{"uid":"cap_H-NQDk3uF4RUvNO8CHeyb","slug":"deepseek-chat-bb22b2ff","name":"DeepSeek Chat (V3 / R1)","description":"Create a chat completion using DeepSeek V4 Flash or V4 Pro, with optional thinking mode. OpenAI-compatible request/response format.","url":"https://deepseek.mpp.paywithlocus.com/deepseek/chat?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","required":["model","messages","max_tokens"],"properties":{"stop":{"type":"string","description":"Stop sequence(s) — string or array of strings."},"model":{"type":"string","description":"Metered x402 model: deepseek-v4-flash or deepseek-v4-pro"},"top_p":{"type":"number","description":"Nucleus sampling parameter. Default: 1."},"stream":{"type":"boolean","description":"Streaming is not currently supported through public x402. Omit or use false."},"messages":{"type":"array","items":{"type":"object","required":["role"],"properties":{"name":{"type":"string"},"role":{"type":"string"},"content":{"anyOf":[{"type":"string"},{"type":"array","items":{"type":"object","required":["type"],"properties":{"text":{"type":"string"},"type":{"type":"string"},"image_url":{"type":"object","required":["url"],"properties":{"url":{"type":"string"}},"additionalProperties":true}},"additionalProperties":true}},{"type":"null"}]},"tool_calls":{"type":"array","items":{"type":"object","additionalProperties":true}},"tool_call_id":{"type":"string"}},"additionalProperties":true},"description":"Array of message objects: [{\"role\":\"system\"|\"user\"|\"assistant\",\"content\":\"...\"}]"},"max_tokens":{"type":"number","description":"Maximum tokens to generate (up to 384000). Required to bound metered x402 authorization."},"temperature":{"type":"number","description":"Sampling temperature 0–2. Default: 1. Lower = more deterministic."}},"additionalProperties":true},"responseSchema":null,"example":{"request":{"model":"deepseek-chat","messages":[{"role":"user","content":"Explain the concept of machine learning in simple terms."}],"max_tokens":256,"temperature":0.7},"response":{"data":{"id":"6cb7cb6d-4ae2-4a86-a277-92afcf4663d6","model":"deepseek-v4-flash","usage":{"total_tokens":270,"prompt_tokens":14,"completion_tokens":256,"prompt_tokens_details":{"cached_tokens":0},"prompt_cache_hit_tokens":0,"prompt_cache_miss_tokens":14},"object":"chat.completion","choices":[{"index":0,"message":{"role":"assistant","content":"Here's a simple explanation of machine learning:\n\n**Think of it like teaching a child to recognize animals.**\n\n**Traditional programming** is like giving a child a rulebook: \"If it has 4 legs and fur, it's a dog. If it has 2 legs and feathers, it's a bird.\" The child just follows the rules you gave.\n\n**Machine learning** is different. Instead of giving rules, you **show the child thousands of pictures** of dogs and birds, and you tell them which is which. Over time, the child's brain starts to notice patterns on its own: \"Hmm, most of the things called 'dog' have floppy ears and a wet nose.\" Eventually, the child can look at a **new picture** they've never seen before and correctly guess if it's a dog or a bird.\n\n**In short:**\n\n- **You don't program the rules.**\n- **You feed the computer lots of examples (data).**\n- **The computer figures out the patterns by itself.**\n- **It then uses those patterns to make predictions or decisions on new data.**\n\n**Real-world examples you use every day:**\n\n- **Spam filter:** You mark emails as \"spam.\" The computer learns what spam looks like"},"logprobs":null,"finish_reason":"length"}],"created":1781064057,"system_fingerprint":"fp_8b330d02d0_prod0820_fp8_kvcache_20260402"},"success":true}},"exampleRequest":{"model":"deepseek-chat","messages":[{"role":"user","content":"Explain the concept of machine learning in simple terms."}],"max_tokens":256,"temperature":0.7},"tags":["llm","reasoning","code","chat","chain-of-thought","ai"],"displayCostAmount":"0.004","displayCostAsset":"USDC","priceDynamic":true,"priceHint":"Model + token dependent (~$0.004–$0.025)","priceStatus":"priced","priceSource":"settled","requiresHandshake":false,"reviewCount":1,"rating":{"score":"0.75","successRate":"1.00","reviews":1,"stars":"4.0","state":"rated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"dynamic","summary":"Model + token dependent (~$0.004–$0.025) (dynamic)","primary":{"kind":"dynamic","protocol":"mpp","network":"tempo","amountUsd":"0.004","per":"call","confidence":"exact"},"accepted":[{"kind":"dynamic","protocol":"mpp","network":"tempo","amountUsd":"0.004","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_bVNqPn98Nt4eKnjeKAz-k","protocol":"mpp","methodType":"crypto","chain":"tempo","mode":"charge","costAmount":"0.004","costPer":"request","priority":0,"asset":"0x20c000000000000000000000b9537d11c60e8b50","unit":"request","depositMicros":null,"planRef":null}],"brandName":"DeepSeek","brandSlug":"deepseek","brandBaseUrl":"https://deepseek.com","brandDocsUrl":"https://api-docs.deepseek.com","whatItDoes":"Send a conversation to DeepSeek's LLM (fast V3 or reasoning R1) and receive a generated text response","exampleAgentPrompt":"Use DeepSeek-reasoner (R1) to walk me through, step by step, why the halting problem is undecidable — keep it under 500 tokens and use a temperature of 0.3 for a precise answer.","exampleUseCases":null,"resultDescription":"Returns an assistant message object containing the model's generated text response. When using deepseek-reasoner (R1), the response may include a chain-of-thought reasoning trace followed by the final answer. Streaming responses are delivered via SSE if enabled.","failureModes":["Invalid model name returns 400 error","Messages array missing or malformed returns 422 validation error","max_tokens exceeded for model context window returns 400","Temperature out of range (>2) returns 400","Payment not included or insufficient USDC balance returns 402","Rate limiting or upstream DeepSeek API unavailability returns 503"],"whenToPreferThis":"Choose this endpoint when you need access to DeepSeek's frontier models — specifically V3 for fast, cost-efficient chat and code generation, or R1 for deep chain-of-thought reasoning tasks. Prefer over generic OpenAI endpoints when the task benefits from DeepSeek's reasoning capabilities or cost profile. Ideal for agents needing programmable LLM inference with per-call micropayment pricing via USDC.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":5,"lastUsedAt":"2026-05-29T14:32:35.747Z","lastSuccessfullyRanAt":"2026-05-29T14:32:35.747Z","lastHealthCheckAt":"2026-10-12T06:30:37.068Z","isFirstParty":false,"canonicalSlug":"deepseek-chat-bb22b2ff"}