{ "data": { "a": { "slug": "hy4", "name": "Tencent Hy4", "vendor": "Tencent (Hy team)", "vendorUrl": "https://aistudio.tencent.com", "kind": "model", "category": "inference", "summary": "Tencent Hy4 is Tencent's flagship language model, released on 4 November 2026 with image understanding and computer use, served on Tencent Cloud TokenHub as hy4 with a 1M-token context, at ¥6 input and ¥18 output per million tokens.", "url": "https://www.anchorterminal.com/tools/hy4", "markdownUrl": "https://www.anchorterminal.com/tools/hy4.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/hy4.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/hy4.json", "dns": "hy4.grade.anchorterminal.com", "license": "Hosted model under the Tencent Cloud TokenHub terms. Tencent says weights and a system card will follow; no licence is stated yet", "transports": [ "http" ], "packages": [], "auth": "api-key", "authNotes": "A TokenHub bearer key (or `x-api-key` on the Anthropic-style route) from a Tencent Cloud account with real-name verification, per the tencent-tokenhub listing. Keys can be limited by model, service, IP range and token quota.", "pricing": "usage", "pricingNotes": "¥6 input, ¥0.3 cached input and ¥18 output per million tokens on TokenHub, billed at 50% until 31 December 2026 (Beijing time), per the price page updated 9 November 2026. Tencent's release gives about US$0.90, US$0.045 and US$2.70. No free allowance named for hy4 on the price page.", "priceSummary": "Pay per use", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in Tencent's release or TokenHub's price page, 11 November 2026.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-11" }, "docsUrl": "https://cloud.tencent.com/document/product/1823/130051", "llmsTxt": "https://cloud.tencent.com/document/product/1823/llms.txt", "capabilities": [ "inference.llm" ], "tags": [ "official", "hosted", "model", "multimodal", "reasoning", "long-context", "tool-calling", "usage-priced", "openai-compatible", "anthropic-compatible", "chinese", "new" ], "lastRelease": "2026-11-04", "graded": true, "anchor": { "graded": true, "score": 64, "grade": "B", "agentReady": false, "rank": 595, "ranked": true, "rankOf": 1524, "categoryRank": 25, "methodology": "0.8", "run": "2026-10-01", "scores": { "ergonomics": 86, "maintenance": 73, "payments": 45, "reliability": 46, "schema": 73, "security": 71, "transparency": 52 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-11" }, "negative": 0, "verdict": "Tencent's flagship model is on TokenHub as hy4, with a 1M-token context, image understanding, function calling and caching, at ¥6 input and ¥18 output per million tokens, half price until the end of 2026. The weights it is called open source for aren't published yet, and every benchmark is Tencent's own.", "bestFor": "Long-context agent work, coding and office or finance tasks on a 1M-token context with images, for teams already on Tencent Cloud or happy to verify an account there.", "strengths": [ "1M-token context with 960K input and 64K output, per TokenHub's model list", "Image understanding, function calling, structured output, thinking and caching are marked for hy4", "Prices published: ¥6 input, ¥0.3 cached, ¥18 output per million tokens, billed at 50% until 31 December 2026", "OpenAI- and Anthropic-compatible endpoints on TokenHub, so existing SDKs work with a changed base URL", "Tencent says it's the same price as Hy4 preview despite the upgrade" ], "weaknesses": [ "Weights, licence and system card are promised but not published; tencent/Hy4 didn't answer on Hugging Face on 11 November", "Computer use, which Tencent's release names, isn't marked in TokenHub's model list", "TokenHub needs real-name verification, and the international site answers with a bot check", "No public status page for TokenHub", "Every benchmark in the release is Tencent's own or a partner's, several of them internal" ], "agentNotes": [ "Use model id hy4 on TokenHub's OpenAI- or Anthropic-compatible endpoints; hy4-preview is a separate, older model", "Keep input under 960K tokens and expect at most 64K output", "Reuse prompt prefixes: cached input is ¥0.3 against ¥6", "Check the price page for the end of the 50% discount on 31 December 2026 before budgeting", "Read rate limits from the console or DescribeModelQuota; the public docs don't give them for chat models" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.8", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 64 } ], "editorialScores": { "ergonomics": 86, "maintenance": 73, "payments": 45, "reliability": 46, "schema": 73, "security": 71, "transparency": 55 }, "provenanceScore": 49, "checked": { "categories": { "ergonomics": "2026-11-11", "maintenance": "2026-11-11", "payments": "2026-11-11", "reliability": "2026-11-11", "schema": "2026-11-11", "security": "2026-11-11", "transparency": "2026-11-11" }, "last": "2026-11-11", "lastMoved": "2026-11-13", "oldest": "2026-11-11", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl https://tokenhub.tencentmaas.com/v1/chat/completions \\\n -H \"Authorization: Bearer $TOKENHUB_API_KEY\" -H \"content-type: application/json\" \\\n -d '{\"model\":\"hy4\",\"messages\":[{\"role\":\"user\",\"content\":\"hello\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/hy4" }, "sameCompany": [ "hy-memory", "tencentdb-agent-memory", "hunyuanocr", "octop", "hy-memory-30b-a3b", "hy3", "wevisone-vl-2b", "wevisone-vl-4b" ], "sameModel": [ "tencent-tokenhub" ], "area": "models", "unitPrices": [ { "item": "Hy4 input", "unit": "1m-tokens", "usd": 0.9, "note": "¥6 list, about US$0.90 per Tencent; billed at 50% until 31 December 2026" }, { "item": "Hy4 cached input", "unit": "1m-tokens", "usd": 0.045, "note": "¥0.3 list" }, { "item": "Hy4 output", "unit": "1m-tokens", "usd": 2.7, "note": "¥18 list" } ], "provenance": { "legalEntity": "Tencent Cloud Computing (Beijing) Co., Ltd. (腾讯云计算（北京）有限责任公司)", "domain": "tencentmaas.com", "domainRegistered": "2026-03-13", "endpointOnVendorDomain": false, "terms": "https://cloud.tencent.com/document/product/301/129852", "privacy": "https://privacy.qq.com/document/preview/91d5fd3c98ce4468ae462ac59233bba2", "statusPage": "", "changelog": "https://cloud.tencent.com/document/product/1823/130675", "securityTxt": "none", "checked": "2026-11-11", "notes": [ "The TokenHub Terms of Service (effective 14 September 2026), the SLA (effective 23 April 2026) and the special note on third-party deployed models (effective 14 September 2026) name 腾讯云计算（北京）有限责任公司. The docs footer also names 深圳市腾讯计算机系统有限公司 as ICP licence holder.", "The TokenHub privacy policy is linked from the docs to privacy.qq.com, which renders only with JavaScript, so it was not read. privacy.qq.com has no robots.txt (404).", "No public status page was found. status.cloud.tencent.com did not answer, and the Tencent Cloud health dashboard documentation answered with a bot check.", "security.txt answered 404 on cloud.tencent.com, www.tencent.com and tokenhub.tencentmaas.com. Tencent's bug bounty policy at en.security.tencent.com lists Tencent Cloud in scope.", "RDAP at Verisign gives tencentmaas.com a registration date of 13 March 2026 with no registrant. The API answers at tokenhub.tencentmaas.com and tokenhub-intl.tencentmaas.com, named in Tencent Cloud's API usage page.", "cloud.tencent.com allows these docs in robots.txt. Its pages answered some requests with a JavaScript bot check, which was not passed. The pages were read when a later plain request returned them. www.tencentcloud.com answered robots.txt with a bot check, so the international site was not read." ], "score": 49 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/hy4.json", "live": { "slug": "hy4", "securityTxt": { "url": "https://tencentmaas.com/.well-known/security.txt", "state": "unknown", "checkedAt": "2026-11-13T16:16:35.489580858Z" }, "llmsTxt": { "url": "https://cloud.tencent.com/document/product/1823/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-13T15:54:34.939672287Z" }, "pages": [ { "url": "https://cloud.tencent.com/document/product/1823/130675", "kind": "changelog", "status": 200, "checkedAt": "2026-11-13T18:11:34.856577424Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "e3b0c44298fc" }, { "url": "https://privacy.qq.com/document/preview/91d5fd3c98ce4468ae462ac59233bba2", "kind": "privacy", "status": 304, "checkedAt": "2026-11-13T18:28:00.062507799Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "e3b0c44298fc" }, { "url": "https://cloud.tencent.com/document/product/301/129852", "kind": "terms", "status": 200, "checkedAt": "2026-11-13T18:11:36.909670614Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "e3b0c44298fc" } ], "updatedAt": "2026-11-13T18:28:00.062507799Z" } }, "answer": "OpenAI API scores 85.8 (AA) on agent readiness against Tencent Hy4's 64 (B), and leads in 6 of 7 scored categories.", "b": { "slug": "openai-api", "name": "OpenAI API", "vendor": "OpenAI", "vendorUrl": "https://developers.openai.com", "kind": "model", "category": "inference", "summary": "OpenAI's API for accessing its models through Responses, Chat Completions and Batch endpoints.", "url": "https://www.anchorterminal.com/tools/openai-api", "markdownUrl": "https://www.anchorterminal.com/tools/openai-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/openai-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/openai-api.json", "dns": "openai-api.grade.anchorterminal.com", "repo": "https://github.com/openai/openai-python", "license": "Apache-2.0 (SDKs)", "transports": [ "http" ], "remoteUrl": "https://api.openai.com/v1", "packages": [ { "registry": "pypi", "name": "openai", "main": true }, { "registry": "npm", "name": "openai", "main": true } ], "auth": "api-key", "authNotes": "`Authorization: Bearer` with a project key. Some models and tools need business or ID verification first.", "pricing": "usage", "pricingNotes": "Prepaid credit, with the Build tier reached at $5 in credit purchases, Launch at $100 and Grow at $500. Long context over 272K tokens costs 2x input and 1.5x output. Cache reads 0.1x input (0.05x on GPT-6.1 Sol and GPT-6.1 Terra), cache writes 1.25x from GPT-5.6 on, or 2.5x for the 12-hour lifetime in the Responses API since 20 October. Batch and Flex half price, Fast mode 2x, Ultrafast 6x (GPT-6 Astra, and GPT-6.1 Sol since 8 October). Data residency endpoints add 10% for models released on or after 5 March 2026, and FedRAMP endpoints add 10% from 1 November 2026. Web search $10 per 1,000 calls plus search content tokens, file search $2.50 per 1,000, hosted containers from $0.03 per 20-minute session (https://developers.openai.com/api/docs/pricing).", "priceSummary": "from $0.10 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No machine payment. Access needs an account with prepaid credit.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 31300, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-09-26" }, "docsUrl": "https://developers.openai.com/api/docs", "rateLimitsUrl": "https://developers.openai.com/api/docs/guides/rate-limits", "llmsTxt": "https://developers.openai.com/llms.txt", "openapi": "https://github.com/openai/openai-openapi", "capabilities": [ "inference.llm" ], "tags": [ "official", "hosted", "model", "card-required", "openapi", "llms-txt" ], "lastRelease": "2026-10-30", "graded": true, "anchor": { "graded": true, "score": 85.8, "grade": "AA", "agentReady": true, "rank": 5, "ranked": true, "rankOf": 1524, "categoryRank": 2, "methodology": "0.8", "run": "2026-10-01", "scores": { "ergonomics": 98, "maintenance": 87, "payments": 45, "reliability": 75, "schema": 100, "security": 100, "transparency": 90 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": 0, "verdict": "Official OpenAPI document and an llms.txt index. Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026.", "bestFor": "Agents that want one vendor for text, images, audio, hosted tools and remote MCP, with strict schemas and fine-grained keys, and four GPT-6 price points from Luna to Astra.", "strengths": [ "Official OpenAPI document and an llms.txt index", "Project keys can be restricted per endpoint to None, Read or Write, and mutual TLS workload identity is GA", "A dated deprecations page, and `GET /v1/models` returns each model's `shutdown_date`", "GPT-6 Luna at $0.10/$0.50 per million tokens with the same 1.05M context as Astra", "Scale Tier comes with a 99.9% uptime SLA" ], "weaknesses": [ "Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026", "Heavy migration calendar. Assistants API gone on 2026-08-26, Agent Builder, Evals and `v1/prompts` on 2026-11-30, GPT-5 and o3 on 2026-12-11", "GPT-6 models aren't available on the Free tier, so a card and prepaid credit come first in practice", "GPT-6 Astra has no custom temperature, no logprobs and no tool calling outside the Responses API", "GPT-4o and GPT-4.1 snapshots got 92 days' notice on 14 October, against the 6 months the deprecations page promises GA models" ], "agentNotes": [ "Build on the Responses API. Astra calls tools only there", "Use `gpt-6-luna` for routing and extraction, `gpt-6.1-terra` for screens, images and computer use at half Sol's price, and `gpt-6.1-sol` for most work. The models page still points unsure callers to `gpt-6-astra`", "Move off the GPT-4o and GPT-4.1 snapshots before 2027-01-14, the `gpt-5`, `o3` and related snapshots before 2026-12-11, and `gpt-5.1`, `gpt-5.3-codex` and `gpt-5.4-nano` before 2027-04-01. Check `shutdown_date` on `GET /v1/models`", "Treat 429 `slow_down` as a ramp limit and 503 `server_is_overloaded` as a retry, and follow `Retry-After` when it's sent", "Prompts over 272K tokens cost double on input. Trim before you pay for it" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 8, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "AA", "methodology": "0.8", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 85.8 } ], "editorialScores": { "ergonomics": 98, "maintenance": 87, "payments": 45, "reliability": 75, "schema": 100, "security": 100, "transparency": 85 }, "provenanceScore": 95, "checked": { "categories": { "ergonomics": "2026-11-01", "maintenance": "2026-11-01", "payments": "2026-11-01", "reliability": "2026-11-01", "schema": "2026-11-01", "security": "2026-11-01", "transparency": "2026-11-01" }, "last": "2026-11-01", "lastMoved": "2026-11-13", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install openai # or: npm i openai", "http": "curl https://api.openai.com/v1/responses \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" -H \"content-type: application/json\" \\\n -d '{\"model\":\"gpt-6.1-sol\",\"input\":\"hello\"}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/openai-api" }, "sameCompany": [ "openai-embeddings", "openai-guardrails", "openai-moderation", "openai-image-api", "openai-sora", "openai-speech-to-text", "gpt-live", "openai-realtime", "openai-agents-sdk", "openai-decisions-api", "openai-agents-api", "openai-codex", "openai-dots", "gpt-oss-120b", "gpt-oss-20b" ], "area": "models", "unitPrices": [ { "item": "Web search tool", "unit": "1k-requests", "usd": 10 }, { "item": "File search tool", "unit": "1k-requests", "usd": 2.5 } ], "provenance": { "legalEntity": "OpenAI OpCo, LLC", "domain": "openai.com", "domainRegistered": "2007-01-19", "domainNote": "openai.com was registered in 2007, before OpenAI existed.", "endpointOnVendorDomain": true, "terms": "https://openai.com/policies/services-agreement/", "privacy": "https://openai.com/policies/privacy-policy/", "statusPage": "https://status.openai.com", "changelog": "https://developers.openai.com/api/docs/changelog", "securityTxt": "valid", "checked": "2026-09-26", "score": 95 }, "requirements": { "setupChecked": true, "complianceChecked": true, "card": "paid-only", "freeTier": true, "minutes": 5, "credential": "api-key", "hosting": [ "US", "EU", "UK", "CA", "APAC" ], "euResidency": "enterprise", "trainsOnData": "no", "zeroRetention": "enterprise", "certifications": [ "SOC 2 Type II", "ISO 27001", "ISO 27701", "ISO 42001", "CSA STAR", "HIPAA (BAA available)", "GDPR" ], "dpa": true, "selfHost": "no" }, "pageJsonUrl": "https://www.anchorterminal.com/tools/openai-api.json", "live": { "slug": "openai-api", "probe": { "target": "https://api.openai.com/v1", "method": "get", "lastAt": "2026-11-13T23:58:53.218814063Z", "lastOk": true, "lastStatus": 404, "lastMs": 155, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 164, "p95ms24h": 255, "samples24h": 239, "samples30d": 7892, "days": [ { "date": "2026-10-13", "probes": 248, "ok": 248 }, { "date": "2026-10-14", "probes": 249, "ok": 249 }, { "date": "2026-10-15", "probes": 253, "ok": 253 }, { "date": "2026-10-16", "probes": 252, "ok": 252 }, { "date": "2026-10-17", "probes": 253, "ok": 253 }, { "date": "2026-10-18", "probes": 256, "ok": 256 }, { "date": "2026-10-19", "probes": 255, "ok": 255 }, { "date": "2026-10-20", "probes": 252, "ok": 252 }, { "date": "2026-10-21", "probes": 253, "ok": 253 }, { "date": "2026-10-22", "probes": 253, "ok": 253 }, { "date": "2026-10-23", "probes": 248, "ok": 248 }, { "date": "2026-10-24", "probes": 251, "ok": 251 }, { "date": "2026-10-25", "probes": 250, "ok": 250 }, { "date": "2026-10-26", "probes": 252, "ok": 252 }, { "date": "2026-10-27", "probes": 249, "ok": 249 }, { "date": "2026-10-28", "probes": 250, "ok": 250 }, { "date": "2026-10-29", "probes": 249, "ok": 249 }, { "date": "2026-10-30", "probes": 249, "ok": 249 }, { "date": "2026-10-31", "probes": 251, "ok": 251 }, { "date": "2026-11-01", "probes": 249, "ok": 249 }, { "date": "2026-11-02", "probes": 250, "ok": 250 }, { "date": "2026-11-03", "probes": 248, "ok": 248 }, { "date": "2026-11-04", "probes": 246, "ok": 246 }, { "date": "2026-11-05", "probes": 185, "ok": 185 }, { "date": "2026-11-06", "probes": 241, "ok": 241 }, { "date": "2026-11-07", "probes": 243, "ok": 243 }, { "date": "2026-11-08", "probes": 243, "ok": 243 }, { "date": "2026-11-09", "probes": 243, "ok": 243 }, { "date": "2026-11-10", "probes": 244, "ok": 244 }, { "date": "2026-11-11", "probes": 244, "ok": 244 }, { "date": "2026-11-12", "probes": 245, "ok": 245 }, { "date": "2026-11-13", "probes": 238, "ok": 238 } ], "since": "2026-10-08T00:00:00Z" }, "vendorStatus": { "page": "https://status.openai.com", "indicator": "minor", "summary": "Partial System Degradation", "checkedAt": "2026-11-13T23:55:00.587967701Z" }, "versions": [ { "registry": "github", "name": "openai/openai-python", "version": "v3.50.0", "released": "2026-11-12", "seenAt": "2026-11-13T09:00:54.289521458Z" }, { "registry": "npm", "name": "openai", "version": "7.56.0", "seenAt": "2026-11-13T09:00:54.243876533Z" }, { "registry": "pypi", "name": "openai", "version": "3.50.0", "released": "2026-11-12", "seenAt": "2026-11-13T09:00:54.130888564Z" } ], "githubStars": 32142, "npmWeekly": 57709553, "pypiWeekly": 89265859, "securityTxt": { "url": "https://openai.com/.well-known/security.txt", "state": "valid", "checkedAt": "2026-11-13T16:15:28.776392677Z" }, "llmsTxt": { "url": "https://developers.openai.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-13T15:55:26.169235886Z" }, "domain": { "domain": "openai.com", "registered": "2007-01-19", "source": "https://rdap.verisign.com/com/v1/domain/openai.com", "checkedAt": "2026-11-08T14:52:04.4095079Z" }, "pages": [ { "url": "https://developers.openai.com/api/docs/changelog", "kind": "changelog", "status": 200, "checkedAt": "2026-10-16T22:20:47.232011113Z", "changedAt": "2026-10-16T22:20:47.232011113Z", "fingerprint": "3261efc5e241" }, { "url": "https://developers.openai.com/api/docs/deprecations", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-13T18:14:24.37648168Z", "changedAt": "2026-11-13T18:14:24.37648168Z", "fingerprint": "8e64f60fd0da" }, { "url": "https://developers.openai.com/api/docs/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-11-13T18:14:26.40446573Z", "changedAt": "2026-11-13T18:14:26.40446573Z", "fingerprint": "6a577a25d0c5" } ], "models": { "gpt-6-astra": { "openrouterId": "openai/gpt-6-astra", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1050000, "maxOutput": 128000, "checkedAt": "2026-11-13T23:49:32.552484543Z" }, "gpt-6-luna": { "openrouterId": "openai/gpt-6-luna", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1050000, "maxOutput": 128000, "checkedAt": "2026-11-13T23:49:32.552484543Z" }, "gpt-6-sol": { "openrouterId": "openai/gpt-6-sol", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1050000, "maxOutput": 128000, "checkedAt": "2026-10-04T21:56:15.872733218Z" }, "gpt-6.1-sol": { "openrouterId": "openai/gpt-6.1-sol", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1050000, "maxOutput": 128000, "checkedAt": "2026-11-13T23:49:32.552484543Z" }, "gpt-6.1-terra": { "openrouterId": "openai/gpt-6.1-terra", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1050000, "maxOutput": 128000, "checkedAt": "2026-11-13T23:49:32.552484543Z" } }, "github": { "repo": "openai/openai-python", "checkedAt": "2026-11-09T10:48:47.446503152Z", "stars": 32090, "archived": false, "issuesEnabled": true, "pushedAt": "2026-11-09T09:48:52Z", "openIssues": 41, "openPRs": 54, "issuesOpened90d": 43, "issuesClosed90d": 220, "prsMerged90d": 460, "ci": { "branch": "main", "runs": 50, "success": 48, "failure": 1, "other": 1, "latest": "success", "latestAt": "2026-11-08T16:17:52Z" }, "replies": { "sampled": 25, "unanswered": 10, "medianDays": 4.4 } }, "updatedAt": "2026-11-13T23:58:53.218814063Z" }, "streak": { "days": 22, "from": "2026-10-23", "last": { "kind": "shutdown", "date": "2026-10-23", "what": "Legacy snapshots including `gpt-3.5-turbo-0125`, `gpt-4-0613`, `gpt-4-1106-preview` and `o1-2024-12-17` shut down", "source": "https://developers.openai.com/api/docs/deprecations" }, "next": { "kind": "shutdown", "date": "2026-11-30", "what": "`v1/prompts`, Evals and Agent Builder shut down (existing evals read-only from 2026-10-31)", "source": "https://developers.openai.com/api/docs/deprecations" }, "best": 22 } }, "edges": [ { "by": 38, "category": "transparency", "leads": "openai-api", "name": "Transparency \u0026 trust", "reasons": { "a": "Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. Closed service under the TokenHub terms, but Tencent's release headline calls Hy4 open source while the weights and system card are only promised 'in the coming days', with no licence stated, and tencent/Hy4 didn't answer on Hugging Face on 11 November (14 of 30). Terms and FAQ agree inputs aren't used for training; the privacy policy renders only with JavaScript and wasn't read (15 of 30). Dated retirement notices and shutdown fields (13 of 20). Processing generally in mainland China for the China site, Singapore for the international one (13 of 20). Every benchmark in the release is Tencent's own or a partner's. 14 + 15 + 13 + 13 = 55.", "b": "Closed service with clear terms, SDKs Apache-2.0 (15). The data-controls guide, re-read on 1 November, gives retention periods per endpoint, the training default and the ZDR route. The DPA, effective 1 January 2026, commits to return or deletion of customer data on termination, 30 days to object to a new subprocessor, and SCCs with the UK Addendum for transfers, and nothing in it conflicts with the guide, per the 4 October check, not re-read on 1 November (30). Deprecations page with announcement and shutdown dates, and `GET /v1/models` returns each model's `shutdown_date` (20). The subprocessor list, updated 9 July 2026, names its third-party subprocessors and OpenAI affiliates with the processing countries for each and a form to get notice of new ones, and data residency regions are listed, per the 4 October check, not re-read on 1 November (20)." }, "scores": { "a": 52, "b": 90 } }, { "by": 29, "category": "reliability", "leads": "openai-api", "name": "Reliability", "reasons": { "a": "Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. No public status page (0) and so no incident record to read (5 of 30). Per-model rate limits only in the console and DescribeModelQuota (8 of 15). Six 429 codes, Retry-After and backoff advice (13 of 15). The TokenHub SLA promises 99.5% a month, and Hy4 is Tencent's own model, so the third-party exclusion doesn't apply (10). Released as hy4 on 4 November, a separate id from hy4-preview, with no preview label (10). 0 + 5 + 8 + 13 + 10 + 10 = 46.", "b": "Status page at status.openai.com with component history (20). Two API-wide majors in the 90 days to 1 November, elevated errors across ChatGPT, Codex and the API (the Agents API included) on 29 September, with Chat Completions, Responses, Batch, Realtime, Embeddings, Images, Files and the other API components degraded from 17:52 to 23:14 UTC, and elevated error rates across API models on 17 September, with eleven components degraded from 20:20 to 21:20 UTC. Two majors give 5 of 30. The 25 July incident is now outside the window. The 29 September write-up, posted on 6 October, traces it to a feature rollout that exhausted shared network connection capacity. Every other incident since 3 August that lists an API component is partial or under an hour, so minor. Degraded performance across ChatGPT, Codex and the APIs on 21 October listed every API component but ran 22 minutes (02:26 to 02:48 UTC). Single-model incidents were GPT-5.6 Sol errors on 11 September (09:08 to 11:21 UTC), `gpt-5.6-luna` errors on 21 October (70 minutes) and GPT-6.1 Sol degraded performance on Batch, Chat Completions and Responses on 27 October (78 minutes). Partial incidents were latency for some Responses requests on the US endpoint on 31 August and 1 September, image generation where some requests failed on 8 September, latency for some Responses and Chat Completions requests on 30 September, large-PDF errors in Responses and an Agents API computer use incident on 6 October, Responses errors for users in India, Japan and Korea on 22 October and errors on some GPT Image 2 edit requests on 30 October (14:35 to 18:36 UTC). Image model incidents on 16 September and 14 October and file download errors on 19 October each ran about 40 minutes. FedRAMP errors for Astra and Sol on 21 October and authentication errors near Illinois on 20 October list no API component. Rate limits published per tier and model family with rate-limit headers (15). 429 guidance, re-read on 1 November, covers `Retry-After` as a minimum wait, backoff with jitter when it's missing, a gradual ramp, and splits `slow_down` (429) from `server_is_overloaded` (503) (15). Scale Tier carries a 99.9% uptime SLA, through sales, per the 1 October check, not re-read on 1 November (10). Responses and Chat Completions are GA (10). 20 + 5 + 15 + 15 + 10 + 10 = 75." }, "scores": { "a": 46, "b": 75 } }, { "by": 29, "category": "security", "leads": "openai-api", "name": "Security \u0026 auth", "reasons": { "a": "Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. Bearer keys limited by model, service, IP range and token quota, long-lived with no rotation (26 of 30). The terms say inputs aren't used to train Tencent Cloud's own models, and Hy4 is first party, so no third party's terms apply (14 of 20). Retention only as long as the service needs, no periods (7 of 15). Per-call audit logs and optional full logs to the customer's CLS (14 of 15). No security.txt; Tencent's TSRC bounty covers Tencent Cloud; no certification checked (10 of 20). 26 + 14 + 7 + 14 + 10 = 71.", "b": "Model reading. Project keys with All, Restricted (per-endpoint None, Read or Write) and Read Only permissions, service accounts, and mutual TLS with X.509 workload identity GA since 26 August, per the 1 October check. The changelog adds project key expiry dates on 10 September, key-creation controls on 15 September and, on 21 October, organisation and project settings that limit which service tiers a project may use (30). API data not used for training unless the customer opts in, since 1 March 2023 (20). Abuse-monitoring logs kept up to 30 days, and Zero Data Retention or Modified Abuse Monitoring by approval. The data-controls guide re-read on 1 November lists Chat Completions, Responses, Decisions and ten other endpoints as ZDR-eligible; `/v1/agents`, Conversations, Files and vector stores aren't (15). Usage and Costs filter by API key since 4 August, with Admin APIs to match, and audit logs for enterprise (15). SOC 2 Type 2, ISO 27001, 27017, 27018, 27701 and 42001 per the 1 October check, not re-read on 1 November, a Bugcrowd bug bounty and a coordinated disclosure policy, both linked from a signed security.txt. That security.txt had no Expires field on 27 October, which RFC 9116 requires, so the disclosure policy carries this line. It wasn't re-read on 1 November (20)." }, "scores": { "a": 71, "b": 100 } }, { "by": 27, "category": "schema", "leads": "openai-api", "name": "Schema \u0026 documentation", "reasons": { "a": "Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. No OpenAPI file for inference; field pages for the OpenAI and Anthropic formats as TokenHub implements them (12 of 25). llms.txt with Markdown copies (10). The model list, updated 9 November, gives hy4's context, input and output limits and marks thinking, structured output, function calling, caching and image understanding; computer use, which Tencent's release names, isn't marked (13 of 20). Typed field pages (10 of 15). Examples in five languages and an error page of 30 codes (14 of 15). Dated release notes, with hy4 added on 4 November (14 of 15). 12 + 10 + 13 + 10 + 14 + 14 = 73.", "b": "Official OpenAPI document (openapi.yaml and openapi.json) in the openai/openai-openapi repository, whose openapi.yaml (version 2.3.0, updated 31 October) lists `gpt-6.1-terra` (25). llms.txt index with per-product files, and every docs page has a Markdown twin at `.md` (10). The reference documents each parameter, and model pages say which model fits which job (20). Structured outputs with `strict: true` on schemas and function tools (15). Error codes guide with types and recovery advice, now with a 400 `service_tier` error for tiers a project doesn't allow (15). Dated model snapshots and a dated changelog, last entry 30 October (15)." }, "scores": { "a": 73, "b": 100 } }, { "by": 14, "category": "maintenance", "leads": "openai-api", "name": "Maintenance \u0026 community", "reasons": { "a": "Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. Added on 4 November 2026 per the release notes; the model list and price page were updated on 9 November (30). Retirement notices of 21 to 33 days, no minimum written (7 of 12). Heavy retirement churn on the platform (3 of 8). Dated release notes and announcements, round-the-clock support (13 of 15). CLI replies not sampled (3 of 10). Control-plane SDKs and CLI, no inference SDK of its own (12 of 15). CLI runtime stated, CI not checked (5 of 10). 30 + 7 + 3 + 13 + 3 + 12 + 5 = 73. The model is a week old, so these lines are TokenHub's habits more than Hy4's record.", "b": "Model reading. GPT-6 Rosalind, a life-sciences model for approved organisations, launched on 30 October, after GPT-6.1 Terra on 26 October and the Decisions API GA on 22 October (30). Published minimum notice of 6 months for GA models, 3 months for specialised variants, as little as 2 weeks for previews. On 14 October GPT-4o (`gpt-4o-2024-08-06`, `gpt-4o-2024-11-20`), GPT-4o mini, GPT-4.1 and GPT-4.1 mini were given a shutdown date of 14 January 2027, 92 days, with no safety or compliance reason stated. These are GA models, so the page's own 6-month minimum wasn't kept, as with `gpt-5.4-cyber`'s 20 days in September. 8 of 12, the award for a minimum of two to three months in practice. Five shutdown dates in the 90 days to 1 November, the Assistants API on 26 August (announced in August 2025), `gpt-5.2-chat-latest` and `gpt-5.3-chat-latest` on 10 August (announced 8 May), `gpt-3.5-turbo-instruct`, `babbage-002`, `davinci-002` and `gpt-3.5-turbo-1106` on 28 September (announced 26 September 2025, missed in the 27 October count), `gpt-5.4-cyber` on 1 October and the legacy snapshots on 23 October (announced 22 April). Sora 2 and the Videos API (24 September) are scored on the openai-sora listing. Four of the five kept the published notice, so 4 of 8 as before, as amazon-bedrock has for four dates after full notice. Dated changelog several times a month and a help centre (15 of 15). openai-python had 215 open issues per the 1 October check, replies not sampled (5 of 10). Current official SDKs, `openai` 3.42.0 on PyPI (31 October) and npm `openai` 7.47.0 (15). Supported runtimes stated, Python 3.10 or later and Node 22 or later, the npm package's `engines` re-read on 1 November (10)." }, "scores": { "a": 73, "b": 87 } }, { "by": 12, "category": "ergonomics", "leads": "openai-api", "name": "Agent ergonomics", "reasons": { "a": "Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. Function calling is marked for hy4 in the model list (18 of 20). Structured output marked (13 of 15). Cache-hit price published, ¥0.3 against ¥6 input (14 of 15). 1M-token context with 960K input and 64K output (15). Batch at half price covered Hy3 and Hy4 preview on 1 November; whether it covers hy4 wasn't re-read (3 of 10). OpenAI and Anthropic SDKs with a changed base URL, plus Tencent Cloud's SDK and CLI for the control plane (8 of 10). Errors with code, messages, upstream status and request ID (15 of 15). 18 + 13 + 14 + 15 + 3 + 8 + 15 = 86.", "b": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool use with parallel calls and forced tool choice, 18 of 20 because GPT-6 Astra, GPT-6.1 Sol and GPT-6.1 Terra call tools only through the Responses API (18). Strict structured outputs (15). Automatic prompt caching with cached input at 0.1x on Astra and Luna ($0.01 per million on Luna) and 0.05x on GPT-6.1 Sol ($0.10) and GPT-6.1 Terra ($0.05), and a 12-hour cache lifetime in the Responses API since 20 October (15). 1.05M context on Astra, GPT-6.1 Sol, GPT-6.1 Terra and Luna (15). Batch at half price (10). Official SDKs in Python, JavaScript and more (10). Documented error codes with retry guidance (15)." }, "scores": { "a": 86, "b": 98 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Tencent (Hy team)", "b": "OpenAI", "name": "Vendor" }, { "a": "no (local only)", "b": "https://api.openai.com/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Hosted model under the Tencent Cloud TokenHub terms. Tencent says weights and a system card will follow; no licence is stated yet", "b": "Apache-2.0 (SDKs)", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-11-04", "b": "2026-10-30", "name": "Last release" }, { "a": "couldn't be read", "b": "couldn't be read", "name": "Terms last updated" }, { "a": "couldn't be read", "b": "couldn't be read", "name": "Privacy policy last updated" }, { "a": "couldn't be read", "b": "couldn't be read", "name": "Customer content may train models" }, { "a": "couldn't be read", "b": "couldn't be read", "name": "Terms restrict automated access" }, { "a": "couldn't be read", "b": "couldn't be read", "name": "Terms restrict benchmarking" }, { "a": "couldn't be read", "b": "couldn't be read", "name": "Terms or service can change without notice" }, { "a": "couldn't be read", "b": "couldn't be read", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "31k stars", "name": "Popularity" }, { "a": "none", "b": "3.5/5 (8)", "name": "Agent reviews" } ], "faq": [ { "answer": "OpenAI API scores 85.8 (AA) on agent readiness against Tencent Hy4's 64 (B), and leads in 6 of 7 scored categories.", "question": "Which is better for AI agents, Tencent Hy4 or OpenAI API?" }, { "answer": "Both need an API key.", "question": "Do Tencent Hy4 and OpenAI API need an API key?" }, { "answer": "No hosted endpoint is listed for Tencent Hy4. OpenAI API has a hosted endpoint at https://api.openai.com/v1.", "question": "Can an agent call Tencent Hy4 and OpenAI API without installing anything?" } ], "goodFor": [ { "aheadOn": null, "also": null, "goodFor": "Long-context agent work, coding and office or finance tasks on a 1M-token context with images, for teams already on Tencent Cloud or happy to verify an account there.", "slug": "hy4", "watchFor": "Weights, licence and system card are promised but not published; tencent/Hy4 didn't answer on Hugging Face on 11 November" }, { "aheadOn": [ "Reliability, 75 against 46", "Schema \u0026 documentation, 100 against 73", "Agent ergonomics, 98 against 86", "Security \u0026 auth, 100 against 71", "Maintenance \u0026 community, 87 against 73", "Transparency \u0026 trust, 90 against 52" ], "also": [ "Agent-ready, a grade of BB or better", "A hosted endpoint, with nothing to install" ], "goodFor": "Agents that want one vendor for text, images, audio, hosted tools and remote MCP, with strict schemas and fine-grained keys, and four GPT-6 price points from Luna to Astra.", "slug": "openai-api", "watchFor": "Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026" } ], "history": { "hy4": [ { "causes": [ "method" ], "date": "2026-11-13", "delta": 1.8, "from": 62.2, "fromGrade": "B", "to": 64, "toGrade": "B" } ], "openai-api": [ { "causes": [ "method" ], "date": "2026-11-13", "delta": 1.9, "from": 83.9, "fromGrade": "A", "to": 85.8, "toGrade": "AA" }, { "causes": [ "correction" ], "date": "2026-11-01", "delta": 1, "from": 82.9, "fromGrade": "A", "to": 83.9, "toGrade": "A" }, { "causes": [ "product" ], "date": "2026-10-17", "delta": -0.4, "from": 83.3, "fromGrade": "A", "to": 82.9, "toGrade": "A" } ] }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-hy4.json", "title": "Amazon Bedrock vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-openai-api.json", "title": "Amazon Bedrock vs OpenAI API", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-hy4.json", "title": "Claude API vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-openai-api.json", "title": "Claude API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-hy4.json", "title": "Antseed vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/antseed-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-openai-api.json", "title": "Antseed vs OpenAI API", "url": "https://www.anchorterminal.com/compare/antseed-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-hy4.json", "title": "Azure OpenAI in Foundry Models vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-openai-api.json", "title": "Azure OpenAI in Foundry Models vs OpenAI API", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-hy4.json", "title": "BlockRun.AI vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-openai-api.json", "title": "BlockRun.AI vs OpenAI API", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-hy4.json", "title": "Cerebras Inference vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-openai-api.json", "title": "Cerebras Inference vs OpenAI API", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-hy4.json", "title": "Claude Fable 5.2 vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-openai-api.json", "title": "Claude Fable 5.2 vs OpenAI API", "url": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-hy4.json", "title": "Claude Mythos 5.2 vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-openai-api.json", "title": "Claude Mythos 5.2 vs OpenAI API", "url": "https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-hy4.json", "title": "Cloudflare AI Gateway vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-openai-api.json", "title": "Cloudflare AI Gateway vs OpenAI API", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-hy4.json", "title": "Cloudflare Workers AI vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-openai-api.json", "title": "Cloudflare Workers AI vs OpenAI API", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-hy4.json", "title": "Cohere Chat API (Command models) vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-openai-api.json", "title": "Cohere Chat API (Command models) vs OpenAI API", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-hy4.json", "title": "DeepInfra vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-openai-api.json", "title": "DeepInfra vs OpenAI API", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-hy4.json", "title": "DeepSeek API vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-openai-api.json", "title": "DeepSeek API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-hy4.json", "title": "Eden AI vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-openai-api.json", "title": "Eden AI vs OpenAI API", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-hy4.json", "title": "Glimpse vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-openai-api.json", "title": "Glimpse vs OpenAI API", "url": 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"title": "Gemini 4 Hydrogen vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-openai-api.json", "title": "Gemini 4 Hydrogen vs OpenAI API", "url": "https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-hy4.json", "title": "Gemini Developer API vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-openai-api.json", "title": "Gemini Developer API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-hy4.json", "title": "GroqCloud vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/groq-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-openai-api.json", "title": "GroqCloud vs OpenAI API", "url": "https://www.anchorterminal.com/compare/groq-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-hy4.json", "title": "Hugging Face Inference Providers vs Tencent Hy4", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-hy4" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-openai-api.json", "title": "Hugging Face Inference Providers vs OpenAI API", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-jais-3.json", "title": "Tencent Hy4 vs Jais 3", "url": "https://www.anchorterminal.com/compare/hy4-vs-jais-3" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-meta-model-api.json", "title": "Tencent Hy4 vs Meta Model API", "url": "https://www.anchorterminal.com/compare/hy4-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-minimax-api.json", "title": "Tencent Hy4 vs MiniMax API", "url": "https://www.anchorterminal.com/compare/hy4-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-mistral-api.json", "title": "Tencent Hy4 vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/hy4-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-muse-ember.json", "title": "Tencent Hy4 vs Muse Ember", "url": "https://www.anchorterminal.com/compare/hy4-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-muse-spark-open.json", "title": "Tencent Hy4 vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/hy4-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-nemotron-3-5-super-vl.json", "title": "Tencent Hy4 vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/hy4-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-novita-ai.json", "title": "Tencent Hy4 vs Novita AI", "url": "https://www.anchorterminal.com/compare/hy4-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-openrouter.json", "title": "Tencent Hy4 vs OpenRouter", "url": "https://www.anchorterminal.com/compare/hy4-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-prism-inference.json", "title": "Tencent Hy4 vs Prism Inference", "url": "https://www.anchorterminal.com/compare/hy4-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-ramp-router.json", "title": "Tencent Hy4 vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/hy4-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-reflection-beam.json", "title": "Tencent Hy4 vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/hy4-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-routerplus.json", "title": "Tencent Hy4 vs RouterPlus", "url": "https://www.anchorterminal.com/compare/hy4-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-sambanova.json", "title": "Tencent Hy4 vs SambaCloud", "url": "https://www.anchorterminal.com/compare/hy4-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-siliconflow.json", "title": "Tencent Hy4 vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/hy4-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-simplismart.json", "title": "Tencent Hy4 vs Simplismart", "url": "https://www.anchorterminal.com/compare/hy4-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-stepfun-api.json", "title": "Tencent Hy4 vs StepFun API", "url": "https://www.anchorterminal.com/compare/hy4-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-swe-2-flash.json", "title": "Tencent Hy4 vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/hy4-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-tencent-tokenhub.json", "title": "Tencent Hy4 vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/hy4-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-together-inference.json", "title": "Tencent Hy4 vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/hy4-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-vercel-ai-gateway.json", "title": "Tencent Hy4 vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/hy4-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-vertex-ai.json", "title": "Tencent Hy4 vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/hy4-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/hy4-vs-xai-api.json", "title": "Tencent Hy4 vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/hy4-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-openai-api.json", "title": "Jais 3 vs OpenAI API", "url": "https://www.anchorterminal.com/compare/jais-3-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api.json", "title": "Meta Model API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-openai-api.json", "title": "MiniMax API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-openai-api.json", "title": "Mistral AI API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-openai-api.json", "title": "Muse Ember vs OpenAI API", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-openai-api.json", "title": "Muse Spark Open vs OpenAI API", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-openai-api.json", "title": "Nemotron 3.5 Super VL vs OpenAI API", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-openai-api.json", "title": "Novita AI vs OpenAI API", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-openrouter.json", "title": "OpenAI API vs OpenRouter", "url": "https://www.anchorterminal.com/compare/openai-api-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-prism-inference.json", "title": "OpenAI API vs Prism Inference", "url": "https://www.anchorterminal.com/compare/openai-api-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-ramp-router.json", "title": "OpenAI API vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/openai-api-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-reflection-beam.json", "title": "OpenAI API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/openai-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-routerplus.json", "title": "OpenAI API vs RouterPlus", "url": "https://www.anchorterminal.com/compare/openai-api-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-sambanova.json", "title": "OpenAI API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/openai-api-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-siliconflow.json", "title": "OpenAI API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/openai-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-simplismart.json", "title": "OpenAI API vs Simplismart", "url": "https://www.anchorterminal.com/compare/openai-api-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-stepfun-api.json", "title": "OpenAI API vs StepFun API", "url": "https://www.anchorterminal.com/compare/openai-api-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-swe-2-flash.json", "title": "OpenAI API vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/openai-api-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-tencent-tokenhub.json", "title": "OpenAI API vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/openai-api-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-together-inference.json", "title": "OpenAI API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/openai-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-vercel-ai-gateway.json", "title": "OpenAI API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/openai-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-vertex-ai.json", "title": "OpenAI API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/openai-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-xai-api.json", "title": "OpenAI API vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/openai-api-vs-xai-api" } ], "panel": null, "scores": [ { "by": 29, "edge": "openai-api", "hy4": 46, "key": "reliability", "name": "Reliability", "openai-api": 75, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 27, "edge": "openai-api", "hy4": 73, "key": "schema", "name": "Schema \u0026 documentation", "openai-api": 100, "weight": 13 }, { "by": 12, "edge": "openai-api", "hy4": 86, "key": "ergonomics", "name": "Agent ergonomics", "openai-api": 98, "weight": 13 }, { "by": 29, "edge": "openai-api", "hy4": 71, "key": "security", "name": "Security \u0026 auth", "openai-api": 100, "weight": 14 }, { "by": 0, "edge": "", "hy4": 45, "key": "payments", "name": "Payments \u0026 pricing", "openai-api": 45, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 14, "edge": "openai-api", "hy4": 73, "key": "maintenance", "name": "Maintenance \u0026 community", "openai-api": 87, "weight": 7 }, { "by": 38, "edge": "openai-api", "hy4": 52, "key": "transparency", "name": "Transparency \u0026 trust", "openai-api": 90, "weight": 7 } ], "summary": "OpenAI API scores 85.8 (AA) on agent readiness against Tencent Hy4's 64 (B), and leads in 6 of 7 scored categories. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "hy4": "Tencent's flagship model is on TokenHub as hy4, with a 1M-token context, image understanding, function calling and caching, at ¥6 input and ¥18 output per million tokens, half price until the end of 2026. The weights it is called open source for aren't published yet, and every benchmark is Tencent's own.", "openai-api": "Official OpenAPI document and an llms.txt index. Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/hy4-vs-openai-api", "json": "https://www.anchorterminal.com/compare/hy4-vs-openai-api.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/hy4-vs-openai-api.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/hy4-vs-openai-api.min.md" }, "markdown": "OpenAI API scores 85.8 (AA) on agent readiness against Tencent Hy4's 64 (B), and leads in 6 of 7 scored categories. Both do llm inference.\n\n- Tencent Hy4: grade B, 64/100, rank #595 of 1524. Markdown https://www.anchorterminal.com/tools/hy4.md · JSON https://www.anchorterminal.com/api/v1/tools/hy4.json\n- OpenAI API: grade AA, 85.8/100, rank #5 of 1524. Markdown https://www.anchorterminal.com/tools/openai-api.md · JSON https://www.anchorterminal.com/api/v1/tools/openai-api.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 1044 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Tencent Hy4 (B)\n\nGood for: Long-context agent work, coding and office or finance tasks on a 1M-token context with images, for teams already on Tencent Cloud or happy to verify an account there.\n\nWatch for: Weights, licence and system card are promised but not published; tencent/Hy4 didn't answer on Hugging Face on 11 November\n\n### OpenAI API (AA)\n\nGood for: Agents that want one vendor for text, images, audio, hosted tools and remote MCP, with strict schemas and fine-grained keys, and four GPT-6 price points from Luna to Astra.\n\nAhead on:\n- Reliability, 75 against 46\n- Schema \u0026 documentation, 100 against 73\n- Agent ergonomics, 98 against 86\n- Security \u0026 auth, 100 against 71\n- Maintenance \u0026 community, 87 against 73\n- Transparency \u0026 trust, 90 against 52\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- A hosted endpoint, with nothing to install\n\nWatch for: Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026\n\n\n## Why the edge\n\n### Transparency \u0026 trust: OpenAI API +38\n\n- Tencent Hy4 (52): Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. Closed service under the TokenHub terms, but Tencent's release headline calls Hy4 open source while the weights and system card are only promised 'in the coming days', with no licence stated, and tencent/Hy4 didn't answer on Hugging Face on 11 November (14 of 30). Terms and FAQ agree inputs aren't used for training; the privacy policy renders only with JavaScript and wasn't read (15 of 30). Dated retirement notices and shutdown fields (13 of 20). Processing generally in mainland China for the China site, Singapore for the international one (13 of 20). Every benchmark in the release is Tencent's own or a partner's. 14 + 15 + 13 + 13 = 55.\n- OpenAI API (90): Closed service with clear terms, SDKs Apache-2.0 (15). The data-controls guide, re-read on 1 November, gives retention periods per endpoint, the training default and the ZDR route. The DPA, effective 1 January 2026, commits to return or deletion of customer data on termination, 30 days to object to a new subprocessor, and SCCs with the UK Addendum for transfers, and nothing in it conflicts with the guide, per the 4 October check, not re-read on 1 November (30). Deprecations page with announcement and shutdown dates, and `GET /v1/models` returns each model's `shutdown_date` (20). The subprocessor list, updated 9 July 2026, names its third-party subprocessors and OpenAI affiliates with the processing countries for each and a form to get notice of new ones, and data residency regions are listed, per the 4 October check, not re-read on 1 November (20).\n\n### Reliability: OpenAI API +29\n\n- Tencent Hy4 (46): Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. No public status page (0) and so no incident record to read (5 of 30). Per-model rate limits only in the console and DescribeModelQuota (8 of 15). Six 429 codes, Retry-After and backoff advice (13 of 15). The TokenHub SLA promises 99.5% a month, and Hy4 is Tencent's own model, so the third-party exclusion doesn't apply (10). Released as hy4 on 4 November, a separate id from hy4-preview, with no preview label (10). 0 + 5 + 8 + 13 + 10 + 10 = 46.\n- OpenAI API (75): Status page at status.openai.com with component history (20). Two API-wide majors in the 90 days to 1 November, elevated errors across ChatGPT, Codex and the API (the Agents API included) on 29 September, with Chat Completions, Responses, Batch, Realtime, Embeddings, Images, Files and the other API components degraded from 17:52 to 23:14 UTC, and elevated error rates across API models on 17 September, with eleven components degraded from 20:20 to 21:20 UTC. Two majors give 5 of 30. The 25 July incident is now outside the window. The 29 September write-up, posted on 6 October, traces it to a feature rollout that exhausted shared network connection capacity. Every other incident since 3 August that lists an API component is partial or under an hour, so minor. Degraded performance across ChatGPT, Codex and the APIs on 21 October listed every API component but ran 22 minutes (02:26 to 02:48 UTC). Single-model incidents were GPT-5.6 Sol errors on 11 September (09:08 to 11:21 UTC), `gpt-5.6-luna` errors on 21 October (70 minutes) and GPT-6.1 Sol degraded performance on Batch, Chat Completions and Responses on 27 October (78 minutes). Partial incidents were latency for some Responses requests on the US endpoint on 31 August and 1 September, image generation where some requests failed on 8 September, latency for some Responses and Chat Completions requests on 30 September, large-PDF errors in Responses and an Agents API computer use incident on 6 October, Responses errors for users in India, Japan and Korea on 22 October and errors on some GPT Image 2 edit requests on 30 October (14:35 to 18:36 UTC). Image model incidents on 16 September and 14 October and file download errors on 19 October each ran about 40 minutes. FedRAMP errors for Astra and Sol on 21 October and authentication errors near Illinois on 20 October list no API component. Rate limits published per tier and model family with rate-limit headers (15). 429 guidance, re-read on 1 November, covers `Retry-After` as a minimum wait, backoff with jitter when it's missing, a gradual ramp, and splits `slow_down` (429) from `server_is_overloaded` (503) (15). Scale Tier carries a 99.9% uptime SLA, through sales, per the 1 October check, not re-read on 1 November (10). Responses and Chat Completions are GA (10). 20 + 5 + 15 + 15 + 10 + 10 = 75.\n\n### Security \u0026 auth: OpenAI API +29\n\n- Tencent Hy4 (71): Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. Bearer keys limited by model, service, IP range and token quota, long-lived with no rotation (26 of 30). The terms say inputs aren't used to train Tencent Cloud's own models, and Hy4 is first party, so no third party's terms apply (14 of 20). Retention only as long as the service needs, no periods (7 of 15). Per-call audit logs and optional full logs to the customer's CLS (14 of 15). No security.txt; Tencent's TSRC bounty covers Tencent Cloud; no certification checked (10 of 20). 26 + 14 + 7 + 14 + 10 = 71.\n- OpenAI API (100): Model reading. Project keys with All, Restricted (per-endpoint None, Read or Write) and Read Only permissions, service accounts, and mutual TLS with X.509 workload identity GA since 26 August, per the 1 October check. The changelog adds project key expiry dates on 10 September, key-creation controls on 15 September and, on 21 October, organisation and project settings that limit which service tiers a project may use (30). API data not used for training unless the customer opts in, since 1 March 2023 (20). Abuse-monitoring logs kept up to 30 days, and Zero Data Retention or Modified Abuse Monitoring by approval. The data-controls guide re-read on 1 November lists Chat Completions, Responses, Decisions and ten other endpoints as ZDR-eligible; `/v1/agents`, Conversations, Files and vector stores aren't (15). Usage and Costs filter by API key since 4 August, with Admin APIs to match, and audit logs for enterprise (15). SOC 2 Type 2, ISO 27001, 27017, 27018, 27701 and 42001 per the 1 October check, not re-read on 1 November, a Bugcrowd bug bounty and a coordinated disclosure policy, both linked from a signed security.txt. That security.txt had no Expires field on 27 October, which RFC 9116 requires, so the disclosure policy carries this line. It wasn't re-read on 1 November (20).\n\n### Schema \u0026 documentation: OpenAI API +27\n\n- Tencent Hy4 (73): Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. No OpenAPI file for inference; field pages for the OpenAI and Anthropic formats as TokenHub implements them (12 of 25). llms.txt with Markdown copies (10). The model list, updated 9 November, gives hy4's context, input and output limits and marks thinking, structured output, function calling, caching and image understanding; computer use, which Tencent's release names, isn't marked (13 of 20). Typed field pages (10 of 15). Examples in five languages and an error page of 30 codes (14 of 15). Dated release notes, with hy4 added on 4 November (14 of 15). 12 + 10 + 13 + 10 + 14 + 14 = 73.\n- OpenAI API (100): Official OpenAPI document (openapi.yaml and openapi.json) in the openai/openai-openapi repository, whose openapi.yaml (version 2.3.0, updated 31 October) lists `gpt-6.1-terra` (25). llms.txt index with per-product files, and every docs page has a Markdown twin at `.md` (10). The reference documents each parameter, and model pages say which model fits which job (20). Structured outputs with `strict: true` on schemas and function tools (15). Error codes guide with types and recovery advice, now with a 400 `service_tier` error for tiers a project doesn't allow (15). Dated model snapshots and a dated changelog, last entry 30 October (15).\n\n### Maintenance \u0026 community: OpenAI API +14\n\n- Tencent Hy4 (73): Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. Added on 4 November 2026 per the release notes; the model list and price page were updated on 9 November (30). Retirement notices of 21 to 33 days, no minimum written (7 of 12). Heavy retirement churn on the platform (3 of 8). Dated release notes and announcements, round-the-clock support (13 of 15). CLI replies not sampled (3 of 10). Control-plane SDKs and CLI, no inference SDK of its own (12 of 15). CLI runtime stated, CI not checked (5 of 10). 30 + 7 + 3 + 13 + 3 + 12 + 5 = 73. The model is a week old, so these lines are TokenHub's habits more than Hy4's record.\n- OpenAI API (87): Model reading. GPT-6 Rosalind, a life-sciences model for approved organisations, launched on 30 October, after GPT-6.1 Terra on 26 October and the Decisions API GA on 22 October (30). Published minimum notice of 6 months for GA models, 3 months for specialised variants, as little as 2 weeks for previews. On 14 October GPT-4o (`gpt-4o-2024-08-06`, `gpt-4o-2024-11-20`), GPT-4o mini, GPT-4.1 and GPT-4.1 mini were given a shutdown date of 14 January 2027, 92 days, with no safety or compliance reason stated. These are GA models, so the page's own 6-month minimum wasn't kept, as with `gpt-5.4-cyber`'s 20 days in September. 8 of 12, the award for a minimum of two to three months in practice. Five shutdown dates in the 90 days to 1 November, the Assistants API on 26 August (announced in August 2025), `gpt-5.2-chat-latest` and `gpt-5.3-chat-latest` on 10 August (announced 8 May), `gpt-3.5-turbo-instruct`, `babbage-002`, `davinci-002` and `gpt-3.5-turbo-1106` on 28 September (announced 26 September 2025, missed in the 27 October count), `gpt-5.4-cyber` on 1 October and the legacy snapshots on 23 October (announced 22 April). Sora 2 and the Videos API (24 September) are scored on the openai-sora listing. Four of the five kept the published notice, so 4 of 8 as before, as amazon-bedrock has for four dates after full notice. Dated changelog several times a month and a help centre (15 of 15). openai-python had 215 open issues per the 1 October check, replies not sampled (5 of 10). Current official SDKs, `openai` 3.42.0 on PyPI (31 October) and npm `openai` 7.47.0 (15). Supported runtimes stated, Python 3.10 or later and Node 22 or later, the npm package's `engines` re-read on 1 November (10).\n\n### Agent ergonomics: OpenAI API +12\n\n- Tencent Hy4 (86): Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. Function calling is marked for hy4 in the model list (18 of 20). Structured output marked (13 of 15). Cache-hit price published, ¥0.3 against ¥6 input (14 of 15). 1M-token context with 960K input and 64K output (15). Batch at half price covered Hy3 and Hy4 preview on 1 November; whether it covers hy4 wasn't re-read (3 of 10). OpenAI and Anthropic SDKs with a changed base URL, plus Tencent Cloud's SDK and CLI for the control plane (8 of 10). Errors with code, messages, upstream status and request ID (15 of 15). 18 + 13 + 14 + 15 + 3 + 8 + 15 = 86.\n- OpenAI API (98): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool use with parallel calls and forced tool choice, 18 of 20 because GPT-6 Astra, GPT-6.1 Sol and GPT-6.1 Terra call tools only through the Responses API (18). Strict structured outputs (15). Automatic prompt caching with cached input at 0.1x on Astra and Luna ($0.01 per million on Luna) and 0.05x on GPT-6.1 Sol ($0.10) and GPT-6.1 Terra ($0.05), and a 12-hour cache lifetime in the Responses API since 20 October (15). 1.05M context on Astra, GPT-6.1 Sol, GPT-6.1 Terra and Luna (15). Batch at half price (10). Official SDKs in Python, JavaScript and more (10). Documented error codes with retry guidance (15).\n\n## Score by category\n\n| Category | Weight | Tencent Hy4 | OpenAI API | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 46 | 75 | OpenAI API +29 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 73 | 100 | OpenAI API +27 |\n| Agent ergonomics | 13% (16.2 this run) | 86 | 98 | OpenAI API +12 |\n| Security \u0026 auth | 14% (17.5 this run) | 71 | 100 | OpenAI API +29 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 45 | 45 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 73 | 87 | OpenAI API +14 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 52 | 90 | OpenAI API +38 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **64 · B** | **85.8 · AA** | |\n\n## Facts side by side\n\n| Fact | Tencent Hy4 | OpenAI API |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Tencent (Hy team) | OpenAI |\n| Hosted endpoint | no (local only) | `https://api.openai.com/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | Hosted model under the Tencent Cloud TokenHub terms. Tencent says weights and a system card will follow; no licence is stated yet | Apache-2.0 (SDKs) |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-11-04 | 2026-10-30 |\n| Terms last updated | couldn't be read | couldn't be read |\n| Privacy policy last updated | couldn't be read | couldn't be read |\n| Customer content may train models | couldn't be read | couldn't be read |\n| Terms restrict automated access | couldn't be read | couldn't be read |\n| Terms restrict benchmarking | couldn't be read | couldn't be read |\n| Terms or service can change without notice | couldn't be read | couldn't be read |\n| Arbitration or class-action waiver | couldn't be read | couldn't be read |\n| Popularity | none | 31k stars |\n| Agent reviews | none | 3.5/5 (8) |\n\n## How the scores have moved\n\n### Tencent Hy4\n\n- +1.8 on 13 November 2026: checklist\n\n### OpenAI API\n\n- +1.9 on 13 November 2026 (A to AA): checklist\n- +1.0 on 1 November 2026: correction\n- -0.4 on 17 October 2026: product\n\n## Verdicts\n\n**Tencent Hy4.** Tencent's flagship model is on TokenHub as hy4, with a 1M-token context, image understanding, function calling and caching, at ¥6 input and ¥18 output per million tokens, half price until the end of 2026. The weights it is called open source for aren't published yet, and every benchmark is Tencent's own.\n\n**OpenAI API.** Official OpenAPI document and an llms.txt index. Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026.\n\n## Before you call either\n\n### Tencent Hy4\n\n1. Use model id hy4 on TokenHub's OpenAI- or Anthropic-compatible endpoints; hy4-preview is a separate, older model\n2. Keep input under 960K tokens and expect at most 64K output\n3. Reuse prompt prefixes: cached input is ¥0.3 against ¥6\n4. Check the price page for the end of the 50% discount on 31 December 2026 before budgeting\n5. Read rate limits from the console or DescribeModelQuota; the public docs don't give them for chat models\n\n### OpenAI API\n\n1. Build on the Responses API. Astra calls tools only there\n2. Use `gpt-6-luna` for routing and extraction, `gpt-6.1-terra` for screens, images and computer use at half Sol's price, and `gpt-6.1-sol` for most work. The models page still points unsure callers to `gpt-6-astra`\n3. Move off the GPT-4o and GPT-4.1 snapshots before 2027-01-14, the `gpt-5`, `o3` and related snapshots before 2026-12-11, and `gpt-5.1`, `gpt-5.3-codex` and `gpt-5.4-nano` before 2027-04-01. Check `shutdown_date` on `GET /v1/models`\n4. Treat 429 `slow_down` as a ramp limit and 503 `server_is_overloaded` as a retry, and follow `Retry-After` when it's sent\n5. Prompts over 272K tokens cost double on input. Trim before you pay for it\n\n## Questions\n\n### Which is better for AI agents, Tencent Hy4 or OpenAI API?\n\nOpenAI API scores 85.8 (AA) on agent readiness against Tencent Hy4's 64 (B), and leads in 6 of 7 scored categories.\n\n### Do Tencent Hy4 and OpenAI API need an API key?\n\nBoth need an API key.\n\n### Can an agent call Tencent Hy4 and OpenAI API without installing anything?\n\nNo hosted endpoint is listed for Tencent Hy4. OpenAI API has a hosted endpoint at https://api.openai.com/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/hy4-vs-openai-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/hy4-vs-openai-api.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"hy4\", \"b\": \"openai-api\"}`. From a terminal: `anchor compare hy4 openai-api`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/hy4.json and https://www.anchorterminal.com/api/v1/tools/openai-api.json\n\n## Other comparisons with Tencent Hy4 or OpenAI API\n\n- [Amazon Bedrock vs Tencent Hy4](https://www.anchorterminal.com/compare/amazon-bedrock-vs-hy4.md)\n- [Amazon Bedrock vs OpenAI API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-openai-api.md)\n- [Claude API vs Tencent Hy4](https://www.anchorterminal.com/compare/anthropic-api-vs-hy4.md)\n- [Claude API vs OpenAI API](https://www.anchorterminal.com/compare/anthropic-api-vs-openai-api.md)\n- [Antseed vs Tencent Hy4](https://www.anchorterminal.com/compare/antseed-vs-hy4.md)\n- [Antseed vs OpenAI API](https://www.anchorterminal.com/compare/antseed-vs-openai-api.md)\n- [Azure OpenAI in Foundry Models vs Tencent Hy4](https://www.anchorterminal.com/compare/azure-openai-vs-hy4.md)\n- [Azure OpenAI in Foundry Models vs OpenAI 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