{ "data": { "a": { "slug": "stepfun-api", "name": "StepFun API", "vendor": "StepFun", "vendorUrl": "https://platform.stepfun.ai", "kind": "model", "category": "inference", "summary": "The StepFun API is StepFun's paid model API for its Step language, vision and speech models, including the flagship Step 5 Preview, through OpenAI-style Chat Completions and Responses endpoints and an Anthropic-style Messages endpoint.", "url": "https://www.anchorterminal.com/tools/stepfun-api", "markdownUrl": "https://www.anchorterminal.com/tools/stepfun-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/stepfun-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/stepfun-api.json", "dns": "stepfun-api.grade.anchorterminal.com", "license": "Closed service under the StepFun Open Platform Terms of Service (STEPFUN TECHNOLOGY (HK) LIMITED, Hong Kong law).", "transports": [ "http" ], "remoteUrl": "https://api.stepfun.ai/v1", "packages": [], "auth": "api-key", "authNotes": "A bearer API key created in the StepFun Open Platform console after sign-up. Organisations can create one key per project, billed to the organisation's credit and deletable at once. No key scopes were found. Individual accounts must complete identity verification before tiered rate limits apply.", "pricing": "usage", "pricingNotes": "Step 5 Preview is $1.00 per million input tokens on a cache miss, $0.10 on a cache hit and $2.70 per million output tokens, reasoning included (checked 2026-10-12). Prepaid top-ups. No free API allowance was found. A Step Plan subscription covers coding tools separately.", "priceSummary": "from $0.10 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the international docs index, the pricing page or the Chat Completions reference, checked 12 October 2026. Calls draw on a prepaid balance.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-12" }, "docsUrl": "https://platform.stepfun.ai/docs/en/guides/models/step-5-preview", "llmsTxt": "https://platform.stepfun.ai/docs/llms.txt", "capabilities": [ "inference.llm" ], "tags": [ "official", "hosted", "model", "usage-priced", "closed-source", "llms-txt", "multimodal", "streaming" ], "graded": true, "anchor": { "graded": true, "score": 44.3, "grade": "E", "agentReady": false, "rank": 1223, "ranked": true, "rankOf": 1510, "categoryRank": 38, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 68, "maintenance": 50, "payments": 20, "reliability": 28, "schema": 53, "security": 41, "transparency": 57 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-12" }, "negative": 0, "verdict": "StepFun's API serves Step 5 Preview with a 1M-token context, video input, strict JSON Schema output and published per-token prices, documented in Markdown with an llms.txt. The model is a preview with no release date found, there's no free allowance or SLA, and the terms and privacy policy leave room to train on customer data.", "bestFor": "Long-context agent and coding work over text, screenshots and video at a low per-token price, where a preview model is acceptable.", "strengths": [ "Step 5 Preview takes text, images and video with a 1M-token context and up to 64k output tokens", "Strict JSON Schema output and tool calls on Step 5 Preview, per the structured-output guide", "Per-token prices with cache-hit rates published without a login, and rate-limit tiers published with numbers", "OpenAI-style Chat Completions and Responses endpoints and an Anthropic-style Messages endpoint", "llms.txt and a Markdown copy of every docs page" ], "weaknesses": [ "Step 5 Preview is labelled a preview, and no release date or support commitment was found", "No free API allowance found, and individual accounts need identity verification for tiered limits", "No OpenAPI file, no official SDK and no batch endpoint found", "The privacy policy allows training on user data where law and program terms permit, with no zero-retention option found", "No SLA, security.txt or certification found" ], "agentNotes": [ "Set `max_tokens` yourself. It defaults to unlimited on Step 5 Preview, and reasoning tokens are billed as output", "Use `response_format` with `type: json_schema` and `strict: true` when the shape matters. JSON Mode alone isn't schema-checked", "Back off and retry on 429, 500, 503 and 504. The docs give no Retry-After header or backoff schedule", "Expect HTTP 451 or `finish_reason: content_filter` when content fails StepFun's review, and don't retry the same input", "Use api.stepfun.ai for the international platform. api.stepfun.com is the China platform with yuan pricing" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 3.3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "E", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 44.3 } ], "editorialScores": { "ergonomics": 68, "maintenance": 50, "payments": 20, "reliability": 28, "schema": 53, "security": 41, "transparency": 51 }, "provenanceScore": 62, "checked": { "categories": { "ergonomics": "2026-10-12", "maintenance": "2026-10-12", "payments": "2026-10-12", "reliability": "2026-10-12", "schema": "2026-10-12", "security": "2026-10-12", "transparency": "2026-10-12" }, "last": "2026-10-12", "lastMoved": "2026-10-28", "oldest": "2026-10-12", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl https://api.stepfun.ai/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $STEPFUN_API_KEY\" \\\n -d '{\"model\":\"step-5-preview\",\"messages\":[{\"role\":\"user\",\"content\":\"Hello\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/stepfun-api" }, "area": "models", "unitPrices": [ { "item": "Step 5 Preview input, cache miss", "unit": "1m-tokens", "usd": 1, "note": "Includes writing new content to the cache." }, { "item": "Step 5 Preview input, cache hit", "unit": "1m-tokens", "usd": 0.1 }, { "item": "Step 5 Preview output", "unit": "1m-tokens", "usd": 2.7, "note": "Reasoning and final answer tokens." } ], "provenance": { "legalEntity": "STEPFUN TECHNOLOGY (HK) LIMITED", "domain": "stepfun.ai", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://platform.stepfun.ai/docs/en/agreement/userservice", "privacy": "https://platform.stepfun.ai/docs/en/agreement/userprivacy", "statusPage": "", "changelog": "https://platform.stepfun.ai/docs/en/guides/model-migration", "securityTxt": "none", "checked": "2026-10-12", "notes": [ "The terms and the privacy policy name STEPFUN TECHNOLOGY (HK) LIMITED. Disputes go to HKIAC arbitration under Hong Kong law.", "platform.stepfun.ai/.well-known/security.txt returned 404, and stepfun.ai/.well-known/security.txt redirects to the platform home page.", "status.stepfun.ai refused our reader by robots.txt, and the shell couldn't connect, so whether it is a status page wasn't established.", "The X handle comes from the QR code labelled X account on the platform home page, which decodes to https://x.com/StepFun_ai.", "Domain registration date was not checked." ], "score": 62 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/stepfun-api.json", "live": { "slug": "stepfun-api", "probe": { "target": "https://api.stepfun.ai/v1", "method": "get", "lastAt": "2026-11-07T19:22:36.049435872Z", "lastOk": true, "lastStatus": 404, "lastMs": 377, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 297, "p95ms24h": 407, "samples24h": 238, "samples30d": 6610, "days": [ { "date": "2026-10-12", "probes": 221, "ok": 221 }, { "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": 197, "ok": 197 } ] }, "securityTxt": { "url": "https://stepfun.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:00:20.384102443Z" }, "llmsTxt": { "url": "https://platform.stepfun.ai/docs/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:34:03.95242188Z" }, "domain": { "domain": "stepfun.ai", "registered": "2023-03-23", "source": "https://rdap.identitydigital.services/rdap/domain/stepfun.ai", "checkedAt": "2026-11-01T14:23:53.578776563Z" }, "pages": [ { "url": "https://platform.stepfun.ai/docs/en/guides/model-migration", "kind": "changelog", "status": 200, "checkedAt": "2026-11-07T14:16:53.997459265Z", "changedAt": "2026-11-06T13:38:33.586652298Z", "fingerprint": "05d8b90a13cc" }, { "url": "https://platform.stepfun.ai/docs/en/guides/image-offline-notice", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:16:52.104408963Z", "changedAt": "2026-11-06T13:38:32.195771661Z", "fingerprint": "ce427e012456" }, { "url": "https://platform.stepfun.ai/docs/en/agreement/userprivacy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:16:47.619696391Z", "changedAt": "2026-11-06T13:38:27.237331116Z", "fingerprint": "597fa1278404" }, { "url": "https://platform.stepfun.ai/docs/en/agreement/userservice", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:16:49.979240402Z", "changedAt": "2026-11-06T13:38:30.139946008Z", "fingerprint": "2ff748ab87c5" } ], "updatedAt": "2026-11-07T19:22:36.049435872Z" } }, "answer": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against StepFun API's 44.3 (E), and leads in every scored category.", "b": { "slug": "vertex-ai", "name": "Vertex AI (Gemini Enterprise Agent Platform)", "vendor": "Google Cloud", "vendorUrl": "https://cloud.google.com/products/gemini-enterprise-agent-platform", "kind": "model", "category": "inference", "summary": "Google Cloud's enterprise API for Gemini models and Model Garden partner and open models, including Claude, Llama and Qwen, on the platform formerly called Vertex AI, with regional endpoints, provisioned throughput and IAM access.", "url": "https://www.anchorterminal.com/tools/vertex-ai", "markdownUrl": "https://www.anchorterminal.com/tools/vertex-ai.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/vertex-ai.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/vertex-ai.json", "dns": "vertex-ai.grade.anchorterminal.com", "repo": "https://github.com/googleapis/python-genai", "license": "Proprietary service under the Google Cloud Platform terms. Partner models carry their providers' terms. The Google Gen AI SDKs are Apache-2.0", "transports": [ "http" ], "remoteUrl": "https://aiplatform.googleapis.com/v1", "packages": [ { "registry": "pypi", "name": "google-genai" }, { "registry": "npm", "name": "@google/genai" }, { "registry": "pypi", "name": "google-cloud-aiplatform" } ], "auth": "mixed", "authNotes": "OAuth 2.0 bearer tokens from application default credentials or service accounts, with IAM roles on a Google Cloud project, which the docs recommend for production. Google Cloud API keys, including express mode keys (Preview) that need no project or location in the URL, are recommended for testing. The OpenAI-compatible endpoint accepts only Google Cloud auth.", "pricing": "usage", "pricingNotes": "Per-token prices per model, with global and higher non-global rates and Standard, Priority and Flex/Batch options. Gemini 4 Argon costs $4/$20 per million, with 50% credits back through 2026-11-30. Gemini 3.8 Flash costs $0.75/$3.75 through 2026-12-31, then $1.50/$7.50. Claude Opus 5.5 $4/$20. Batch and Flex half price on Gemini. Only requests that return 200 are charged. Express mode gives new users 90 days free with no billing details (https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing).", "priceSummary": "from $0.30 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 on the pricing page or in the express mode docs (checked 2026-11-06). Access needs a Google account and, after the express trial, a Cloud billing account.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": 20917051, "asOf": "2026-11-06" }, "docsUrl": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/start", "rateLimitsUrl": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/standard-paygo", "openapi": "https://aiplatform.googleapis.com/$discovery/rest?version=v1", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "hosted", "model", "open-weights", "enterprise", "usage-priced", "free-tier", "no-card", "python", "typescript", "status-page" ], "lastRelease": "2026-11-05", "graded": true, "anchor": { "graded": true, "score": 88.7, "grade": "AA", "agentReady": true, "rank": 2, "ranked": true, "rankOf": 1510, "categoryRank": 1, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 97, "maintenance": 91, "payments": 40, "reliability": 99, "schema": 94, "security": 97, "transparency": 90 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "verdict": "Gemini, Claude and open models through one Google Cloud API with IAM, regional endpoints, schema-guaranteed JSON and a 99.5 per cent SLA, and no Vertex incident on the Cloud status page in the 90 days to 6 November 2026. Gemini 4 Argon and 3.8 Flash have 12-month availability, but short-term Flash models get a 95 per cent SLA.", "bestFor": "Google Cloud customers who need Gemini with residency, VPC-SC, provisioned throughput and an SLA, or Claude under a Google bill.", "strengths": [ "No incident naming Vertex or Gemini on status.cloud.google.com between 8 July and 6 October 2026", "Public discovery document for the v1 API (revision 20260930) with 1,128 methods and 1,493 schemas", "JSON output follows a supplied `response_schema` when `response_mime_type` is `application/json`", "Express mode gives new users 90 days free with an API key and no billing details", "Only requests that return 200 are charged", "Gemini 4 Argon, GA since 13 October 2026, has a 1,048,576-token unified limit at $4/$20 per million tokens" ], "weaknesses": [ "The SLA drops from 99.5 to 95 per cent for short-term availability models, Gemini 3.7 and 3.6 Flash among them", "Gemini 3.6 Flash, released 21 July 2026, retires on 19 November 2026, and 3.7 Flash on 28 January 2027", "Zero retention needs an exception request, and flagged prompts may be kept up to 90 days", "The Interactions API stores prompts and responses unless `store` is set to false", "No llms.txt on the docs site, and the docs mix the Vertex AI and Agent Platform names", "The model versions table still listed Gemini 2.5 Pro, Flash and Flash-Lite as available after their 20 October 2026 retirement date" ], "agentNotes": [ "Call the `global` location on aiplatform.googleapis.com unless data residency requires a Region. The 429 guide says it spreads load and reduces errors", "Back off exponentially on 429 `Resource exhausted`. On Standard PayGo it means shared capacity is busy, not a fixed quota", "Send `response_schema` with `response_mime_type: application/json`. JSON mode alone doesn't guarantee valid output", "Set `store` to false on Interactions API calls. It defaults to true and keeps prompts and responses", "Pin `gemini-4-argon` or `gemini-3.8-flash`, both in the 12-month tier, rather than 3.7 or 3.6 Flash, which retire on 28 January 2027 and 19 November 2026" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "AA", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 88.7 } ], "editorialScores": { "ergonomics": 97, "maintenance": 91, "payments": 40, "reliability": 99, "schema": 94, "security": 97, "transparency": 83 }, "provenanceScore": 97, "checked": { "categories": { "ergonomics": "2026-11-06", "maintenance": "2026-11-06", "payments": "2026-11-06", "reliability": "2026-11-06", "schema": "2026-11-06", "security": "2026-11-06", "transparency": "2026-11-06" }, "last": "2026-11-06", "oldest": "2026-11-06", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install google-genai # or: npm i @google/genai", "http": "curl -X POST \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $(gcloud auth print-access-token)\" \\\n \"https://aiplatform.googleapis.com/v1/projects/${GOOGLE_CLOUD_PROJECT}/locations/global/publishers/google/models/gemini-3.8-flash:generateContent\" \\\n -d '{\"contents\":{\"role\":\"user\",\"parts\":{\"text\":\"Explain how AI works in a few words\"}}}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/vertex-ai" }, "sameCompany": [ "gemini-api", "gemini-embedding", "vertex-ai-tuning", "cloud-run-gpus", "google-model-armor", "google-imagen", "google-veo", "google-lyria", "google-speech-to-text", "google-cloud-tts", "gemini-live", "google-adk", "google-memory-bank", "google-secret-manager", "google-cloud-document-ai", "google-weather-api", "chrome-devtools-mcp", "google-maps-platform", "google-cloud-translation", "google-calendar-api", "firebase-cloud-messaging", "google-cloud-storage", "google-drive-api", "gemini-enterprise", "gemini-cli", "google-search-console", "google-ads-api", "google-forms", "google-sheets-api", "gmail-api", "google-people-api" ], "area": "models", "unitPrices": [ { "item": "Grounding with Google Search over 5,000 a month (Gemini 3)", "unit": "1k-requests", "usd": 14 } ], "provenance": { "legalEntity": "Google LLC", "domain": "google.com", "domainRegistered": "1997-09-15", "domainNote": "The endpoint is on googleapis.com, Google's API domain. google.com was registered in 1997.", "endpointOnVendorDomain": true, "terms": "https://cloud.google.com/terms", "privacy": "https://policies.google.com/privacy", "statusPage": "https://status.cloud.google.com", "changelog": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/release-notes", "securityTxt": "valid", "checked": "2026-11-06", "notes": [ "The product runs under the Google Cloud Platform terms, whose contracting Google entity depends on the billing country, as for vertex-ai-tuning.", "www.google.com/.well-known/security.txt expires on 2030-04-01 (read 2026-11-06).", "docs.cloud.google.com has no llms.txt (404 on 6 October 2026), but each docs page answers as Markdown when `.md.txt` is added to its URL." ], "score": 97 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/vertex-ai.json", "live": { "slug": "vertex-ai", "probe": { "target": "https://aiplatform.googleapis.com/v1", "method": "get", "lastAt": "2026-11-07T19:22:43.041024218Z", "lastOk": true, "lastStatus": 404, "lastMs": 664, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 118, "p95ms24h": 752, "samples24h": 210, "samples30d": 210, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 13 }, { "date": "2026-11-07", "probes": 197, "ok": 197 } ] }, "versions": [ { "registry": "github", "name": "googleapis/python-genai", "version": "v3.0.0", "released": "2026-11-06", "seenAt": "2026-11-07T00:15:33.519504561Z" }, { "registry": "npm", "name": "@google/genai", "version": "3.0.0", "seenAt": "2026-11-07T00:15:31.639429892Z" }, { "registry": "pypi", "name": "google-cloud-aiplatform", "version": "2.7.0", "released": "2026-10-28", "seenAt": "2026-11-07T00:15:32.521225598Z" }, { "registry": "pypi", "name": "google-genai", "version": "3.0.0", "released": "2026-11-06", "seenAt": "2026-11-07T00:15:31.485691571Z" } ], "githubStars": 4057, "npmWeekly": 31989360, "pypiWeekly": 38431674, "securityTxt": { "url": "https://google.com/.well-known/security.txt", "state": "valid", "expires": "2030-04-01T00:00:00z", "checkedAt": "2026-11-07T16:01:22.068349931Z" }, "pages": [ { "url": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:01:16.257808105Z", "changedAt": "2026-11-07T14:01:16.257808105Z", "fingerprint": "a4fe253bd23f" } ], "updatedAt": "2026-11-07T19:22:43.041024218Z" } }, "edges": [ { "by": 71, "category": "reliability", "leads": "vertex-ai", "name": "Reliability", "reasons": { "a": "No status page read. status.stepfun.ai refused our reader by robots.txt and the shell couldn't connect, so we couldn't establish whether it is a status page or read any history. Scored absent for both lines, with 5 for unreadable history, and named in the open questions (0 + 5). Rate limits published with numbers per tier, from 5 concurrent, 100 RPM and 500,000 TPM to 130, 2,600 and 13,000,000 (15). The error and exception guides say to retry 429, 500, 503 and 504 after a short delay, with no Retry-After header, backoff schedule or idempotency guidance (8 of 15). No SLA found in the terms or pricing (0). Step 5 Preview is labelled a preview (0).", "b": "Google Cloud status dashboard with per-product history (20). Its incident feed, read on 6 November, has no incident naming Vertex Gemini API, Gemini or the Agent Platform in the 90 days. The regional incidents of 20 August, 1 September and 20 October (europe-west2) and the Cloud Storage incident of 8 and 9 October didn't list it among affected products (30). Standard PayGo publishes usage tiers by 30-day spend with baseline throughput, 2,000,000 to 50,000,000 tokens a minute for Flash models and 500,000 to 10,000,000 for Pro, plus quota tables for other methods (15). A 429 page says to use the global endpoint and truncated exponential backoff, and a retry-strategy page (15). SLA of 99.5 per cent a month on generateContent and streamGenerateContent, 95 per cent for short-term availability models, and a latency SLO on Provisioned Throughput. The 429 page says pay-as-you-go 429s don't count toward the SLA error rate (10). Gemini 4 Argon reached GA on 13 October and Gemini 3.8 Flash moved to the 12-month tier, and the v1 API, 3.5 Flash-Lite and Claude Opus 5.5 are GA, but express mode was Preview at the 6 October check (9 of 10, up from 8). Up from 98 on 6 October." }, "scores": { "a": 28, "b": 99 } }, { "by": 56, "category": "security", "leads": "vertex-ai", "name": "Security \u0026 auth", "reasons": { "a": "Model reading. Bearer API keys, revocable by deletion. Organisations can create one key per project, billed to a project's credit with a per-member cap. No scopes or read-only keys found (20 of 30). Training on API data is not off by default in plain words. The privacy policy (effective 7 August 2026) says StepFun may use and retain data to improve its models, including training and fine-tuning where law and program terms permit, and the terms name early-access programmes as one such case. No opt-out found (5 of 20). No retention period for prompts and outputs and no zero-retention option. IP addresses are kept three years (3 of 15). The console's usage details list each billed call by key, model and date, with export (8 of 15). No security.txt, bug bounty or certification found. A DPA with breach notification exists (5 of 20).", "b": "Model reading. OAuth 2.0 with IAM roles and service accounts, which the docs recommend for production, with API keys for testing. No key in a query string found in the docs we read (30). The training restriction in the Service Specific Terms says Google won't use customer data to train or fine-tune any model without permission, GA and pre-GA alike (20). Default in-memory caching for 24 hours that can be disabled, flagged prompts logged up to 90 days unless an abuse-monitoring exception is granted or the customer has a Cloud Master Agreement, the Interactions API storing by default, and Claude Fable 5 and Mythos 5 requiring 30-day retention shared with Anthropic (12 of 15, a judgement call matching the Fable exception on the Anthropic and Bedrock listings). Cloud Audit Logs, with Data Access logs off until enabled, and optional request-response logging to BigQuery (15). google.com security.txt valid to 2030-04-01, the Google VRP, and Generative AI on the platform in ISO 27001, 27017 and 27018 and SOC 1, 2 and 3 scope per the 1 October services-in-scope check for vertex-ai-tuning, not re-read on 6 October (20)." }, "scores": { "a": 41, "b": 97 } }, { "by": 41, "category": "schema", "leads": "vertex-ai", "name": "Schema \u0026 documentation", "reasons": { "a": "No OpenAPI or similar machine-readable contract found. The API reference is Markdown pages (0). llms.txt at platform.stepfun.ai/docs/llms.txt, and every page has a Markdown copy (10). The Chat Completions reference describes each parameter with its default, and the model page lists what Step 5 Preview supports, but little on when not to use an option (12 of 20). Tool definitions take JSON Schema parameters, structured output takes a JSON Schema with `strict: true`, and `reasoning_effort` is an enum of low, medium and high. No `tool_choice` parameter is documented (11 of 15). Worked requests and responses on each page, and an error table of eight codes with causes and fixes, but no error bodies (12 of 15). No API changelog. A model lifecycle page with dated retirements and announcement pages (8 of 15).", "b": "Model reading. Keyless discovery document for the Agent Platform API v1, revision 20260930, with 1,128 methods and 1,493 schemas (25). No llms.txt, but every docs page answers as Markdown at `.md.txt`, counted as for vertex-ai-tuning (10). Model cards give limits, capabilities and retirement dates, and the 3.8 Flash card says when to use 3.7 Flash instead, but the docs mix the Vertex AI and Agent Platform names, and the OpenAI page tells new users to call the Gemini Developer API instead (16 of 20). Structured output with `response_schema` and `response_mime_type: application/json` always follows the schema per the docs, and complex schemas fail with a 400 (15). Examples on every page and a 429 guide, but we found no full error code list for generateContent (13 of 15). Versioned v1 and v1beta1 APIs and release notes with entries on most working days, newest 5 November 2026 (15)." }, "scores": { "a": 53, "b": 94 } }, { "by": 41, "category": "maintenance", "leads": "vertex-ai", "name": "Maintenance \u0026 community", "reasons": { "a": "Model reading. The image models `step-2x-large` and `step-image-edit-2` were retired on 10 October 2026, and a Step 5 Preview price change is announced for 14 October (30). No stated notice period. The 10 October image retirement had a dated notice page and the July retirements a migration table, but we couldn't date when either notice went up (4 of 12). One retirement date in the last 90 days, 10 October, with nine models retired on 8 July just outside that window (6 of 8). Dated announcements, a Discord server and platform@stepfun.com for support. We didn't test whether either answers (10 of 15). No official SDK (0 of 15, 0 of 10).", "b": "Model reading. Gemini Omni 1.2 Flash GA on 5 November, Grok 4.7 GA on 27 October, Gemini 4 Argon GA on 13 October and Claude Haiku 5.5 on 7 October 2026 (30). Stable models stay at least 12 months, and since 6 October Gemini 4 Argon and Gemini 3.8 Flash are in that tier, while 3.7 and 3.6 Flash remain short-term with at least 45 days' notice once a date is set (10 of 12, up from 8). Gemini 2.5 Pro, Flash and Flash-Lite were due to retire on 20 October, three models on one date after more than 12 months, with replacements named. We didn't check partner model retirements (6 of 8, down from 8). Dated release notes on most working days, newest 5 November, and Cloud Customer Care (15). python-genai replies not sampled this run (5 of 10). Current SDKs, google-genai 3.0.0 on 6 November and `@google/genai` 3.0.0, and google-cloud-aiplatform 2.7.0 on 28 October 2026 (15). Supported runtimes stated, Python 3.10 or later and Node 20 or later, per the 6 October check (10). Unchanged at 91." }, "scores": { "a": 50, "b": 91 } }, { "by": 33, "category": "transparency", "leads": "vertex-ai", "name": "Transparency \u0026 trust", "reasons": { "a": "Closed service with clear terms under Hong Kong law, with HKIAC arbitration and liability capped at six months of fees. Some earlier Step models have open weights, which doesn't change the hosted service (15). The privacy policy, terms and DPA agree that data may be used for training under program terms, but the terms' licence to Content is broad and perpetual, no retention period is given for prompts and outputs, and no subprocessor list was found (12 of 30). A model lifecycle page with dated retirements and replacements (14 of 20). Servers are disclosed as in the United States. The DPA gives general authorisation for subprocessors without a published list (10 of 20).", "b": "Closed service under the Google Cloud terms, with the Gen AI SDKs under Apache-2.0 and a public discovery document (18, as for Bedrock's open service models). The zero data retention and abuse monitoring pages agree with the Cloud terms and give periods for each case, 24 hours in memory, up to 90 days for flagged prompts, 30 days for Advanced AI models, 3 days for Search grounding logs and 30 days for Maps grounding, and say which can't be switched off (27 of 30). A dated model versions table with release and retirement dates and a stated 12-month or 45-day policy, but on 6 November it still listed Gemini 2.5 Pro, Flash and Flash-Lite as available with a 20 October 2026 retirement date and left them out of the retired table (18 of 20, down from 20). The Cloud subprocessor list with locations, per the 1 October vertex-ai-tuning check, regional and multi-region endpoints, and per-model ML processing locations on the partner model cards (20)." }, "scores": { "a": 57, "b": 90 } }, { "by": 29, "category": "ergonomics", "leads": "vertex-ai", "name": "Agent ergonomics", "reasons": { "a": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool calls through Chat Completions, Responses and Messages, with no documented way to force or forbid a call (15 of 20). Strict JSON Schema output on Step 5 Preview (13 of 15). Prompt caching with a published cache-hit price at a tenth of the miss price (15). 1M-token context and 64k output (15). No batch endpoint found (0). No official SDK. The docs use the OpenAI and Anthropic clients against compatible endpoints (0). Eight error codes with a fix each, plus `finish_reason` handling for length, content filter and tool calls (10 of 15).", "b": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Function calling with `FunctionCallingConfig` mode ANY and `allowedFunctionNames` to force a named tool (20). Schema-guaranteed JSON output (15). Implicit and explicit context caching, cached input at 0.1x, $0.075 per million on 3.8 Flash through 31 December (15). 1,048,576-token context on 3.8 Flash, a unified 1,048,576-token input and output limit on Gemini 4 Argon, and 1,000,000 on Claude Opus 5.5 (15). Flex/Batch at half price on Gemini (10). Gen AI SDKs for Python and JavaScript among others, and the OpenAI libraries work with Google Cloud auth (10). 429 handling documented per quota framework, with standard Google status codes elsewhere (12 of 15)." }, "scores": { "a": 68, "b": 97 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "StepFun", "b": "Google Cloud", "name": "Vendor" }, { "a": "https://api.stepfun.ai/v1", "b": "https://aiplatform.googleapis.com/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "OAuth or key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Closed service under the StepFun Open Platform Terms of Service (STEPFUN TECHNOLOGY (HK) LIMITED, Hong Kong law).", "b": "Proprietary service under the Google Cloud Platform terms. Partner models carry their providers' terms. The Google Gen AI SDKs are Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "no", "name": "llms.txt" }, { "a": "none", "b": "2026-11-05", "name": "Last release" }, { "a": "couldn't be read", "b": "2026-09-02", "name": "Terms last updated" }, { "a": "couldn't be read", "b": "2026-10-01", "name": "Privacy policy last updated" }, { "a": "couldn't be read", "b": "yes", "name": "Customer content may train models" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "20.9M PyPI/wk", "name": "Popularity" }, { "a": "3.3/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against StepFun API's 44.3 (E), and leads in every scored category.", "question": "Which is better for AI agents, StepFun API or Vertex AI (Gemini Enterprise Agent Platform)?" }, { "answer": "StepFun API needs an API key. Vertex AI (Gemini Enterprise Agent Platform) takes an API key or an OAuth sign-in.", "question": "Do StepFun API and Vertex AI (Gemini Enterprise Agent Platform) need an API key?" }, { "answer": "Yes. StepFun API has a hosted endpoint at https://api.stepfun.ai/v1 and Vertex AI (Gemini Enterprise Agent Platform) at https://aiplatform.googleapis.com/v1.", "question": "Can an agent call StepFun API and Vertex AI (Gemini Enterprise Agent Platform) without installing anything?" } ], "goodFor": [ { "aheadOn": null, "also": null, "goodFor": "Long-context agent and coding work over text, screenshots and video at a low per-token price, where a preview model is acceptable.", "slug": "stepfun-api", "watchFor": "Step 5 Preview is labelled a preview, and no release date or support commitment was found" }, { "aheadOn": [ "Reliability, 99 against 28", "Schema \u0026 documentation, 94 against 53", "Agent ergonomics, 97 against 68", "Security \u0026 auth, 97 against 41", "Payments \u0026 pricing, 40 against 20", "Maintenance \u0026 community, 91 against 50", "Transparency \u0026 trust, 90 against 57" ], "also": [ "Agent-ready, a grade of BB or better", "Free to start without a card" ], "goodFor": "Google Cloud customers who need Gemini with residency, VPC-SC, provisioned throughput and an SLA, or Claude under a Google bill.", "slug": "vertex-ai", "watchFor": "The SLA drops from 99.5 to 95 per cent for short-term availability models, Gemini 3.7 and 3.6 Flash among them" } ], "history": { "stepfun-api": [ { "causes": [ "correction" ], "date": "2026-10-28", "delta": -0.1, "from": 44.4, "fromGrade": "E", "to": 44.3, "toGrade": "E" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.3, "from": 44.1, "fromGrade": "E", "to": 44.4, "toGrade": "E" } ], "vertex-ai": null }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-stepfun-api.json", "title": "Amazon Bedrock vs StepFun API", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-vertex-ai.json", "title": "Amazon Bedrock vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-stepfun-api.json", "title": "Claude API vs StepFun API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-vertex-ai.json", "title": "Claude API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-stepfun-api.json", "title": "Antseed vs StepFun API", "url": "https://www.anchorterminal.com/compare/antseed-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-vertex-ai.json", "title": "Antseed vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/antseed-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-stepfun-api.json", "title": "Azure OpenAI in Foundry Models vs StepFun API", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-vertex-ai.json", "title": "Azure OpenAI in Foundry Models vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-stepfun-api.json", "title": "BlockRun.AI vs StepFun API", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-vertex-ai.json", "title": "BlockRun.AI vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-stepfun-api.json", "title": "Cerebras Inference vs StepFun API", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-vertex-ai.json", "title": "Cerebras Inference vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-stepfun-api.json", "title": "Cloudflare AI Gateway vs StepFun API", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-vertex-ai.json", "title": "Cloudflare AI Gateway vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-stepfun-api.json", "title": "Cloudflare Workers AI vs StepFun API", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-vertex-ai.json", "title": "Cloudflare Workers AI vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-stepfun-api.json", "title": "Cohere Chat API (Command models) vs StepFun API", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-vertex-ai.json", "title": "Cohere Chat API (Command models) vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-stepfun-api.json", "title": "DeepInfra vs StepFun API", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-vertex-ai.json", "title": "DeepInfra vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-stepfun-api.json", "title": "DeepSeek API vs StepFun API", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-vertex-ai.json", "title": "DeepSeek API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-stepfun-api.json", "title": "Eden AI vs StepFun API", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-vertex-ai.json", "title": "Eden AI vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-stepfun-api.json", "title": "Glimpse vs StepFun API", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-vertex-ai.json", "title": "Glimpse vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-stepfun-api.json", "title": "Fireworks AI Inference vs StepFun API", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-vertex-ai.json", "title": "Fireworks AI Inference vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-stepfun-api.json", "title": "Gemini Developer API vs StepFun API", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-vertex-ai.json", "title": "Gemini Developer API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-stepfun-api.json", "title": "GroqCloud vs StepFun API", "url": "https://www.anchorterminal.com/compare/groq-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-vertex-ai.json", "title": "GroqCloud vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/groq-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-stepfun-api.json", "title": "Hugging Face Inference Providers vs StepFun API", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vertex-ai.json", "title": "Hugging Face Inference Providers vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-stepfun-api.json", "title": "Inkling 2 Small vs StepFun API", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-vertex-ai.json", "title": "Inkling 2 Small vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-stepfun-api.json", "title": "Jais 3 vs StepFun API", "url": "https://www.anchorterminal.com/compare/jais-3-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-vertex-ai.json", "title": "Jais 3 vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/jais-3-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-stepfun-api.json", "title": "Meta Model API vs StepFun API", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-vertex-ai.json", "title": "Meta Model API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-stepfun-api.json", "title": "MiniMax API vs StepFun API", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-vertex-ai.json", "title": "MiniMax API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-stepfun-api.json", "title": "Mistral AI API vs StepFun API", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-vertex-ai.json", "title": "Mistral AI API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-stepfun-api.json", "title": "Muse Spark Open vs StepFun API", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-vertex-ai.json", "title": "Muse Spark Open vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-stepfun-api.json", "title": "Nemotron 3.5 Super VL vs StepFun API", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-stepfun-api.json", "title": "Novita AI vs StepFun API", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-vertex-ai.json", "title": "Novita AI vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-vertex-ai" }, { "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-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/openrouter-vs-stepfun-api.json", "title": "OpenRouter vs StepFun API", "url": "https://www.anchorterminal.com/compare/openrouter-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/openrouter-vs-vertex-ai.json", "title": "OpenRouter vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/openrouter-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/prism-inference-vs-stepfun-api.json", "title": "Prism Inference vs StepFun API", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/prism-inference-vs-vertex-ai.json", "title": "Prism Inference vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-stepfun-api.json", "title": "Router.com (Ramp Router) vs StepFun API", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-vertex-ai.json", "title": "Router.com (Ramp Router) vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-stepfun-api.json", "title": "Beam 1.0 vs StepFun API", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-vertex-ai.json", "title": "Beam 1.0 vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/routerplus-vs-stepfun-api.json", "title": "RouterPlus vs StepFun API", "url": "https://www.anchorterminal.com/compare/routerplus-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/routerplus-vs-vertex-ai.json", "title": "RouterPlus vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/routerplus-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-stepfun-api.json", "title": "SambaCloud vs StepFun API", "url": "https://www.anchorterminal.com/compare/sambanova-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-vertex-ai.json", "title": "SambaCloud vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/sambanova-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/siliconflow-vs-stepfun-api.json", "title": "SiliconFlow vs StepFun API", "url": "https://www.anchorterminal.com/compare/siliconflow-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/siliconflow-vs-vertex-ai.json", "title": "SiliconFlow vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/siliconflow-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-stepfun-api.json", "title": "Simplismart vs StepFun API", "url": "https://www.anchorterminal.com/compare/simplismart-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-vertex-ai.json", "title": "Simplismart vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/simplismart-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/stepfun-api-vs-swe-2-flash.json", "title": "StepFun API vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/stepfun-api-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/stepfun-api-vs-tencent-tokenhub.json", "title": "StepFun API vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/stepfun-api-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/stepfun-api-vs-together-inference.json", "title": "StepFun API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/stepfun-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/stepfun-api-vs-vercel-ai-gateway.json", "title": "StepFun API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/stepfun-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/stepfun-api-vs-xai-api.json", "title": "StepFun API vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/stepfun-api-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/swe-2-flash-vs-vertex-ai.json", "title": "SWE-2 Flash vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/swe-2-flash-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-vertex-ai.json", "title": "Tencent Cloud TokenHub vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/together-inference-vs-vertex-ai.json", "title": "Together AI Inference vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/together-inference-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-vertex-ai.json", "title": "Vercel AI Gateway vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/vertex-ai-vs-xai-api.json", "title": "Vertex AI (Gemini Enterprise Agent Platform) vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/vertex-ai-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-vertex-ai.json", "title": "Nemotron 3.5 Super VL vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-vertex-ai" } ], "panel": null, "scores": [ { "by": 71, "edge": "vertex-ai", "key": "reliability", "name": "Reliability", "stepfun-api": 28, "vertex-ai": 99, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 41, "edge": "vertex-ai", "key": "schema", "name": "Schema \u0026 documentation", "stepfun-api": 53, "vertex-ai": 94, "weight": 13 }, { "by": 29, "edge": "vertex-ai", "key": "ergonomics", "name": "Agent ergonomics", "stepfun-api": 68, "vertex-ai": 97, "weight": 13 }, { "by": 56, "edge": "vertex-ai", "key": "security", "name": "Security \u0026 auth", "stepfun-api": 41, "vertex-ai": 97, "weight": 14 }, { "by": 20, "edge": "vertex-ai", "key": "payments", "name": "Payments \u0026 pricing", "stepfun-api": 20, "vertex-ai": 40, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 41, "edge": "vertex-ai", "key": "maintenance", "name": "Maintenance \u0026 community", "stepfun-api": 50, "vertex-ai": 91, "weight": 7 }, { "by": 33, "edge": "vertex-ai", "key": "transparency", "name": "Transparency \u0026 trust", "stepfun-api": 57, "vertex-ai": 90, "weight": 7 } ], "summary": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against StepFun API's 44.3 (E), and leads in every scored category. Both do llm inference.", "tasks": [ { "a": "$1.38", "b": "$22.03", "cheaper": "stepfun-api", "task": "Research a product and write a sourced report", "what": "step-5-preview on StepFun API, gemini-3.1-pro-preview on Vertex AI (Gemini Enterprise Agent Platform)" }, { "a": "$0.44", "b": "$5.09", "cheaper": "stepfun-api", "task": "Build a small four-page website", "what": "step-5-preview on StepFun API, gemini-3.1-pro-preview on Vertex AI (Gemini Enterprise Agent Platform)" }, { "a": "$0.11", "b": "$1.09", "cheaper": "stepfun-api", "task": "Find and fix a bug in a large codebase", "what": "step-5-preview on StepFun API, gemini-3.1-pro-preview on Vertex AI (Gemini Enterprise Agent Platform)" } ], "tutorials": [], "verdicts": { "stepfun-api": "StepFun's API serves Step 5 Preview with a 1M-token context, video input, strict JSON Schema output and published per-token prices, documented in Markdown with an llms.txt. The model is a preview with no release date found, there's no free allowance or SLA, and the terms and privacy policy leave room to train on customer data.", "vertex-ai": "Gemini, Claude and open models through one Google Cloud API with IAM, regional endpoints, schema-guaranteed JSON and a 99.5 per cent SLA, and no Vertex incident on the Cloud status page in the 90 days to 6 November 2026. Gemini 4 Argon and 3.8 Flash have 12-month availability, but short-term Flash models get a 95 per cent SLA." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/stepfun-api-vs-vertex-ai", "json": "https://www.anchorterminal.com/compare/stepfun-api-vs-vertex-ai.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/stepfun-api-vs-vertex-ai.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/stepfun-api-vs-vertex-ai.min.md" }, "markdown": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against StepFun API's 44.3 (E), and leads in every scored category. Both do llm inference.\n\n- StepFun API: grade E, 44.3/100, rank #1223 of 1510. Markdown https://www.anchorterminal.com/tools/stepfun-api.md · JSON https://www.anchorterminal.com/api/v1/tools/stepfun-api.json\n- Vertex AI (Gemini Enterprise Agent Platform): grade AA, 88.7/100, rank #2 of 1510. Markdown https://www.anchorterminal.com/tools/vertex-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/vertex-ai.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 830 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### StepFun API (E)\n\nGood for: Long-context agent and coding work over text, screenshots and video at a low per-token price, where a preview model is acceptable.\n\nWatch for: Step 5 Preview is labelled a preview, and no release date or support commitment was found\n\n### Vertex AI (Gemini Enterprise Agent Platform) (AA)\n\nGood for: Google Cloud customers who need Gemini with residency, VPC-SC, provisioned throughput and an SLA, or Claude under a Google bill.\n\nAhead on:\n- Reliability, 99 against 28\n- Schema \u0026 documentation, 94 against 53\n- Agent ergonomics, 97 against 68\n- Security \u0026 auth, 97 against 41\n- Payments \u0026 pricing, 40 against 20\n- Maintenance \u0026 community, 91 against 50\n- Transparency \u0026 trust, 90 against 57\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- Free to start without a card\n\nWatch for: The SLA drops from 99.5 to 95 per cent for short-term availability models, Gemini 3.7 and 3.6 Flash among them\n\n\n## Why the edge\n\n### Reliability: Vertex AI (Gemini Enterprise Agent Platform) +71\n\n- StepFun API (28): No status page read. status.stepfun.ai refused our reader by robots.txt and the shell couldn't connect, so we couldn't establish whether it is a status page or read any history. Scored absent for both lines, with 5 for unreadable history, and named in the open questions (0 + 5). Rate limits published with numbers per tier, from 5 concurrent, 100 RPM and 500,000 TPM to 130, 2,600 and 13,000,000 (15). The error and exception guides say to retry 429, 500, 503 and 504 after a short delay, with no Retry-After header, backoff schedule or idempotency guidance (8 of 15). No SLA found in the terms or pricing (0). Step 5 Preview is labelled a preview (0).\n- Vertex AI (Gemini Enterprise Agent Platform) (99): Google Cloud status dashboard with per-product history (20). Its incident feed, read on 6 November, has no incident naming Vertex Gemini API, Gemini or the Agent Platform in the 90 days. The regional incidents of 20 August, 1 September and 20 October (europe-west2) and the Cloud Storage incident of 8 and 9 October didn't list it among affected products (30). Standard PayGo publishes usage tiers by 30-day spend with baseline throughput, 2,000,000 to 50,000,000 tokens a minute for Flash models and 500,000 to 10,000,000 for Pro, plus quota tables for other methods (15). A 429 page says to use the global endpoint and truncated exponential backoff, and a retry-strategy page (15). SLA of 99.5 per cent a month on generateContent and streamGenerateContent, 95 per cent for short-term availability models, and a latency SLO on Provisioned Throughput. The 429 page says pay-as-you-go 429s don't count toward the SLA error rate (10). Gemini 4 Argon reached GA on 13 October and Gemini 3.8 Flash moved to the 12-month tier, and the v1 API, 3.5 Flash-Lite and Claude Opus 5.5 are GA, but express mode was Preview at the 6 October check (9 of 10, up from 8). Up from 98 on 6 October.\n\n### Security \u0026 auth: Vertex AI (Gemini Enterprise Agent Platform) +56\n\n- StepFun API (41): Model reading. Bearer API keys, revocable by deletion. Organisations can create one key per project, billed to a project's credit with a per-member cap. No scopes or read-only keys found (20 of 30). Training on API data is not off by default in plain words. The privacy policy (effective 7 August 2026) says StepFun may use and retain data to improve its models, including training and fine-tuning where law and program terms permit, and the terms name early-access programmes as one such case. No opt-out found (5 of 20). No retention period for prompts and outputs and no zero-retention option. IP addresses are kept three years (3 of 15). The console's usage details list each billed call by key, model and date, with export (8 of 15). No security.txt, bug bounty or certification found. A DPA with breach notification exists (5 of 20).\n- Vertex AI (Gemini Enterprise Agent Platform) (97): Model reading. OAuth 2.0 with IAM roles and service accounts, which the docs recommend for production, with API keys for testing. No key in a query string found in the docs we read (30). The training restriction in the Service Specific Terms says Google won't use customer data to train or fine-tune any model without permission, GA and pre-GA alike (20). Default in-memory caching for 24 hours that can be disabled, flagged prompts logged up to 90 days unless an abuse-monitoring exception is granted or the customer has a Cloud Master Agreement, the Interactions API storing by default, and Claude Fable 5 and Mythos 5 requiring 30-day retention shared with Anthropic (12 of 15, a judgement call matching the Fable exception on the Anthropic and Bedrock listings). Cloud Audit Logs, with Data Access logs off until enabled, and optional request-response logging to BigQuery (15). google.com security.txt valid to 2030-04-01, the Google VRP, and Generative AI on the platform in ISO 27001, 27017 and 27018 and SOC 1, 2 and 3 scope per the 1 October services-in-scope check for vertex-ai-tuning, not re-read on 6 October (20).\n\n### Schema \u0026 documentation: Vertex AI (Gemini Enterprise Agent Platform) +41\n\n- StepFun API (53): No OpenAPI or similar machine-readable contract found. The API reference is Markdown pages (0). llms.txt at platform.stepfun.ai/docs/llms.txt, and every page has a Markdown copy (10). The Chat Completions reference describes each parameter with its default, and the model page lists what Step 5 Preview supports, but little on when not to use an option (12 of 20). Tool definitions take JSON Schema parameters, structured output takes a JSON Schema with `strict: true`, and `reasoning_effort` is an enum of low, medium and high. No `tool_choice` parameter is documented (11 of 15). Worked requests and responses on each page, and an error table of eight codes with causes and fixes, but no error bodies (12 of 15). No API changelog. A model lifecycle page with dated retirements and announcement pages (8 of 15).\n- Vertex AI (Gemini Enterprise Agent Platform) (94): Model reading. Keyless discovery document for the Agent Platform API v1, revision 20260930, with 1,128 methods and 1,493 schemas (25). No llms.txt, but every docs page answers as Markdown at `.md.txt`, counted as for vertex-ai-tuning (10). Model cards give limits, capabilities and retirement dates, and the 3.8 Flash card says when to use 3.7 Flash instead, but the docs mix the Vertex AI and Agent Platform names, and the OpenAI page tells new users to call the Gemini Developer API instead (16 of 20). Structured output with `response_schema` and `response_mime_type: application/json` always follows the schema per the docs, and complex schemas fail with a 400 (15). Examples on every page and a 429 guide, but we found no full error code list for generateContent (13 of 15). Versioned v1 and v1beta1 APIs and release notes with entries on most working days, newest 5 November 2026 (15).\n\n### Maintenance \u0026 community: Vertex AI (Gemini Enterprise Agent Platform) +41\n\n- StepFun API (50): Model reading. The image models `step-2x-large` and `step-image-edit-2` were retired on 10 October 2026, and a Step 5 Preview price change is announced for 14 October (30). No stated notice period. The 10 October image retirement had a dated notice page and the July retirements a migration table, but we couldn't date when either notice went up (4 of 12). One retirement date in the last 90 days, 10 October, with nine models retired on 8 July just outside that window (6 of 8). Dated announcements, a Discord server and platform@stepfun.com for support. We didn't test whether either answers (10 of 15). No official SDK (0 of 15, 0 of 10).\n- Vertex AI (Gemini Enterprise Agent Platform) (91): Model reading. Gemini Omni 1.2 Flash GA on 5 November, Grok 4.7 GA on 27 October, Gemini 4 Argon GA on 13 October and Claude Haiku 5.5 on 7 October 2026 (30). Stable models stay at least 12 months, and since 6 October Gemini 4 Argon and Gemini 3.8 Flash are in that tier, while 3.7 and 3.6 Flash remain short-term with at least 45 days' notice once a date is set (10 of 12, up from 8). Gemini 2.5 Pro, Flash and Flash-Lite were due to retire on 20 October, three models on one date after more than 12 months, with replacements named. We didn't check partner model retirements (6 of 8, down from 8). Dated release notes on most working days, newest 5 November, and Cloud Customer Care (15). python-genai replies not sampled this run (5 of 10). Current SDKs, google-genai 3.0.0 on 6 November and `@google/genai` 3.0.0, and google-cloud-aiplatform 2.7.0 on 28 October 2026 (15). Supported runtimes stated, Python 3.10 or later and Node 20 or later, per the 6 October check (10). Unchanged at 91.\n\n### Transparency \u0026 trust: Vertex AI (Gemini Enterprise Agent Platform) +33\n\n- StepFun API (57): Closed service with clear terms under Hong Kong law, with HKIAC arbitration and liability capped at six months of fees. Some earlier Step models have open weights, which doesn't change the hosted service (15). The privacy policy, terms and DPA agree that data may be used for training under program terms, but the terms' licence to Content is broad and perpetual, no retention period is given for prompts and outputs, and no subprocessor list was found (12 of 30). A model lifecycle page with dated retirements and replacements (14 of 20). Servers are disclosed as in the United States. The DPA gives general authorisation for subprocessors without a published list (10 of 20).\n- Vertex AI (Gemini Enterprise Agent Platform) (90): Closed service under the Google Cloud terms, with the Gen AI SDKs under Apache-2.0 and a public discovery document (18, as for Bedrock's open service models). The zero data retention and abuse monitoring pages agree with the Cloud terms and give periods for each case, 24 hours in memory, up to 90 days for flagged prompts, 30 days for Advanced AI models, 3 days for Search grounding logs and 30 days for Maps grounding, and say which can't be switched off (27 of 30). A dated model versions table with release and retirement dates and a stated 12-month or 45-day policy, but on 6 November it still listed Gemini 2.5 Pro, Flash and Flash-Lite as available with a 20 October 2026 retirement date and left them out of the retired table (18 of 20, down from 20). The Cloud subprocessor list with locations, per the 1 October vertex-ai-tuning check, regional and multi-region endpoints, and per-model ML processing locations on the partner model cards (20).\n\n### Agent ergonomics: Vertex AI (Gemini Enterprise Agent Platform) +29\n\n- StepFun API (68): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool calls through Chat Completions, Responses and Messages, with no documented way to force or forbid a call (15 of 20). Strict JSON Schema output on Step 5 Preview (13 of 15). Prompt caching with a published cache-hit price at a tenth of the miss price (15). 1M-token context and 64k output (15). No batch endpoint found (0). No official SDK. The docs use the OpenAI and Anthropic clients against compatible endpoints (0). Eight error codes with a fix each, plus `finish_reason` handling for length, content filter and tool calls (10 of 15).\n- Vertex AI (Gemini Enterprise Agent Platform) (97): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Function calling with `FunctionCallingConfig` mode ANY and `allowedFunctionNames` to force a named tool (20). Schema-guaranteed JSON output (15). Implicit and explicit context caching, cached input at 0.1x, $0.075 per million on 3.8 Flash through 31 December (15). 1,048,576-token context on 3.8 Flash, a unified 1,048,576-token input and output limit on Gemini 4 Argon, and 1,000,000 on Claude Opus 5.5 (15). Flex/Batch at half price on Gemini (10). Gen AI SDKs for Python and JavaScript among others, and the OpenAI libraries work with Google Cloud auth (10). 429 handling documented per quota framework, with standard Google status codes elsewhere (12 of 15).\n\n## Score by category\n\n| Category | Weight | StepFun API | Vertex AI (Gemini Enterprise Agent Platform) | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 28 | 99 | Vertex AI (Gemini Enterprise Agent Platform) +71 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 53 | 94 | Vertex AI (Gemini Enterprise Agent Platform) +41 |\n| Agent ergonomics | 13% (16.2 this run) | 68 | 97 | Vertex AI (Gemini Enterprise Agent Platform) +29 |\n| Security \u0026 auth | 14% (17.5 this run) | 41 | 97 | Vertex AI (Gemini Enterprise Agent Platform) +56 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 40 | Vertex AI (Gemini Enterprise Agent Platform) +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 50 | 91 | Vertex AI (Gemini Enterprise Agent Platform) +41 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 57 | 90 | Vertex AI (Gemini Enterprise Agent Platform) +33 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **44.3 · E** | **88.7 · AA** | |\n\n## Facts side by side\n\n| Fact | StepFun API | Vertex AI (Gemini Enterprise Agent Platform) |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | StepFun | Google Cloud |\n| Hosted endpoint | `https://api.stepfun.ai/v1` | `https://aiplatform.googleapis.com/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | OAuth or key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | Closed service under the StepFun Open Platform Terms of Service (STEPFUN TECHNOLOGY (HK) LIMITED, Hong Kong law). | Proprietary service under the Google Cloud Platform terms. Partner models carry their providers' terms. The Google Gen AI SDKs are Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| Last release | none | 2026-11-05 |\n| Terms last updated | couldn't be read | 2026-09-02 |\n| Privacy policy last updated | couldn't be read | 2026-10-01 |\n| Customer content may train models | couldn't be read | yes |\n| Terms restrict automated access | couldn't be read | not found in the text |\n| Terms restrict benchmarking | couldn't be read | not found in the text |\n| Terms or service can change without notice | couldn't be read | not found in the text |\n| Arbitration or class-action waiver | couldn't be read | not found in the text |\n| Popularity | none | 20.9M PyPI/wk |\n| Agent reviews | 3.3/5 (4) | none |\n\n## What the same task costs\n\n| Task | StepFun API | Vertex AI (Gemini Enterprise Agent Platform) |\n| --- | --- | --- |\n| Research a product and write a sourced report | $1.38 | $22.03 |\n| Build a small four-page website | $0.44 | $5.09 |\n| Find and fix a bug in a large codebase | $0.11 | $1.09 |\n\n## How the scores have moved\n\n### StepFun API\n\n- -0.1 on 28 October 2026: correction\n- +0.3 on 27 October 2026: checklist\n\n### Vertex AI (Gemini Enterprise Agent Platform)\n\nNo score change since it was listed.\n\n## Verdicts\n\n**StepFun API.** StepFun's API serves Step 5 Preview with a 1M-token context, video input, strict JSON Schema output and published per-token prices, documented in Markdown with an llms.txt. The model is a preview with no release date found, there's no free allowance or SLA, and the terms and privacy policy leave room to train on customer data.\n\n**Vertex AI (Gemini Enterprise Agent Platform).** Gemini, Claude and open models through one Google Cloud API with IAM, regional endpoints, schema-guaranteed JSON and a 99.5 per cent SLA, and no Vertex incident on the Cloud status page in the 90 days to 6 November 2026. Gemini 4 Argon and 3.8 Flash have 12-month availability, but short-term Flash models get a 95 per cent SLA.\n\n## Before you call either\n\n### StepFun API\n\n1. Set `max_tokens` yourself. It defaults to unlimited on Step 5 Preview, and reasoning tokens are billed as output\n2. Use `response_format` with `type: json_schema` and `strict: true` when the shape matters. JSON Mode alone isn't schema-checked\n3. Back off and retry on 429, 500, 503 and 504. The docs give no Retry-After header or backoff schedule\n4. Expect HTTP 451 or `finish_reason: content_filter` when content fails StepFun's review, and don't retry the same input\n5. Use api.stepfun.ai for the international platform. api.stepfun.com is the China platform with yuan pricing\n\n### Vertex AI (Gemini Enterprise Agent Platform)\n\n1. Call the `global` location on aiplatform.googleapis.com unless data residency requires a Region. The 429 guide says it spreads load and reduces errors\n2. Back off exponentially on 429 `Resource exhausted`. On Standard PayGo it means shared capacity is busy, not a fixed quota\n3. Send `response_schema` with `response_mime_type: application/json`. JSON mode alone doesn't guarantee valid output\n4. Set `store` to false on Interactions API calls. It defaults to true and keeps prompts and responses\n5. Pin `gemini-4-argon` or `gemini-3.8-flash`, both in the 12-month tier, rather than 3.7 or 3.6 Flash, which retire on 28 January 2027 and 19 November 2026\n\n## Questions\n\n### Which is better for AI agents, StepFun API or Vertex AI (Gemini Enterprise Agent Platform)?\n\nVertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against StepFun API's 44.3 (E), and leads in every scored category.\n\n### Do StepFun API and Vertex AI (Gemini Enterprise Agent Platform) need an API key?\n\nStepFun API needs an API key. Vertex AI (Gemini Enterprise Agent Platform) takes an API key or an OAuth sign-in.\n\n### Can an agent call StepFun API and Vertex AI (Gemini Enterprise Agent Platform) without installing anything?\n\nYes. StepFun API has a hosted endpoint at https://api.stepfun.ai/v1 and Vertex AI (Gemini Enterprise Agent Platform) at https://aiplatform.googleapis.com/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/stepfun-api-vs-vertex-ai.json, and with the fewest tokens: https://www.anchorterminal.com/compare/stepfun-api-vs-vertex-ai.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"stepfun-api\", \"b\": \"vertex-ai\"}`. From a terminal: `anchor compare stepfun-api vertex-ai`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/stepfun-api.json and https://www.anchorterminal.com/api/v1/tools/vertex-ai.json\n\n## Other comparisons with StepFun API or Vertex AI (Gemini Enterprise Agent Platform)\n\n- [Amazon Bedrock vs StepFun API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-stepfun-api.md)\n- [Amazon Bedrock vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/amazon-bedrock-vs-vertex-ai.md)\n- [Claude API vs StepFun API](https://www.anchorterminal.com/compare/anthropic-api-vs-stepfun-api.md)\n- [Claude API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/anthropic-api-vs-vertex-ai.md)\n- [Antseed vs StepFun API](https://www.anchorterminal.com/compare/antseed-vs-stepfun-api.md)\n- [Antseed vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/antseed-vs-vertex-ai.md)\n- [Azure OpenAI in Foundry Models vs StepFun API](https://www.anchorterminal.com/compare/azure-openai-vs-stepfun-api.md)\n- [Azure OpenAI in Foundry Models vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/azure-openai-vs-vertex-ai.md)\n- [BlockRun.AI vs StepFun API](https://www.anchorterminal.com/compare/blockrun-ai-vs-stepfun-api.md)\n- [BlockRun.AI vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/blockrun-ai-vs-vertex-ai.md)\n- [Cerebras Inference vs StepFun API](https://www.anchorterminal.com/compare/cerebras-inference-vs-stepfun-api.md)\n- [Cerebras Inference vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/cerebras-inference-vs-vertex-ai.md)\n- [Cloudflare AI Gateway vs StepFun API](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-stepfun-api.md)\n- [Cloudflare AI Gateway vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-vertex-ai.md)\n- [Cloudflare Workers AI vs StepFun API](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-stepfun-api.md)\n- [Cloudflare Workers AI vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-vertex-ai.md)\n- [Cohere Chat API (Command models) vs StepFun API](https://www.anchorterminal.com/compare/cohere-chat-vs-stepfun-api.md)\n- [Cohere Chat API (Command models) vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/cohere-chat-vs-vertex-ai.md)\n- [DeepInfra vs StepFun API](https://www.anchorterminal.com/compare/deepinfra-vs-stepfun-api.md)\n- [DeepInfra vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/deepinfra-vs-vertex-ai.md)\n- [DeepSeek API vs StepFun API](https://www.anchorterminal.com/compare/deepseek-api-vs-stepfun-api.md)\n- [DeepSeek API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/deepseek-api-vs-vertex-ai.md)\n- [Eden AI vs StepFun API](https://www.anchorterminal.com/compare/eden-ai-vs-stepfun-api.md)\n- [Eden AI vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/eden-ai-vs-vertex-ai.md)\n- [Glimpse vs StepFun API](https://www.anchorterminal.com/compare/elorian-glimpse-vs-stepfun-api.md)\n- [Glimpse vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/elorian-glimpse-vs-vertex-ai.md)\n- [Fireworks AI Inference vs StepFun API](https://www.anchorterminal.com/compare/fireworks-inference-vs-stepfun-api.md)\n- [Fireworks AI Inference vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/fireworks-inference-vs-vertex-ai.md)\n- [Gemini Developer API vs StepFun API](https://www.anchorterminal.com/compare/gemini-api-vs-stepfun-api.md)\n- [Gemini Developer API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/gemini-api-vs-vertex-ai.md)\n- [GroqCloud vs StepFun API](https://www.anchorterminal.com/compare/groq-vs-stepfun-api.md)\n- [GroqCloud vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/groq-vs-vertex-ai.md)\n- [Hugging Face Inference Providers vs StepFun API](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-stepfun-api.md)\n- [Hugging Face Inference Providers vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vertex-ai.md)\n- [Inkling 2 Small vs StepFun API](https://www.anchorterminal.com/compare/inkling-2-small-vs-stepfun-api.md)\n- [Inkling 2 Small vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/inkling-2-small-vs-vertex-ai.md)\n- [Jais 3 vs StepFun API](https://www.anchorterminal.com/compare/jais-3-vs-stepfun-api.md)\n- [Jais 3 vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/jais-3-vs-vertex-ai.md)\n- [Meta Model API vs StepFun API](https://www.anchorterminal.com/compare/meta-model-api-vs-stepfun-api.md)\n- [Meta Model API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/meta-model-api-vs-vertex-ai.md)\n- [MiniMax API vs StepFun API](https://www.anchorterminal.com/compare/minimax-api-vs-stepfun-api.md)\n- [MiniMax API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/minimax-api-vs-vertex-ai.md)\n- [Mistral AI API vs StepFun API](https://www.anchorterminal.com/compare/mistral-api-vs-stepfun-api.md)\n- [Mistral AI API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/mistral-api-vs-vertex-ai.md)\n- [Muse Spark Open vs StepFun API](https://www.anchorterminal.com/compare/muse-spark-open-vs-stepfun-api.md)\n- [Muse Spark Open vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/muse-spark-open-vs-vertex-ai.md)\n- [Nemotron 3.5 Super VL vs StepFun API](https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-stepfun-api.md)\n- [Novita AI vs StepFun API](https://www.anchorterminal.com/compare/novita-ai-vs-stepfun-api.md)\n- [Novita AI vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/novita-ai-vs-vertex-ai.md)\n- [OpenAI API vs StepFun API](https://www.anchorterminal.com/compare/openai-api-vs-stepfun-api.md)\n- [OpenAI API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/openai-api-vs-vertex-ai.md)\n- [OpenRouter vs StepFun API](https://www.anchorterminal.com/compare/openrouter-vs-stepfun-api.md)\n- [OpenRouter vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/openrouter-vs-vertex-ai.md)\n- [Prism Inference vs StepFun API](https://www.anchorterminal.com/compare/prism-inference-vs-stepfun-api.md)\n- [Prism Inference vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/prism-inference-vs-vertex-ai.md)\n- [Router.com (Ramp Router) vs StepFun API](https://www.anchorterminal.com/compare/ramp-router-vs-stepfun-api.md)\n- [Router.com (Ramp Router) vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/ramp-router-vs-vertex-ai.md)\n- [Beam 1.0 vs StepFun API](https://www.anchorterminal.com/compare/reflection-beam-vs-stepfun-api.md)\n- [Beam 1.0 vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/reflection-beam-vs-vertex-ai.md)\n- [RouterPlus vs StepFun API](https://www.anchorterminal.com/compare/routerplus-vs-stepfun-api.md)\n- [RouterPlus vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/routerplus-vs-vertex-ai.md)\n- [SambaCloud vs StepFun API](https://www.anchorterminal.com/compare/sambanova-vs-stepfun-api.md)\n- [SambaCloud vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/sambanova-vs-vertex-ai.md)\n- [SiliconFlow vs StepFun API](https://www.anchorterminal.com/compare/siliconflow-vs-stepfun-api.md)\n- [SiliconFlow vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/siliconflow-vs-vertex-ai.md)\n- [Simplismart vs StepFun API](https://www.anchorterminal.com/compare/simplismart-vs-stepfun-api.md)\n- [Simplismart vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/simplismart-vs-vertex-ai.md)\n- [StepFun API vs SWE-2 Flash](https://www.anchorterminal.com/compare/stepfun-api-vs-swe-2-flash.md)\n- [StepFun API vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/stepfun-api-vs-tencent-tokenhub.md)\n- [StepFun API vs Together AI Inference](https://www.anchorterminal.com/compare/stepfun-api-vs-together-inference.md)\n- [StepFun API vs Vercel AI Gateway](https://www.anchorterminal.com/compare/stepfun-api-vs-vercel-ai-gateway.md)\n- [StepFun API vs xAI API (Grok)](https://www.anchorterminal.com/compare/stepfun-api-vs-xai-api.md)\n- [SWE-2 Flash vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/swe-2-flash-vs-vertex-ai.md)\n- [Tencent Cloud TokenHub vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/tencent-tokenhub-vs-vertex-ai.md)\n- [Together AI Inference vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/together-inference-vs-vertex-ai.md)\n- [Vercel AI Gateway vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-vertex-ai.md)\n- [Vertex AI (Gemini Enterprise Agent Platform) vs xAI API (Grok)](https://www.anchorterminal.com/compare/vertex-ai-vs-xai-api.md)\n- [Nemotron 3.5 Super VL vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-vertex-ai.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-07", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "StepFun API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "" } ], "description": "Vertex AI scores 88.7 (AA) to StepFun's 44.3 (E) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "StepFun API E 44.3", "Vertex AI (Gemini Enterprise Agent Platform) AA 88.7", "scores" ], "h1": "StepFun API vs Vertex AI (Gemini Enterprise Agent Platform)", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/stepfun-api-vs-vertex-ai", "published": "2026-10-01", "section": "tools", "title": "StepFun vs Vertex AI for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/stepfun-api-vs-vertex-ai" }, "tokens": { "markdown": 7350, "slim": 3630 }, "version": 1 }