtered out. |
| model | string | Model slug to run inference against. Available models: deepseek-ai/DeepSeek-V3-0324 (164k context, reasoning), deepseek-ai/DeepSeek-V3.1 (164k context, reasoning), zai-org/GLM-4.6 (200k context, reasoning), zai-org/GLM-4.7 (200k context, reasoning), moonshotai/Kimi-K2-Instruct-0905 (128k context), moonshotai/Kimi-K2-Thinking (262k context, always-on reasoning), moonshotai/Kimi-K2.5 (262k context), openai/gpt-oss-120b (128k context). Reasoning models support the reasoning_effort parameter for controlling thinking depth. |
| tools | array | Array of tool/function definitions the model can call. Each tool has {"type": "function", "function": {"name": "...", "description": "...", "parameters": {...}}}. The model may respond with tool_calls instead of content. |
| top_k | number | Top-K sampling. Only the K most likely next tokens are considered. Lower values make output more focused. |
| top_p | number | Nucleus sampling threshold between 0 and 1. Only tokens within this cumulative probability mass are considered. 0.1 means only the top 10%. Use as an alternative to temperature. |
| stream | boolean | If true, returns server-sent events (SSE) with partial message deltas as tokens are generated, instead of waiting for the full response. |
| best_of | number | Number of candidate completions to generate server-side, returning the best. Currently only supports 1. |
| logprobs | boolean | If true, returns the log probabilities of each output token in the response. |
| messages | array | Array of message objects, each with a 'role' (system, user, assistant, tool) and 'content' (string or array of content parts). This is the conversation history sent to the model. |
| documents | array | Array of document objects for retrieval-augmented generation (RAG). Each document has content the model can reference when responding. |
| top_p_min | number | Minimum dynamic nucleus sampling threshold. Sets a floor for top_p when using adaptive sampling. |
| ignore_eos | boolean | If true, the model continues generating past the end-of-sequence token. |
| logit_bias | object | Map of token IDs to bias values (-100 to 100). Increase or decrease the likelihood of specific tokens appearing in the output. |
| max_tokens | number | Maximum number of tokens to generate in the response. Default is 4096. |
| min_tokens | number | Minimum number of tokens to generate before any stop condition can trigger. |
| temperature | number | Sampling temperature between 0 and 4. Lower values (e.g. 0.2) produce more focused, deterministic output. Higher values (e.g. 1.5) increase creativity. Default is 1. |
| tool_choice | string | Controls tool calling behavior. 'auto' lets the model decide, 'none' disables tools, 'required' forces a tool call, or pass {"type": "function", "function": {"name": "..."}} to force a specific tool. |
| top_logprobs | number | How many of the most likely tokens (0-20) to return log probabilities for at each position. Requires logprobs to be true. |
| bad_token_ids | array | Array of token IDs that should never appear in the output. |
| chat_template | string | Custom Jinja2 template for formatting the conversation. Overrides the model's default chat template. |
| early_stopping | boolean | In beam search, stop as soon as the required number of complete candidates are found. |
| length_penalty | number | Penalty applied during beam search. Values > 1.0 favor longer sequences, < 1.0 favor shorter ones. |
| stop_token_ids | array | Array of token IDs that will cause generation to stop when produced. |
| stream_options | object | Options for streaming. Use {"include_usage": true} to get a final chunk with token usage statistics. |
| response_format | object | Constrain the output format. Use {"type": "json_object"} for JSON mode, or {"type": "json_schema", "json_schema": {"name": "...", "schema": {...}}} for structured outputs with a specific schema. |
| presence_penalty | number | Penalize tokens based on whether they've appeared at all. Range -2.0 to 2.0. Positive values encourage the model to explore new topics. Default: 0. |
| reasoning_effort | string | Controls thinking depth for reasoning models. Options: 'low', 'medium', 'high'. Default: 'medium'. Higher effort uses more tokens but produces more thorough reasoning. Supported on DeepSeek V3/V3.1, GLM 4.6/4.7, and Kimi K2 Thinking. |
| frequency_penalty | number | Penalize tokens based on how often they've appeared so far. Range -2.0 to 2.0. Positive values reduce repetition. Default: 0. |
| add_special_tokens | boolean | If true, adds special tokens (like BOS) to the input. Default: true. |
| chat_template_args | object | Additional arguments passed to the chat template as template variables. |
| repetition_penalty | number | Multiplicative penalty for repeated tokens. Values > 1.0 discourage repetition, < 1.0 encourage it. |
| parallel_tool_calls | boolean | Whether the model can make multiple tool calls in parallel in a single response. Default: true. |
| skip_special_tokens | boolean | If true, special tokens are removed from the output text. Default: true. |
| disaggregated_params | object | Advanced parameters for distributed inference. Only relevant for disaggregated serving configurations. |
| add_generation_prompt | boolean | If true, applies the model's generation prompt template. Usually needed for chat models. |
| truncate_prompt_tokens | number | Truncate the prompt to this many tokens if it exceeds the limit, keeping the most recent tokens. |
| include_stop_str_in_output | boolean | If true, includes the stop string in the generated output rather than trimming it. |
| spaces_between_special_tokens | boolean | If true, adds spaces between special tokens in the detokenized output. |
Tags
x402
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