{"uid":"cap__hkjTxDzfqkpF42rNPuRi","slug":"glm-5-2-large-scale-reasoning-model-via-x402engine-e7903a32","name":"GLM-5.2 Large-Scale Reasoning Model via x402engine","description":"Z.ai's large-scale reasoning model — 1M context for long-horizon agent workflows and software engineering","url":"https://x402engine.app/api/llm/glm-5.2","method":"POST","headers":{},"bodySchema":null,"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.03","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"registry","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.03/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.03","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.03","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_XAnjdSSBJCFfpPXxww10i","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.03","costPer":"request","priority":0,"asset":null,"unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Calls Z.ai's GLM-5.2 large-scale reasoning model with 1M context window, optimized for long-horizon agent workflows and software engineering tasks, via pay-per-call HTTP 402 micropayment.","exampleAgentPrompt":"Use GLM-5.2 to analyze this entire 200,000-token codebase and generate a detailed refactoring plan that identifies architectural bottlenecks, suggests modular improvements, and outlines a phased migration strategy.","exampleUseCases":[{"title":"Full codebase architectural review","prompt":"I have a large Node.js monorepo — can you run it through GLM-5.2 and get me a detailed architectural review with specific recommendations for breaking it into microservices?"},{"title":"Long-horizon multi-step agent planning","prompt":"I need a long-horizon plan to build and deploy a SaaS product from scratch — use GLM-5.2's 1M context to generate a complete, step-by-step agent workflow covering product design, backend, frontend, and deployment."},{"title":"Complex document reasoning and synthesis","prompt":"I have 50 research papers on transformer architectures — feed them all into GLM-5.2 and have it synthesize the key findings, identify contradictions, and suggest open research questions."}],"resultDescription":"The agent receives a text completion from GLM-5.2, which may include structured reasoning, generated code, analytical summaries, multi-step plans, or natural language responses depending on the prompt. The model supports up to 1M tokens of context, enabling extremely long inputs and complex chain-of-thought outputs.","failureModes":["Payment failure via x402 protocol if USDC balance is insufficient","Context window exceeded if input surpasses 1M tokens","Rate limiting or throttling under high load","Model timeout for extremely complex long-horizon reasoning chains","Invalid request format returning 400 error","Network errors or service unavailability returning 5xx"],"whenToPreferThis":"Choose this endpoint when you need a large-scale reasoning model with a 1M token context window, especially for software engineering, long-horizon agentic planning, or processing very large documents or codebases. Prefer it over smaller or cheaper models when task complexity demands deep multi-step reasoning. The pay-per-call x402 micropayment model is ideal for agents that need flexible, subscription-free LLM access. If you need ultra-low-cost or ultra-low-latency inference, consider sibling DeepSeek endpoints on x402engine instead.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T00:43:35.403Z","isFirstParty":false}