x402.orthogonal.com
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.
Offering
- Provider
- x402.orthogonal.com
- Method
- POST
- Offering type
- Api Endpoint
- Transport type
- http
- Category
- Api
- Delivery
- Not provided
- Pricing model
- Not provided
- x402 version
- 2
Endpoint context
- URL
https://x402.orthogonal.com/baseten/v1/chat/completions- MIME type
- Not provided
- First seen
- 2026-10-16T01:58:48.885Z
- Last seen
- Tags
- None supplied
Payment pricing
x402 payment terms are the authoritative price for calling this endpoint.
- Payment option 1
- 0.005 USDC
Atomic price: 5000 · Network: eip155:8453 · Asset: USDC · Scheme: exact - Payment option 2
- 5000 atomic units
Atomic price: 5000 · Network: eip155:8453 · Asset: 0xB2000000000000000000002fEb517dFeC7415344 · Scheme: exact - Payment option 3
- 0.005 USDC
Atomic price: 5000 · Network: solana:5eykt4UsFv8P8NJdTREpY1vzqKqZKvdp · Asset: USDC · Scheme: exact - Payment option 4
- 0.005 USDC
Atomic price: 5000 · Network: eip155:143 · Asset: USDC · Scheme: exact
Raw x402 terms
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"asset": "0x754704Bc059F8C67012fEd69BC8A327a5aafb603",
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]Observed health
- Status
- Healthy
- Latest latency
- 62 ms
- Average latency
- 533 ms
- HTTP status
- 204
- Last checked
- Reachability
- 100% over 12 checks
Latency is measured to the first response headers. A reachable result does not verify response accuracy or merchant identity.
Input schema
{
"additionalProperties": false,
"properties": {
"body": {
"properties": {
"add_generation_prompt": {
"description": "If true, applies the model's generation prompt template. Usually needed for chat models.",
"type": "boolean"
},
"add_special_tokens": {
"description": "If true, adds special tokens (like BOS) to the input. Default: true.",
"type": "boolean"
},
"bad": {
"description": "Words or phrases the model should avoid generating. Passed as a string.",
"type": "string"
},
"bad_token_ids": {
"description": "Array of token IDs that should never appear in the output.",
"type": "array"
},
"best_of": {
"description": "Number of candidate completions to generate server-side, returning the best. Currently only supports 1.",
"type": "number"
},
"chat_template": {
"description": "Custom Jinja2 template for formatting the conversation. Overrides the model's default chat template.",
"type": "string"
},
"chat_template_args": {
"description": "Additional arguments passed to the chat template as template variables.",
"type": "object"
},
"disaggregated_params": {
"description": "Advanced parameters for distributed inference. Only relevant for disaggregated serving configurations.",
"type": "object"
},
"documents": {
"description": "Array of document objects for retrieval-augmented generation (RAG). Each document has content the model can reference when responding.",
"type": "array"
},
"early_stopping": {
"description": "In beam search, stop as soon as the required number of complete candidates are found.",
"type": "boolean"
},
"echo": {
"description": "If true, prepends the last input message to the generated output.",
"type": "boolean"
},
"frequency_penalty": {
"description": "Penalize tokens based on how often they've appeared so far. Range -2.0 to 2.0. Positive values reduce repetition. Default: 0.",
"type": "number"
},
"ignore_eos": {
"description": "If true, the model continues generating past the end-of-sequence token.",
"type": "boolean"
},
"include_stop_str_in_output": {
"description": "If true, includes the stop string in the generated output rather than trimming it.",
"type": "boolean"
},
"length_penalty": {
"description": "Penalty applied during beam search. Values > 1.0 favor longer sequences, < 1.0 favor shorter ones.",
"type": "number"
},
"logit_bias": {
"description": "Map of token IDs to bias values (-100 to 100). Increase or decrease the likelihood of specific tokens appearing in the output.",
"type": "object"
},
"logprobs": {
"description": "If true, returns the log probabilities of each output token in the response.",
"type": "boolean"
},
"max_tokens": {
"description": "Maximum number of tokens to generate in the response. Default is 4096.",
"type": "number"
},
"messages": {
"description": "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.",
"type": "array"
},
"min_p": {
"description": "Minimum probability threshold. Tokens below this probability relative to the most likely token are filtered out.",
"type": "number"
},
"min_tokens": {
"description": "Minimum number of tokens to generate before any stop condition can trigger.",
"type": "number"
},
"model": {
"description": "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.",
"type": "string"
},
"n": {
"description": "Number of completions to generate. Currently only supports 1.",
"type": "number"
},
"parallel_tool_calls": {
"description": "Whether the model can make multiple tool calls in parallel in a single response. Default: true.",
"type": "boolean"
},
"presence_penalty": {
"description": "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.",
"type": "number"
},
"reasoning_effort": {
"description": "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.",
"type": "string"
},
"repetition_penalty": {
"description": "Multiplicative penalty for repeated tokens. Values > 1.0 discourage repetition, < 1.0 encourage it.",
"type": "number"
},
"response_format": {
"description": "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.",
"type": "object"
},
"seed": {
"description": "Integer for deterministic sampling. Same seed with same parameters should return the same result. Not guaranteed across model versions.",
"type": "number"
},
"skip_special_tokens": {
"description": "If true, special tokens are removed from the output text. Default: true.",
"type": "boolean"
},
"spaces_between_special_tokens": {
"description": "If true, adds spaces between special tokens in the detokenized output.",
"type": "boolean"
},
"stop": {
"description": "Up to 4 sequences where the model will stop generating. Can be a string or array of strings.",
"type": "string"
},
"stop_token_ids": {
"description": "Array of token IDs that will cause generation to stop when produced.",
"type": "array"
},
"stream": {
"description": "If true, returns server-sent events (SSE) with partial message deltas as tokens are generated, instead of waiting for the full response.",
"type": "boolean"
},
"stream_options": {
"description": "Options for streaming. Use {\"include_usage\": true} to get a final chunk with token usage statistics.",
"type": "object"
},
"temperature": {
"description": "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.",
"type": "number"
},
"tool_choice": {
"description": "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.",
"type": "string"
},
"tools": {
"description": "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.",
"type": "array"
},
"top_k": {
"description": "Top-K sampling. Only the K most likely next tokens are considered. Lower values make output more focused.",
"type": "number"
},
"top_logprobs": {
"description": "How many of the most likely tokens (0-20) to return log probabilities for at each position. Requires logprobs to be true.",
"type": "number"
},
"top_p": {
"description": "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.",
"type": "number"
},
"top_p_min": {
"description": "Minimum dynamic nucleus sampling threshold. Sets a floor for top_p when using adaptive sampling.",
"type": "number"
},
"truncate_prompt_tokens": {
"description": "Truncate the prompt to this many tokens if it exceeds the limit, keeping the most recent tokens.",
"type": "number"
},
"user": {
"description": "A unique string identifying the end user. Useful for abuse monitoring and rate limiting.",
"type": "string"
}
},
"type": "object"
},
"bodyType": {
"enum": [
"json",
"form-data",
"text"
],
"type": "string"
},
"method": {
"enum": [
"POST"
],
"type": "string"
},
"type": {
"const": "http",
"type": "string"
}
},
"required": [
"type",
"method",
"bodyType",
"body"
],
"type": "object"
}Output schema
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"properties": {
"input": {
"additionalProperties": false,
"properties": {
"body": {
"properties": {
"add_generation_prompt": {
"description": "If true, applies the model's generation prompt template. Usually needed for chat models.",
"type": "boolean"
},
"add_special_tokens": {
"description": "If true, adds special tokens (like BOS) to the input. Default: true.",
"type": "boolean"
},
"bad": {
"description": "Words or phrases the model should avoid generating. Passed as a string.",
"type": "string"
},
"bad_token_ids": {
"description": "Array of token IDs that should never appear in the output.",
"type": "array"
},
"best_of": {
"description": "Number of candidate completions to generate server-side, returning the best. Currently only supports 1.",
"type": "number"
},
"chat_template": {
"description": "Custom Jinja2 template for formatting the conversation. Overrides the model's default chat template.",
"type": "string"
},
"chat_template_args": {
"description": "Additional arguments passed to the chat template as template variables.",
"type": "object"
},
"disaggregated_params": {
"description": "Advanced parameters for distributed inference. Only relevant for disaggregated serving configurations.",
"type": "object"
},
"documents": {
"description": "Array of document objects for retrieval-augmented generation (RAG). Each document has content the model can reference when responding.",
"type": "array"
},
"early_stopping": {
"description": "In beam search, stop as soon as the required number of complete candidates are found.",
"type": "boolean"
},
"echo": {
"description": "If true, prepends the last input message to the generated output.",
"type": "boolean"
},
"frequency_penalty": {
"description": "Penalize tokens based on how often they've appeared so far. Range -2.0 to 2.0. Positive values reduce repetition. Default: 0.",
"type": "number"
},
"ignore_eos": {
"description": "If true, the model continues generating past the end-of-sequence token.",
"type": "boolean"
},
"include_stop_str_in_output": {
"description": "If true, includes the stop string in the generated output rather than trimming it.",
"type": "boolean"
},
"length_penalty": {
"description": "Penalty applied during beam search. Values > 1.0 favor longer sequences, < 1.0 favor shorter ones.",
"type": "number"
},
"logit_bias": {
"description": "Map of token IDs to bias values (-100 to 100). Increase or decrease the likelihood of specific tokens appearing in the output.",
"type": "object"
},
"logprobs": {
"description": "If true, returns the log probabilities of each output token in the response.",
"type": "boolean"
},
"max_tokens": {
"description": "Maximum number of tokens to generate in the response. Default is 4096.",
"type": "number"
},
"messages": {
"description": "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.",
"type": "array"
},
"min_p": {
"description": "Minimum probability threshold. Tokens below this probability relative to the most likely token are filtered out.",
"type": "number"
},
"min_tokens": {
"description": "Minimum number of tokens to generate before any stop condition can trigger.",
"type": "number"
},
"model": {
"description": "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.",
"type": "string"
},
"n": {
"description": "Number of completions to generate. Currently only supports 1.",
"type": "number"
},
"parallel_tool_calls": {
"description": "Whether the model can make multiple tool calls in parallel in a single response. Default: true.",
"type": "boolean"
},
"presence_penalty": {
"description": "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.",
"type": "number"
},
"reasoning_effort": {
"description": "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.",
"type": "string"
},
"repetition_penalty": {
"description": "Multiplicative penalty for repeated tokens. Values > 1.0 discourage repetition, < 1.0 encourage it.",
"type": "number"
},
"response_format": {
"description": "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.",
"type": "object"
},
"seed": {
"description": "Integer for deterministic sampling. Same seed with same parameters should return the same result. Not guaranteed across model versions.",
"type": "number"
},
"skip_special_tokens": {
"description": "If true, special tokens are removed from the output text. Default: true.",
"type": "boolean"
},
"spaces_between_special_tokens": {
"description": "If true, adds spaces between special tokens in the detokenized output.",
"type": "boolean"
},
"stop": {
"description": "Up to 4 sequences where the model will stop generating. Can be a string or array of strings.",
"type": "string"
},
"stop_token_ids": {
"description": "Array of token IDs that will cause generation to stop when produced.",
"type": "array"
},
"stream": {
"description": "If true, returns server-sent events (SSE) with partial message deltas as tokens are generated, instead of waiting for the full response.",
"type": "boolean"
},
"stream_options": {
"description": "Options for streaming. Use {\"include_usage\": true} to get a final chunk with token usage statistics.",
"type": "object"
},
"temperature": {
"description": "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.",
"type": "number"
},
"tool_choice": {
"description": "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.",
"type": "string"
},
"tools": {
"description": "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.",
"type": "array"
},
"top_k": {
"description": "Top-K sampling. Only the K most likely next tokens are considered. Lower values make output more focused.",
"type": "number"
},
"top_logprobs": {
"description": "How many of the most likely tokens (0-20) to return log probabilities for at each position. Requires logprobs to be true.",
"type": "number"
},
"top_p": {
"description": "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.",
"type": "number"
},
"top_p_min": {
"description": "Minimum dynamic nucleus sampling threshold. Sets a floor for top_p when using adaptive sampling.",
"type": "number"
},
"truncate_prompt_tokens": {
"description": "Truncate the prompt to this many tokens if it exceeds the limit, keeping the most recent tokens.",
"type": "number"
},
"user": {
"description": "A unique string identifying the end user. Useful for abuse monitoring and rate limiting.",
"type": "string"
}
},
"type": "object"
},
"bodyType": {
"enum": [
"json",
"form-data",
"text"
],
"type": "string"
},
"method": {
"enum": [
"POST"
],
"type": "string"
},
"type": {
"const": "http",
"type": "string"
}
},
"required": [
"type",
"method",
"bodyType",
"body"
],
"type": "object"
}
},
"required": [
"input"
],
"type": "object"
}