{ "data": { "a": { "slug": "cerebras-inference", "name": "Cerebras Inference", "vendor": "Cerebras Systems Inc.", "vendorUrl": "https://www.cerebras.ai/inference", "kind": "http-api", "category": "inference", "summary": "Cerebras Inference serves language models on Cerebras wafer-scale processors through an OpenAI-compatible API. It supports streaming, structured outputs, tool calling and prompt caching, with shared and dedicated inference options.", "url": "https://www.anchorterminal.com/tools/cerebras-inference", "markdownUrl": "https://www.anchorterminal.com/tools/cerebras-inference.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/cerebras-inference.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/cerebras-inference.json", "dns": "cerebras-inference.grade.anchorterminal.com", "repo": "https://github.com/Cerebras/cerebras-cloud-sdk-python", "license": "Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.", "transports": [ "http" ], "remoteUrl": "https://api.cerebras.ai/v1", "packages": [ { "registry": "pypi", "name": "cerebras-cloud-sdk" }, { "registry": "npm", "name": "@cerebras/cerebras_cloud_sdk" } ], "auth": "api-key", "authNotes": "Bearer API keys from the Cloud Console. Paid accounts scope keys to projects; trial accounts do not have projects. Keys do not expire and can be rotated by creating a replacement and deleting the old key.", "pricing": "paid", "pricingNotes": "Pay per token. GPT OSS 120B is $0.35 per million input tokens and $0.75 per million output tokens. New accounts get $5 for 30 days only after adding a verified payment method. Dedicated capacity is priced by agreement.", "priceSummary": "Paid", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 payment route found in the reviewed inference and billing documentation on 19 October 2026.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 170, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-19" }, "docsUrl": "https://inference-docs.cerebras.ai", "llmsTxt": "https://inference-docs.cerebras.ai/llms.txt", "openapi": "https://inference-docs.cerebras.ai/api-reference/openapi.yaml", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "http-api", "inference", "api-key", "openapi", "llms-txt", "paid" ], "lastRelease": "2026-10-28", "graded": true, "anchor": { "graded": true, "score": 68.6, "grade": "B", "agentReady": false, "rank": 278, "ranked": true, "rankOf": 1510, "categoryRank": 11, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 85, "maintenance": 65, "payments": 20, "reliability": 70, "schema": 93, "security": 70, "transparency": 60 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": 0, "verdict": "An OpenAI-compatible API with typed schemas, official SDKs and model output controls. Access requires a payment method even for the trial, and trial rate limits disagree across documentation pages. Shared-model availability and dedicated-model availability differ.", "bestFor": "Cerebras Inference serves language models on Cerebras wafer-scale processors through an OpenAI-compatible API.", "strengths": [ "Public OpenAPI 3.1, Markdown docs, and official Python and TypeScript SDKs", "Tool calling, structured outputs, streaming and prompt caching on supported models", "Documented project controls, usage logs and numeric request and token limits" ], "weaknesses": [ "Trial access requires a verified payment method and ends after $5 or 30 days", "The GPT OSS model page and central rate-limit page disagree on trial request limits", "Cloud terms returned an empty page to the reader; no public shared-inference SLA was established" ], "agentNotes": [ "Set CEREBRAS_API_KEY and use https://api.cerebras.ai/v1 with an OpenAI-compatible client.", "Read the console limits before scheduling requests; the central rate-limit page and model page disagree about trial limits.", "Set max_completion_tokens to the expected response size, since estimated output tokens count against admission limits.", "Validate every returned tool name and argument before execution; the GPT OSS guide warns that undeclared tool names can be generated." ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 3.3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 68.6 } ], "editorialScores": { "ergonomics": 85, "maintenance": 65, "payments": 20, "reliability": 70, "schema": 93, "security": 70, "transparency": 45 }, "provenanceScore": 75, "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": "2026-10-27", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl 'https://api.cerebras.ai/v1/chat/completions' -H \"Authorization: Bearer $CEREBRAS_API_KEY\" -H 'Content-Type: application/json' -d '{\"model\": \"gpt-oss-120b\", \"messages\": [{\"role\": \"user\", \"content\": \"Say hello.\"}], \"max_tokens\": 128}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/cerebras-inference" }, "area": "models", "unitPrices": [ { "item": "GPT OSS 120B input", "unit": "1m-tokens", "usd": 0.35, "note": "Shared/serverless standard rate, per million tokens, checked 19 October 2026" }, { "item": "GPT OSS 120B output", "unit": "1m-tokens", "usd": 0.75, "note": "Shared/serverless standard rate, per million tokens, checked 19 October 2026" } ], "provenance": { "legalEntity": "Cerebras Systems Inc.", "domain": "cerebras.ai", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://cloud.cerebras.ai/terms", "privacy": "https://www.cerebras.ai/privacy-policy", "statusPage": "https://status.cerebras.ai", "changelog": "https://inference-docs.cerebras.ai/support/change-log", "securityTxt": "none", "checked": "2026-11-01", "notes": [ "Legal identity comes from the vendor policy pages. Domain registration was not checked.", "The SDK repository is not the source for the hosted inference service.", "Cloud terms at cloud.cerebras.ai/terms returned no readable document on 19 October and weren't re-read on 1 November; privacy identifies Cerebras Systems Inc.", "The well-known security.txt at www.cerebras.ai returned 404 again on 1 November 2026. The trust centre lists SOC 2 Type II." ], "score": 75 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/cerebras-inference.json", "live": { "slug": "cerebras-inference", "probe": { "target": "https://api.cerebras.ai/v1", "method": "get", "lastAt": "2026-11-07T19:21:58.854823526Z", "lastOk": true, "lastStatus": 404, "lastMs": 159, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 131, "p95ms24h": 219, "samples24h": 238, "samples30d": 4796, "days": [ { "date": "2026-10-19", "probes": 173, "ok": 173 }, { "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": 251, "ok": 251 }, { "date": "2026-10-29", "probes": 249, "ok": 249 }, { "date": "2026-10-30", "probes": 248, "ok": 248 }, { "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 } ] }, "vendorStatus": { "page": "https://status.cerebras.ai", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-11-07T19:21:13.624394835Z" }, "versions": [ { "registry": "npm", "name": "@cerebras/cerebras_cloud_sdk", "version": "1.91.0", "seenAt": "2026-11-06T23:13:49.446971954Z" }, { "registry": "pypi", "name": "cerebras-cloud-sdk", "version": "1.91.0", "released": "2026-07-16", "seenAt": "2026-11-06T23:13:49.262026332Z" } ], "githubStars": 173, "npmWeekly": 180448, "pypiWeekly": 249281, "securityTxt": { "url": "https://cerebras.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:01:42.51446288Z" }, "llmsTxt": { "url": "https://inference-docs.cerebras.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:31:47.130010713Z" }, "domain": { "domain": "cerebras.ai", "registered": "2017-12-15", "source": "https://rdap.identitydigital.services/rdap/domain/cerebras.ai", "checkedAt": "2026-11-01T14:11:27.609133686Z" }, "pages": [ { "url": "https://inference-docs.cerebras.ai/support/change-log", "kind": "changelog", "status": 200, "checkedAt": "2026-11-07T14:11:30.48401691Z", "changedAt": "2026-10-29T05:08:49.839928383Z", "fingerprint": "a8abcec170f3" }, { "url": "https://www.cerebras.ai/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:26:28.792856066Z", "changedAt": "2026-11-06T13:47:29.432265889Z", "fingerprint": "218d0061c477" }, { "url": "https://cloud.cerebras.ai/terms", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:01:12.525816134Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "32931218130a" } ], "github": { "repo": "cerebras/cerebras-cloud-sdk-python", "checkedAt": "2026-11-02T08:24:38.010800971Z", "stars": 174, "archived": false, "issuesEnabled": true, "pushedAt": "2026-07-16T17:08:17Z", "openIssues": 1, "openPRs": 0, "issuesOpened90d": 2, "issuesClosed90d": 1, "prsMerged90d": 0, "replies": { "sampled": 12, "unanswered": 0, "medianDays": 35.4 } }, "updatedAt": "2026-11-07T19:21:58.854823526Z" } }, "answer": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Cerebras Inference's 68.6 (B), 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": 30, "category": "transparency", "leads": "vertex-ai", "name": "Transparency \u0026 trust", "reasons": { "a": "SDK is Apache-2.0, but the hosted cloud terms were not readable in this session (5 of 30). Privacy policy states no inference input/output retention but gives no fixed operational-log retention period (20 of 30). Dated deprecations and API-version migration guidance without a general minimum notice commitment found (10 of 20). Trust centre lists subprocessors and infrastructure controls, but full data-location details were not established (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": 60, "b": 90 } }, { "by": 29, "category": "reliability", "leads": "vertex-ai", "name": "Reliability", "reasons": { "a": "Graded as listed, on the hosted API lines. Public component status history at status.cerebras.ai, with components for GPT-OSS-120B, Qwen-3.8-27b and the Developer Console (20). The history feed, read on 1 November 2026, runs back to November 2025, so the whole 90 days from 3 August were read. On 25 September 2026 Cerebras posted that parts of the service might be unavailable from 10:54 UTC, services were back at 13:41 UTC and the incident was resolved at 17:14 UTC, marked major and affecting both public model components. That is about 2 hours 47 minutes with the whole shared catalogue affected, one major. A 15-minute partial degradation of Gemma 4 31B on 27 August is minor, and the 30 August firewall maintenance was announced on 25 August (10). Numeric rate-limit tables, although the trial request limit is 5 a minute on the rate-limits page and 30 a minute on the GPT OSS page, re-read on 1 November (15). SDK error classes and bounded retries with backoff (15). No public shared-inference SLA established (0). Shared inference is generally available (10).", "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": 70, "b": 99 } }, { "by": 27, "category": "security", "leads": "vertex-ai", "name": "Security \u0026 auth", "reasons": { "a": "Revocable Bearer keys with rotation instructions (20). Paid-project boundaries, but no inference-only key permission found (10 of 20). GPT OSS documentation warns about undeclared tool calls and tells callers to validate them (10 of 15). Request and audit logs in the console (15). Trust centre lists SOC 2 Type II, with reports requiring access (15 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": 70, "b": 97 } }, { "by": 26, "category": "maintenance", "leads": "vertex-ai", "name": "Maintenance \u0026 community", "reasons": { "a": "Dated changelog entry on 28 October 2026, adding five models to the Dedicated catalogue and documenting image inputs in tool messages and new reasoning controls (30). Seven dated changelog entries in the 90 days from 3 August, on 28 and 31 August, two on 3 September, 22 September, 9 October and 28 October (20). Support responsiveness not established (0). Official Python and TypeScript SDKs, both last released as 1.91.0 on 8 July 2026 (15). Runtime dependency health and CI were not audited (0).", "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": 65, "b": 91 } }, { "by": 20, "category": "payments", "leads": "vertex-ai", "name": "Payments \u0026 pricing", "reasons": { "a": "No machine payment protocol found in the reviewed API and billing docs (0). Public token prices (20). The $5 trial requires a verified payment method (0). Account creation and payment setup require a person (0).", "b": "No x402, MPP or L402 (0). Per-token prices per model and option published without a login (20). Express mode gives new Google Cloud users 90 days free within quotas with no billing details, though it's in Preview and needs a @gmail.com account (20). A person signs up in the console to get the express key (0)." }, "scores": { "a": 20, "b": 40 } }, { "by": 12, "category": "ergonomics", "leads": "vertex-ai", "name": "Agent ergonomics", "reasons": { "a": "Model API with bounded output and compact request shape (25). Output token controls, streaming and structured outputs (20). Documented error classes and fixes (20). Bounded transient retries but no request-deduplication guarantee established (5 of 20). Defaults and official Python and TypeScript SDKs (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": 85, "b": 97 } } ], "facts": [ { "a": "HTTP API", "b": "Model API", "name": "Kind" }, { "a": "Cerebras Systems Inc.", "b": "Google Cloud", "name": "Vendor" }, { "a": "https://api.cerebras.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": "Paid", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.", "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": "2026-10-28", "b": "2026-11-05", "name": "Last release" }, { "a": "couldn't be read", "b": "2026-09-02", "name": "Terms last updated" }, { "a": "2024-08-27", "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": "170 stars", "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 Cerebras Inference's 68.6 (B), and leads in every scored category.", "question": "Which is better for AI agents, Cerebras Inference or Vertex AI (Gemini Enterprise Agent Platform)?" }, { "answer": "Cerebras Inference needs an API key. Vertex AI (Gemini Enterprise Agent Platform) takes an API key or an OAuth sign-in.", "question": "Do Cerebras Inference and Vertex AI (Gemini Enterprise Agent Platform) need an API key?" }, { "answer": "Yes. Cerebras Inference has a hosted endpoint at https://api.cerebras.ai/v1 and Vertex AI (Gemini Enterprise Agent Platform) at https://aiplatform.googleapis.com/v1.", "question": "Can an agent call Cerebras Inference and Vertex AI (Gemini Enterprise Agent Platform) without installing anything?" } ], "goodFor": [ { "aheadOn": null, "also": null, "goodFor": "Cerebras Inference serves language models on Cerebras wafer-scale processors through an OpenAI-compatible API.", "slug": "cerebras-inference", "watchFor": "Trial access requires a verified payment method and ends after $5 or 30 days" }, { "aheadOn": [ "Reliability, 99 against 70", "Agent ergonomics, 97 against 85", "Security \u0026 auth, 97 against 70", "Payments \u0026 pricing, 40 against 20", "Maintenance \u0026 community, 91 against 65", "Transparency \u0026 trust, 90 against 60" ], "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": { "cerebras-inference": [ { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.2, "from": 68.4, "fromGrade": "B", "to": 68.6, "toGrade": "B" } ], "vertex-ai": null }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cerebras-inference.json", "title": "Amazon Bedrock vs Cerebras Inference", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cerebras-inference" }, { "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": 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"url": "https://www.anchorterminal.com/compare/prism-inference-vs-vertex-ai" }, { "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-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-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-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-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-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-vertex-ai.json", "title": "StepFun API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/stepfun-api-vs-vertex-ai" }, { "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": 29, "cerebras-inference": 70, "edge": "vertex-ai", "key": "reliability", "name": "Reliability", "vertex-ai": 99, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 1, "cerebras-inference": 93, "edge": "vertex-ai", "key": "schema", "name": "Schema \u0026 documentation", "vertex-ai": 94, "weight": 13 }, { "by": 12, "cerebras-inference": 85, "edge": "vertex-ai", "key": "ergonomics", "name": "Agent ergonomics", "vertex-ai": 97, "weight": 13 }, { "by": 27, "cerebras-inference": 70, "edge": "vertex-ai", "key": "security", "name": "Security \u0026 auth", "vertex-ai": 97, "weight": 14 }, { "by": 20, "cerebras-inference": 20, "edge": "vertex-ai", "key": "payments", "name": "Payments \u0026 pricing", "vertex-ai": 40, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 26, "cerebras-inference": 65, "edge": "vertex-ai", "key": "maintenance", "name": "Maintenance \u0026 community", "vertex-ai": 91, "weight": 7 }, { "by": 30, "cerebras-inference": 60, "edge": "vertex-ai", "key": "transparency", "name": "Transparency \u0026 trust", "vertex-ai": 90, "weight": 7 } ], "summary": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Cerebras Inference's 68.6 (B), and leads in every scored category. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "cerebras-inference": "An OpenAI-compatible API with typed schemas, official SDKs and model output controls. Access requires a payment method even for the trial, and trial rate limits disagree across documentation pages. Shared-model availability and dedicated-model availability differ.", "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/cerebras-inference-vs-vertex-ai", "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-vertex-ai.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/cerebras-inference-vs-vertex-ai.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/cerebras-inference-vs-vertex-ai.min.md" }, "markdown": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Cerebras Inference's 68.6 (B), and leads in every scored category. Both do llm inference.\n\n- Cerebras Inference: grade B, 68.6/100, rank #278 of 1510. Markdown https://www.anchorterminal.com/tools/cerebras-inference.md · JSON https://www.anchorterminal.com/api/v1/tools/cerebras-inference.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### Cerebras Inference (B)\n\nGood for: Cerebras Inference serves language models on Cerebras wafer-scale processors through an OpenAI-compatible API.\n\nWatch for: Trial access requires a verified payment method and ends after $5 or 30 days\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 70\n- Agent ergonomics, 97 against 85\n- Security \u0026 auth, 97 against 70\n- Payments \u0026 pricing, 40 against 20\n- Maintenance \u0026 community, 91 against 65\n- Transparency \u0026 trust, 90 against 60\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### Transparency \u0026 trust: Vertex AI (Gemini Enterprise Agent Platform) +30\n\n- Cerebras Inference (60): SDK is Apache-2.0, but the hosted cloud terms were not readable in this session (5 of 30). Privacy policy states no inference input/output retention but gives no fixed operational-log retention period (20 of 30). Dated deprecations and API-version migration guidance without a general minimum notice commitment found (10 of 20). Trust centre lists subprocessors and infrastructure controls, but full data-location details were not established (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### Reliability: Vertex AI (Gemini Enterprise Agent Platform) +29\n\n- Cerebras Inference (70): Graded as listed, on the hosted API lines. Public component status history at status.cerebras.ai, with components for GPT-OSS-120B, Qwen-3.8-27b and the Developer Console (20). The history feed, read on 1 November 2026, runs back to November 2025, so the whole 90 days from 3 August were read. On 25 September 2026 Cerebras posted that parts of the service might be unavailable from 10:54 UTC, services were back at 13:41 UTC and the incident was resolved at 17:14 UTC, marked major and affecting both public model components. That is about 2 hours 47 minutes with the whole shared catalogue affected, one major. A 15-minute partial degradation of Gemma 4 31B on 27 August is minor, and the 30 August firewall maintenance was announced on 25 August (10). Numeric rate-limit tables, although the trial request limit is 5 a minute on the rate-limits page and 30 a minute on the GPT OSS page, re-read on 1 November (15). SDK error classes and bounded retries with backoff (15). No public shared-inference SLA established (0). Shared inference is generally available (10).\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) +27\n\n- Cerebras Inference (70): Revocable Bearer keys with rotation instructions (20). Paid-project boundaries, but no inference-only key permission found (10 of 20). GPT OSS documentation warns about undeclared tool calls and tells callers to validate them (10 of 15). Request and audit logs in the console (15). Trust centre lists SOC 2 Type II, with reports requiring access (15 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### Maintenance \u0026 community: Vertex AI (Gemini Enterprise Agent Platform) +26\n\n- Cerebras Inference (65): Dated changelog entry on 28 October 2026, adding five models to the Dedicated catalogue and documenting image inputs in tool messages and new reasoning controls (30). Seven dated changelog entries in the 90 days from 3 August, on 28 and 31 August, two on 3 September, 22 September, 9 October and 28 October (20). Support responsiveness not established (0). Official Python and TypeScript SDKs, both last released as 1.91.0 on 8 July 2026 (15). Runtime dependency health and CI were not audited (0).\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### Payments \u0026 pricing: Vertex AI (Gemini Enterprise Agent Platform) +20\n\n- Cerebras Inference (20): No machine payment protocol found in the reviewed API and billing docs (0). Public token prices (20). The $5 trial requires a verified payment method (0). Account creation and payment setup require a person (0).\n- Vertex AI (Gemini Enterprise Agent Platform) (40): No x402, MPP or L402 (0). Per-token prices per model and option published without a login (20). Express mode gives new Google Cloud users 90 days free within quotas with no billing details, though it's in Preview and needs a @gmail.com account (20). A person signs up in the console to get the express key (0).\n\n### Agent ergonomics: Vertex AI (Gemini Enterprise Agent Platform) +12\n\n- Cerebras Inference (85): Model API with bounded output and compact request shape (25). Output token controls, streaming and structured outputs (20). Documented error classes and fixes (20). Bounded transient retries but no request-deduplication guarantee established (5 of 20). Defaults and official Python and TypeScript SDKs (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 | Cerebras Inference | Vertex AI (Gemini Enterprise Agent Platform) | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 70 | 99 | Vertex AI (Gemini Enterprise Agent Platform) +29 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 93 | 94 | Vertex AI (Gemini Enterprise Agent Platform) +1 |\n| Agent ergonomics | 13% (16.2 this run) | 85 | 97 | Vertex AI (Gemini Enterprise Agent Platform) +12 |\n| Security \u0026 auth | 14% (17.5 this run) | 70 | 97 | Vertex AI (Gemini Enterprise Agent Platform) +27 |\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) | 65 | 91 | Vertex AI (Gemini Enterprise Agent Platform) +26 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 60 | 90 | Vertex AI (Gemini Enterprise Agent Platform) +30 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **68.6 · B** | **88.7 · AA** | |\n\n## Facts side by side\n\n| Fact | Cerebras Inference | Vertex AI (Gemini Enterprise Agent Platform) |\n| --- | --- | --- |\n| Kind | HTTP API | Model API |\n| Vendor | Cerebras Systems Inc. | Google Cloud |\n| Hosted endpoint | `https://api.cerebras.ai/v1` | `https://aiplatform.googleapis.com/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | OAuth or key |\n| Pricing | Paid | Pay per use |\n| x402 | no | no |\n| Licence | Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences. | 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 | 2026-10-28 | 2026-11-05 |\n| Terms last updated | couldn't be read | 2026-09-02 |\n| Privacy policy last updated | 2024-08-27 | 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 | 170 stars | 20.9M PyPI/wk |\n| Agent reviews | 3.3/5 (4) | none |\n\n## How the scores have moved\n\n### Cerebras Inference\n\n- +0.2 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**Cerebras Inference.** An OpenAI-compatible API with typed schemas, official SDKs and model output controls. Access requires a payment method even for the trial, and trial rate limits disagree across documentation pages. Shared-model availability and dedicated-model availability differ.\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### Cerebras Inference\n\n1. Set CEREBRAS_API_KEY and use https://api.cerebras.ai/v1 with an OpenAI-compatible client.\n2. Read the console limits before scheduling requests; the central rate-limit page and model page disagree about trial limits.\n3. Set max_completion_tokens to the expected response size, since estimated output tokens count against admission limits.\n4. Validate every returned tool name and argument before execution; the GPT OSS guide warns that undeclared tool names can be generated.\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, Cerebras Inference or Vertex AI (Gemini Enterprise Agent Platform)?\n\nVertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Cerebras Inference's 68.6 (B), and leads in every scored category.\n\n### Do Cerebras Inference and Vertex AI (Gemini Enterprise Agent Platform) need an API key?\n\nCerebras Inference 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 Cerebras Inference and Vertex AI (Gemini Enterprise Agent Platform) without installing anything?\n\nYes. Cerebras Inference has a hosted endpoint at https://api.cerebras.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/cerebras-inference-vs-vertex-ai.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cerebras-inference-vs-vertex-ai.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"cerebras-inference\", \"b\": \"vertex-ai\"}`. From a terminal: `anchor compare cerebras-inference vertex-ai`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/cerebras-inference.json and https://www.anchorterminal.com/api/v1/tools/vertex-ai.json\n\n## Other comparisons with Cerebras Inference or Vertex AI (Gemini Enterprise Agent Platform)\n\n- [Amazon Bedrock vs Cerebras Inference](https://www.anchorterminal.com/compare/amazon-bedrock-vs-cerebras-inference.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 Cerebras Inference](https://www.anchorterminal.com/compare/anthropic-api-vs-cerebras-inference.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 Cerebras Inference](https://www.anchorterminal.com/compare/antseed-vs-cerebras-inference.md)\n- [Antseed vs Vertex AI (Gemini Enterprise Agent 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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 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