{ "data": { "a": { "slug": "amazon-bedrock", "name": "Amazon Bedrock", "vendor": "Amazon Web Services", "vendorUrl": "https://aws.amazon.com/bedrock/", "kind": "model", "category": "inference", "summary": "AWS's managed API for foundation models from Anthropic, OpenAI, Amazon, Meta, Mistral, DeepSeek, Qwen, xAI and others, called through the Converse API or OpenAI- and Anthropic-compatible endpoints under one AWS account.", "url": "https://www.anchorterminal.com/tools/amazon-bedrock", "markdownUrl": "https://www.anchorterminal.com/tools/amazon-bedrock.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/amazon-bedrock.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/amazon-bedrock.json", "dns": "amazon-bedrock.grade.anchorterminal.com", "repo": "https://github.com/aws/api-models-aws", "license": "Proprietary service under the AWS Customer Agreement and Service Terms. Third-party models carry their providers' licence terms. The AWS SDKs and the Smithy service models are Apache-2.0", "transports": [ "http" ], "remoteUrl": "https://bedrock-runtime.us-east-1.amazonaws.com", "packages": [ { "registry": "pypi", "name": "boto3" }, { "registry": "npm", "name": "@aws-sdk/client-bedrock-runtime" } ], "auth": "mixed", "authNotes": "AWS Signature Version 4 with IAM users, roles or short-lived STS credentials, and IAM policies that can name single model or inference-profile ARNs. Bedrock API keys go in an `Authorization: Bearer` header. Short-term keys last up to 12 hours and inherit the caller's IAM permissions; long-term keys create an IAM user and are marked for exploration only. Endpoints are regional, `bedrock-runtime.\u003cregion\u003e.amazonaws.com` and `bedrock-mantle.\u003cregion\u003e.api.aws`.", "pricing": "usage", "pricingNotes": "Per-token prices per model and Region, with Standard, Priority, Flex and Reserved tiers. Claude Opus 5.5 costs $4/$20 per million tokens through global cross-Region inference and $4.40/$22 through geographic or in-Region inference, cache reads $0.20. Cache reads on Claude Sonnet 5.5 were cut by half from 7 October 2026. Batch is half price on supported models but was not shown for Opus 5.5 or Sonnet 5.5. New AWS accounts get up to $200 in Free Tier credits (https://aws.amazon.com/bedrock/pricing/, rates per AWS's price feed of 30 September 2026; the page's tables are drawn by script and were not readable on 6 November).", "priceSummary": "from $0.30 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 on the pricing page or in the user guide's llms.txt (checked 2026-11-06). Access needs an AWS account.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": 21825916, "pypiWeekly": null, "asOf": "2026-11-06" }, "docsUrl": "https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html", "rateLimitsUrl": "https://docs.aws.amazon.com/general/latest/gr/bedrock.html", "llmsTxt": "https://docs.aws.amazon.com/bedrock/latest/userguide/llms.txt", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "hosted", "model", "open-weights", "enterprise", "usage-priced", "llms-txt", "python", "typescript", "status-page" ], "lastRelease": "2026-10-30", "graded": true, "anchor": { "graded": true, "score": 81.7, "grade": "A", "agentReady": true, "rank": 8, "ranked": true, "rankOf": 1510, "categoryRank": 3, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 92, "maintenance": 81, "payments": 30, "reliability": 80, "schema": 94, "security": 98, "transparency": 85 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "verdict": "Bedrock reaches Claude, GPT-6, Nova, Llama and other families through one IAM-controlled API, with a 99.9 per cent SLA and a per-Region zero-retention switch. Setup needs an AWS account, IAM permissions and a Region, capabilities vary by model, and some Regions gave five older Claude models about 34 days of notice.", "bestFor": "Teams already on AWS who want Claude, GPT-6, Nova, Llama and other models under one IAM, billing and VPC boundary, with regional data controls and an SLA.", "strengths": [ "One API and one bill for Anthropic, OpenAI, Amazon, Meta, Mistral, DeepSeek, Qwen, xAI and other model families", "IAM policies can limit a caller to named model ARNs, and short-term API keys expire within 12 hours", "A `none` data retention mode per Region blocks any model that would store prompts", "Published SLA of 99.9 per cent a month per Region with service credits", "Per-model token quotas published with default values, for example 30,000,000 tokens a minute for Opus 5.5 global inference" ], "weaknesses": [ "An AWS account, IAM setup and a Region choice come before the first call, and an agent can't sign up alone", "Batch inference isn't shown for Claude Opus 5.5 or Sonnet 5.5, and since 26 October batch completion isn't guaranteed", "Claude Fable 5 and 5.1 retain all traffic up to 30 days, and AWS may review flagged prompts", "Five older Claude models went Legacy on 10 or 13 October 2026 with end of life on 13 November in some Regions, against the 6-month floor the policy states", "The Middle East (UAE) and (Bahrain) Regions have been disrupted since March 2026, and AWS says some data there can't be restored" ], "agentNotes": [ "Use the geographic or global inference ID from the model card, such as `global.anthropic.claude-opus-5-5`. Global routing is cheaper but can process data in any commercial Region", "Set `data_retention_mode` to `none` in each Region before sending sensitive data. Models that need retention then return ValidationException", "Back off with jitter on 429 ThrottlingException, 503 and 529 `overloaded_error`, and honour `Retry-After` when it's sent", "Generate short-term API keys from an IAM role for production. Long-term keys create an IAM user and AWS marks them exploration only", "Call ListFoundationModels in your Region and read `modelLifecycle` before pinning a model ID. Claude 3.x IDs in several Regions stop working on 13 November 2026 and requests don't redirect" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "A", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 81.7 } ], "editorialScores": { "ergonomics": 92, "maintenance": 81, "payments": 30, "reliability": 80, "schema": 94, "security": 98, "transparency": 76 }, "provenanceScore": 94, "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 boto3 # or: npm i @aws-sdk/client-bedrock-runtime", "http": "curl -X POST \"https://bedrock-runtime.us-east-1.amazonaws.com/model/us.anthropic.claude-sonnet-4-6/converse\" \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $AWS_BEARER_TOKEN_BEDROCK\" \\\n -d '{\"messages\": [{\"role\": \"user\", \"content\": [{\"text\": \"Hello\"}]}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/amazon-bedrock" }, "sameCompany": [ "amazon-nova-embeddings", "amazon-bedrock-guardrails", "amazon-transcribe", "amazon-polly", "amazon-nova-sonic", "agentcore-memory", "agentcore-identity", "aws-secrets-manager", "agentcore-web-search", "aws-mcp-servers", "amazon-ses", "amazon-location", "amazon-translate", "amazon-ads-api", "amazon-creators-api" ], "area": "models", "provenance": { "legalEntity": "Amazon Web Services, Inc.", "domain": "amazon.com", "domainRegistered": "1994-11-01", "domainNote": "The endpoints are on amazonaws.com and api.aws, both AWS domains. The security.txt on aws.amazon.com had expired on 2026-09-24 and was renewed, with Expires 2027-10-16, when read on 2026-11-06.", "endpointOnVendorDomain": true, "terms": "https://aws.amazon.com/service-terms/", "privacy": "https://aws.amazon.com/privacy/", "statusPage": "https://health.aws.amazon.com/health/status", "changelog": "https://docs.aws.amazon.com/bedrock/latest/userguide/doc-history.html", "securityTxt": "valid", "checked": "2026-11-06", "notes": [ "AWS's public history feed (historyevents.json) lists Amazon Bedrock as disrupted in the ME-CENTRAL-1 and ME-SOUTH-1 Regions since March 2026, with a last update on 15 September 2026, and no Bedrock event in other Regions in the 90 days to 6 November 2026. An EU-SOUTH-2 packet-loss event on 4 October 2026 named Bedrock AgentCore, not Bedrock.", "The pricing page fills its tables by script. Prices here come from AWS's public price feed of 30 September 2026; the bedrockfoundationmodels feed read on 6 November (published 12 October) carries only rate codes." ], "score": 94 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/amazon-bedrock.json", "live": { "slug": "amazon-bedrock", "probe": { "target": "https://bedrock-runtime.us-east-1.amazonaws.com", "method": "get", "lastAt": "2026-11-07T19:21:51.459287778Z", "lastOk": true, "lastStatus": 404, "lastMs": 332, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 269, "p95ms24h": 352, "samples24h": 210, "samples30d": 210, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 13 }, { "date": "2026-11-07", "probes": 197, "ok": 197 } ] }, "versions": [ { "registry": "npm", "name": "@aws-sdk/client-bedrock-runtime", "version": "3.1164.0", "seenAt": "2026-11-06T23:05:19.602032841Z" }, { "registry": "pypi", "name": "boto3", "version": "1.43.126", "released": "2026-11-06", "seenAt": "2026-11-06T23:05:17.831478687Z" } ], "githubStars": 229, "npmWeekly": 21825916, "pypiWeekly": 637851852, "securityTxt": { "url": "https://amazon.com/.well-known/security.txt", "state": "valid", "checkedAt": "2026-11-07T16:00:18.354437696Z" }, "llmsTxt": { "url": "https://docs.aws.amazon.com/bedrock/latest/userguide/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:31:17.63045618Z" }, "pages": [ { "url": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:05:11.906374144Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "dce416908c57" } ], "updatedAt": "2026-11-07T19:21:51.459287778Z" } }, "answer": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Amazon Bedrock's 81.7 (A), and leads in 5 of 7 scored categories.", "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": 19, "category": "reliability", "leads": "vertex-ai", "name": "Reliability", "reasons": { "a": "AWS Health Dashboard with per-service, per-Region feeds and a public history file (20). The history lists Amazon Bedrock as disrupted in ME-CENTRAL-1 (UAE) and ME-SOUTH-1 (Bahrain) since March 2026, where AWS said on 15 September 2026 (still inside the 90-day window on 6 November) that it can't restore resources held only there. No other Bedrock event appears in the history in the 90 days to 6 November; an EU-SOUTH-2 packet-loss event on 4 October named Bedrock AgentCore, not Bedrock. This counts as one major event (10). StatusGator's third-party mirror shows 'Increased Error Rates' warnings on 24, 26 and 27 August and 10 September that we couldn't find in AWS's own history, so we didn't score them. Per-model token quotas with default values in the AWS General Reference, such as 30,000,000 tokens a minute for Opus 5.5 global inference (15). The error guide gives exponential backoff with jitter for 429, 503 and 529 and says to honour `Retry-After`, and the SDKs retry ModelNotReadyException up to five times (15). SLA of 99.9 per cent a month per Region for the model APIs, last updated 4 October 2023 (10). Converse and the current Claude, GPT-6 and Nova 2 Lite models are GA (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": 80, "b": 99 } }, { "by": 10, "category": "payments", "leads": "vertex-ai", "name": "Payments \u0026 pricing", "reasons": { "a": "No x402, MPP or L402 (0). Per-token prices per model, tier and Region on the public pricing page, filled from AWS's public price feed (20). New accounts get up to $200 in Free Tier credits and the Free Tier page lists Bedrock among eligible services, and the Free Tier FAQ says most new customers don't need a payment method, but AWS may still ask for one, so half, as for S3 (10). A person signs up for AWS in a browser and sets up IAM before any key exists (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": 30, "b": 40 } }, { "by": 10, "category": "maintenance", "leads": "vertex-ai", "name": "Maintenance \u0026 community", "reasons": { "a": "Model reading. The last model or API change is 30 October 2026 (OpenAI model API support and cross-Region inference in GovCloud), after structured outputs for Claude on both endpoints on 18 October (30). Models launched since 7 September 2026 get a 6-month or 45-day Legacy period, but the legacy page, which promises at least 6 months in Legacy, lists Claude 3 Haiku, 3 Sonnet, 3.5 Sonnet, 3.5 Sonnet v2 and 3.7 Sonnet as Legacy from 10 or 13 October with end of life on 13 November in several Regions, about 34 days (6 of 12, down from 10). Six models reached end of life in the 90 days to 6 November on five dates, Command R and R+ on 19 August, Claude 3 Haiku on 10 September, Nova Sonic on 14 September, Nova Canvas and Nova Reel on 30 September and Claude Sonnet 4 on 14 October (3 of 8, down from 4). Dated document history several times a month, What's New and re:Post, with direct support on a paid plan (12 of 15). SDK issue replies not sampled (5 of 10). Current official SDKs, boto3 1.43.125 on 5 November and `@aws-sdk/client-bedrock-runtime` 3.1163.0 (15). Supported runtimes stated, Python 3.10 or later and Node 20 or later (10). Down from 86 on 6 October.", "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": 81, "b": 91 } }, { "by": 5, "category": "ergonomics", "leads": "vertex-ai", "name": "Agent ergonomics", "reasons": { "a": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Converse takes tools with `toolChoice` auto, any or a named tool and `strict: true`, but forced choice depends on the model behind it (17 of 20). Structured outputs on supported models only (13 of 15). Explicit and implicit prompt caching, cache reads at $0.20 per million on Opus 5.5, 0.05x input, with 5-minute and 1-hour TTLs (15). 1M-token context on Opus 5.5, Sonnet 5.5 and Nova 2 Lite, a judgement call since Bedrock has no default model (15). Batch at half price on supported models, but the pricing page shows none for Opus 5.5 or Sonnet 5.5, while Flex is half price on Nova (7 of 10). AWS SDKs in every major language plus token generators for Python, JavaScript and Java (10). Typed errors with recovery advice per code (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": 92, "b": 97 } }, { "by": 5, "category": "transparency", "leads": "vertex-ai", "name": "Transparency \u0026 trust", "reasons": { "a": "Closed service under the AWS Customer Agreement and Service Terms, with the SDKs and Smithy models under Apache-2.0 (18, as for S3). The data retention, abuse detection and security pages agree that Bedrock stores nothing by default, name the models that retain traffic and for how long, and say retained data isn't shared with providers. The retention page's `default` mode says AWS 'may retain the data for safety and abuse-prevention purposes' without a period, and a legacy `provider_data_share` mode is kept though sharing isn't supported (25 of 30). A written lifecycle policy with Legacy and EOL dates per model, but the legacy table's 34-day Legacy periods for five Claude models in some Regions contradict its own 6-month floor (15 of 20, down from 18). AWS's sub-processor list, per the 4 October S3 check, and per-Region, geographic and global inference options, with global routing able to process data in any commercial Region (18 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": 85, "b": 90 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Amazon Web Services", "b": "Google Cloud", "name": "Vendor" }, { "a": "https://bedrock-runtime.us-east-1.amazonaws.com", "b": "https://aiplatform.googleapis.com/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "OAuth or key", "b": "OAuth or key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary service under the AWS Customer Agreement and Service Terms. Third-party models carry their providers' licence terms. The AWS SDKs and the Smithy service models are Apache-2.0", "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": "2026-10-30", "b": "2026-11-05", "name": "Last release" }, { "a": "2026-10-01", "b": "2026-09-02", "name": "Terms last updated" }, { "a": "2026-05-18", "b": "2026-10-01", "name": "Privacy policy last updated" }, { "a": "yes, with an opt-out", "b": "yes", "name": "Customer content may train models" }, { "a": "yes", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "yes", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "yes", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "21.8M npm/wk", "b": "20.9M PyPI/wk", "name": "Popularity" } ], "faq": [ { "answer": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Amazon Bedrock's 81.7 (A), and leads in 5 of 7 scored categories.", "question": "Which is better for AI agents, Amazon Bedrock or Vertex AI (Gemini Enterprise Agent Platform)?" }, { "answer": "Both take an API key or an OAuth sign-in.", "question": "Do Amazon Bedrock and Vertex AI (Gemini Enterprise Agent Platform) need an API key?" }, { "answer": "Yes. Amazon Bedrock has a hosted endpoint at https://bedrock-runtime.us-east-1.amazonaws.com and Vertex AI (Gemini Enterprise Agent Platform) at https://aiplatform.googleapis.com/v1.", "question": "Can an agent call Amazon Bedrock and Vertex AI (Gemini Enterprise Agent Platform) without installing anything?" } ], "goodFor": [ { "aheadOn": null, "also": null, "goodFor": "Teams already on AWS who want Claude, GPT-6, Nova, Llama and other models under one IAM, billing and VPC boundary, with regional data controls and an SLA.", "slug": "amazon-bedrock", "watchFor": "An AWS account, IAM setup and a Region choice come before the first call, and an agent can't sign up alone" }, { "aheadOn": [ "Reliability, 99 against 80", "Agent ergonomics, 97 against 92", "Payments \u0026 pricing, 40 against 30", "Maintenance \u0026 community, 91 against 81", "Transparency \u0026 trust, 90 against 85" ], "also": [ "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": null, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-anthropic-api.json", "title": "Amazon Bedrock vs Claude API", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-anthropic-api" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-antseed.json", "title": "Amazon Bedrock vs Antseed", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-antseed" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-azure-openai.json", "title": "Amazon Bedrock vs Azure OpenAI in Foundry Models", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-azure-openai" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-blockrun-ai.json", "title": "Amazon Bedrock vs BlockRun.AI", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-blockrun-ai" }, { "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-cloudflare-ai-gateway.json", "title": "Amazon Bedrock vs Cloudflare AI Gateway", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cloudflare-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cloudflare-workers-ai.json", "title": "Amazon Bedrock vs Cloudflare Workers AI", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cloudflare-workers-ai" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cohere-chat.json", "title": "Amazon Bedrock vs Cohere Chat API (Command models)", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cohere-chat" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-deepinfra.json", "title": "Amazon Bedrock vs DeepInfra", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-deepinfra" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-deepseek-api.json", "title": "Amazon Bedrock vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-deepseek-api" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-eden-ai.json", "title": "Amazon Bedrock vs Eden AI", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-eden-ai" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-elorian-glimpse.json", "title": "Amazon Bedrock vs Glimpse", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-elorian-glimpse" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-fireworks-inference.json", "title": "Amazon Bedrock vs Fireworks AI Inference", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-fireworks-inference" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-api.json", "title": "Amazon Bedrock vs Gemini Developer API", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-api" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-groq.json", "title": "Amazon Bedrock vs GroqCloud", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-hugging-face-inference-providers.json", "title": "Amazon Bedrock vs Hugging Face Inference Providers", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-hugging-face-inference-providers" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-inkling-2-small.json", "title": "Amazon Bedrock vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-jais-3.json", "title": "Amazon Bedrock vs Jais 3", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-jais-3" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-meta-model-api.json", "title": "Amazon Bedrock vs Meta Model API", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-minimax-api.json", "title": "Amazon Bedrock vs MiniMax API", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-mistral-api.json", "title": "Amazon Bedrock vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-muse-spark-open.json", "title": "Amazon Bedrock vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-nemotron-3-5-super-vl.json", "title": "Amazon Bedrock vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-novita-ai.json", "title": "Amazon Bedrock vs Novita AI", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-openai-api.json", "title": "Amazon Bedrock vs OpenAI API", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-openrouter.json", "title": "Amazon Bedrock vs OpenRouter", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-prism-inference.json", "title": "Amazon Bedrock vs Prism Inference", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-ramp-router.json", "title": "Amazon Bedrock vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-reflection-beam.json", "title": "Amazon Bedrock vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-routerplus.json", "title": "Amazon Bedrock vs RouterPlus", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-sambanova.json", "title": "Amazon Bedrock vs SambaCloud", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-siliconflow.json", "title": "Amazon Bedrock vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-simplismart.json", "title": "Amazon Bedrock vs Simplismart", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-simplismart" }, { "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-swe-2-flash.json", "title": "Amazon Bedrock vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-tencent-tokenhub.json", "title": "Amazon Bedrock vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-together-inference.json", "title": "Amazon Bedrock vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-vercel-ai-gateway.json", "title": "Amazon Bedrock vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-xai-api.json", "title": "Amazon Bedrock vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-xai-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-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-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-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-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-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-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-vertex-ai.json", "title": "Cohere Chat API (Command models) vs Vertex AI (Gemini Enterprise Agent Platform)", "url": 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"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-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-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-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-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-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/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-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-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-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-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": [ { "amazon-bedrock": 80, "by": 19, "edge": "vertex-ai", "key": "reliability", "name": "Reliability", "vertex-ai": 99, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "amazon-bedrock": 94, "by": 0, "edge": "", "key": "schema", "name": "Schema \u0026 documentation", "vertex-ai": 94, "weight": 13 }, { "amazon-bedrock": 92, "by": 5, "edge": "vertex-ai", "key": "ergonomics", "name": "Agent ergonomics", "vertex-ai": 97, "weight": 13 }, { "amazon-bedrock": 98, "by": 1, "edge": "amazon-bedrock", "key": "security", "name": "Security \u0026 auth", "vertex-ai": 97, "weight": 14 }, { "amazon-bedrock": 30, "by": 10, "edge": "vertex-ai", "key": "payments", "name": "Payments \u0026 pricing", "vertex-ai": 40, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "amazon-bedrock": 81, "by": 10, "edge": "vertex-ai", "key": "maintenance", "name": "Maintenance \u0026 community", "vertex-ai": 91, "weight": 7 }, { "amazon-bedrock": 85, "by": 5, "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 Amazon Bedrock's 81.7 (A), and leads in 5 of 7 scored categories. Both do llm inference.", "tasks": [ { "a": "$43.88", "b": "$22.03", "cheaper": "vertex-ai", "task": "Research a product and write a sourced report", "what": "anthropic.claude-opus-5-5 on Amazon Bedrock, gemini-3.1-pro-preview on Vertex AI (Gemini Enterprise Agent Platform)" }, { "a": "$10.03", "b": "$5.09", "cheaper": "vertex-ai", "task": "Build a small four-page website", "what": "anthropic.claude-opus-5-5 on Amazon Bedrock, gemini-3.1-pro-preview on Vertex AI (Gemini Enterprise Agent Platform)" }, { "a": "$2.16", "b": "$1.09", "cheaper": "vertex-ai", "task": "Find and fix a bug in a large codebase", "what": "anthropic.claude-opus-5-5 on Amazon Bedrock, gemini-3.1-pro-preview on Vertex AI (Gemini Enterprise Agent Platform)" } ], "tutorials": [], "verdicts": { "amazon-bedrock": "Bedrock reaches Claude, GPT-6, Nova, Llama and other families through one IAM-controlled API, with a 99.9 per cent SLA and a per-Region zero-retention switch. Setup needs an AWS account, IAM permissions and a Region, capabilities vary by model, and some Regions gave five older Claude models about 34 days of notice.", "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/amazon-bedrock-vs-vertex-ai", "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-vertex-ai.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-vertex-ai.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-vertex-ai.min.md" }, "markdown": "Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Amazon Bedrock's 81.7 (A), and leads in 5 of 7 scored categories. Both do llm inference.\n\n- Amazon Bedrock: grade A, 81.7/100, rank #8 of 1510. Markdown https://www.anchorterminal.com/tools/amazon-bedrock.md · JSON https://www.anchorterminal.com/api/v1/tools/amazon-bedrock.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### Amazon Bedrock (A)\n\nGood for: Teams already on AWS who want Claude, GPT-6, Nova, Llama and other models under one IAM, billing and VPC boundary, with regional data controls and an SLA.\n\nWatch for: An AWS account, IAM setup and a Region choice come before the first call, and an agent can't sign up alone\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 80\n- Agent ergonomics, 97 against 92\n- Payments \u0026 pricing, 40 against 30\n- Maintenance \u0026 community, 91 against 81\n- Transparency \u0026 trust, 90 against 85\n\nAlso in its favour:\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) +19\n\n- Amazon Bedrock (80): AWS Health Dashboard with per-service, per-Region feeds and a public history file (20). The history lists Amazon Bedrock as disrupted in ME-CENTRAL-1 (UAE) and ME-SOUTH-1 (Bahrain) since March 2026, where AWS said on 15 September 2026 (still inside the 90-day window on 6 November) that it can't restore resources held only there. No other Bedrock event appears in the history in the 90 days to 6 November; an EU-SOUTH-2 packet-loss event on 4 October named Bedrock AgentCore, not Bedrock. This counts as one major event (10). StatusGator's third-party mirror shows 'Increased Error Rates' warnings on 24, 26 and 27 August and 10 September that we couldn't find in AWS's own history, so we didn't score them. Per-model token quotas with default values in the AWS General Reference, such as 30,000,000 tokens a minute for Opus 5.5 global inference (15). The error guide gives exponential backoff with jitter for 429, 503 and 529 and says to honour `Retry-After`, and the SDKs retry ModelNotReadyException up to five times (15). SLA of 99.9 per cent a month per Region for the model APIs, last updated 4 October 2023 (10). Converse and the current Claude, GPT-6 and Nova 2 Lite models are GA (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### Payments \u0026 pricing: Vertex AI (Gemini Enterprise Agent Platform) +10\n\n- Amazon Bedrock (30): No x402, MPP or L402 (0). Per-token prices per model, tier and Region on the public pricing page, filled from AWS's public price feed (20). New accounts get up to $200 in Free Tier credits and the Free Tier page lists Bedrock among eligible services, and the Free Tier FAQ says most new customers don't need a payment method, but AWS may still ask for one, so half, as for S3 (10). A person signs up for AWS in a browser and sets up IAM before any key exists (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### Maintenance \u0026 community: Vertex AI (Gemini Enterprise Agent Platform) +10\n\n- Amazon Bedrock (81): Model reading. The last model or API change is 30 October 2026 (OpenAI model API support and cross-Region inference in GovCloud), after structured outputs for Claude on both endpoints on 18 October (30). Models launched since 7 September 2026 get a 6-month or 45-day Legacy period, but the legacy page, which promises at least 6 months in Legacy, lists Claude 3 Haiku, 3 Sonnet, 3.5 Sonnet, 3.5 Sonnet v2 and 3.7 Sonnet as Legacy from 10 or 13 October with end of life on 13 November in several Regions, about 34 days (6 of 12, down from 10). Six models reached end of life in the 90 days to 6 November on five dates, Command R and R+ on 19 August, Claude 3 Haiku on 10 September, Nova Sonic on 14 September, Nova Canvas and Nova Reel on 30 September and Claude Sonnet 4 on 14 October (3 of 8, down from 4). Dated document history several times a month, What's New and re:Post, with direct support on a paid plan (12 of 15). SDK issue replies not sampled (5 of 10). Current official SDKs, boto3 1.43.125 on 5 November and `@aws-sdk/client-bedrock-runtime` 3.1163.0 (15). Supported runtimes stated, Python 3.10 or later and Node 20 or later (10). Down from 86 on 6 October.\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### Agent ergonomics: Vertex AI (Gemini Enterprise Agent Platform) +5\n\n- Amazon Bedrock (92): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Converse takes tools with `toolChoice` auto, any or a named tool and `strict: true`, but forced choice depends on the model behind it (17 of 20). Structured outputs on supported models only (13 of 15). Explicit and implicit prompt caching, cache reads at $0.20 per million on Opus 5.5, 0.05x input, with 5-minute and 1-hour TTLs (15). 1M-token context on Opus 5.5, Sonnet 5.5 and Nova 2 Lite, a judgement call since Bedrock has no default model (15). Batch at half price on supported models, but the pricing page shows none for Opus 5.5 or Sonnet 5.5, while Flex is half price on Nova (7 of 10). AWS SDKs in every major language plus token generators for Python, JavaScript and Java (10). Typed errors with recovery advice per code (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### Transparency \u0026 trust: Vertex AI (Gemini Enterprise Agent Platform) +5\n\n- Amazon Bedrock (85): Closed service under the AWS Customer Agreement and Service Terms, with the SDKs and Smithy models under Apache-2.0 (18, as for S3). The data retention, abuse detection and security pages agree that Bedrock stores nothing by default, name the models that retain traffic and for how long, and say retained data isn't shared with providers. The retention page's `default` mode says AWS 'may retain the data for safety and abuse-prevention purposes' without a period, and a legacy `provider_data_share` mode is kept though sharing isn't supported (25 of 30). A written lifecycle policy with Legacy and EOL dates per model, but the legacy table's 34-day Legacy periods for five Claude models in some Regions contradict its own 6-month floor (15 of 20, down from 18). AWS's sub-processor list, per the 4 October S3 check, and per-Region, geographic and global inference options, with global routing able to process data in any commercial Region (18 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## Score by category\n\n| Category | Weight | Amazon Bedrock | Vertex AI (Gemini Enterprise Agent Platform) | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 80 | 99 | Vertex AI (Gemini Enterprise Agent Platform) +19 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 94 | 94 | even |\n| Agent ergonomics | 13% (16.2 this run) | 92 | 97 | Vertex AI (Gemini Enterprise Agent Platform) +5 |\n| Security \u0026 auth | 14% (17.5 this run) | 98 | 97 | Amazon Bedrock +1 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 30 | 40 | Vertex AI (Gemini Enterprise Agent Platform) +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 81 | 91 | Vertex AI (Gemini Enterprise Agent Platform) +10 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 85 | 90 | Vertex AI (Gemini Enterprise Agent Platform) +5 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **81.7 · A** | **88.7 · AA** | |\n\n## Facts side by side\n\n| Fact | Amazon Bedrock | Vertex AI (Gemini Enterprise Agent Platform) |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Amazon Web Services | Google Cloud |\n| Hosted endpoint | `https://bedrock-runtime.us-east-1.amazonaws.com` | `https://aiplatform.googleapis.com/v1` |\n| Transports | HTTP | HTTP |\n| Auth | OAuth or key | OAuth or key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | Proprietary service under the AWS Customer Agreement and Service Terms. Third-party models carry their providers' licence terms. The AWS SDKs and the Smithy service models are Apache-2.0 | 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 | 2026-10-30 | 2026-11-05 |\n| Terms last updated | 2026-10-01 | 2026-09-02 |\n| Privacy policy last updated | 2026-05-18 | 2026-10-01 |\n| Customer content may train models | yes, with an opt-out | yes |\n| Terms restrict automated access | yes | not found in the text |\n| Terms restrict benchmarking | yes | not found in the text |\n| Terms or service can change without notice | yes | not found in the text |\n| Arbitration or class-action waiver | not found in the text | not found in the text |\n| Popularity | 21.8M npm/wk | 20.9M PyPI/wk |\n\n## What the same task costs\n\n| Task | Amazon Bedrock | Vertex AI (Gemini Enterprise Agent Platform) |\n| --- | --- | --- |\n| Research a product and write a sourced report | $43.88 | $22.03 |\n| Build a small four-page website | $10.03 | $5.09 |\n| Find and fix a bug in a large codebase | $2.16 | $1.09 |\n\n## Verdicts\n\n**Amazon Bedrock.** Bedrock reaches Claude, GPT-6, Nova, Llama and other families through one IAM-controlled API, with a 99.9 per cent SLA and a per-Region zero-retention switch. Setup needs an AWS account, IAM permissions and a Region, capabilities vary by model, and some Regions gave five older Claude models about 34 days of notice.\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### Amazon Bedrock\n\n1. Use the geographic or global inference ID from the model card, such as `global.anthropic.claude-opus-5-5`. Global routing is cheaper but can process data in any commercial Region\n2. Set `data_retention_mode` to `none` in each Region before sending sensitive data. Models that need retention then return ValidationException\n3. Back off with jitter on 429 ThrottlingException, 503 and 529 `overloaded_error`, and honour `Retry-After` when it's sent\n4. Generate short-term API keys from an IAM role for production. Long-term keys create an IAM user and AWS marks them exploration only\n5. Call ListFoundationModels in your Region and read `modelLifecycle` before pinning a model ID. Claude 3.x IDs in several Regions stop working on 13 November 2026 and requests don't redirect\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, Amazon Bedrock or Vertex AI (Gemini Enterprise Agent Platform)?\n\nVertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Amazon Bedrock's 81.7 (A), and leads in 5 of 7 scored categories.\n\n### Do Amazon Bedrock and Vertex AI (Gemini Enterprise Agent Platform) need an API key?\n\nBoth take an API key or an OAuth sign-in.\n\n### Can an agent call Amazon Bedrock and Vertex AI (Gemini Enterprise Agent Platform) without installing anything?\n\nYes. Amazon Bedrock has a hosted endpoint at https://bedrock-runtime.us-east-1.amazonaws.com 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/amazon-bedrock-vs-vertex-ai.json, and with the fewest tokens: https://www.anchorterminal.com/compare/amazon-bedrock-vs-vertex-ai.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"amazon-bedrock\", \"b\": \"vertex-ai\"}`. From a terminal: `anchor compare amazon-bedrock vertex-ai`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/amazon-bedrock.json and https://www.anchorterminal.com/api/v1/tools/vertex-ai.json\n\n## Other comparisons with Amazon Bedrock or Vertex AI (Gemini Enterprise Agent Platform)\n\n- [Amazon Bedrock vs Claude API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-anthropic-api.md)\n- [Amazon Bedrock vs Antseed](https://www.anchorterminal.com/compare/amazon-bedrock-vs-antseed.md)\n- [Amazon Bedrock vs Azure OpenAI in Foundry Models](https://www.anchorterminal.com/compare/amazon-bedrock-vs-azure-openai.md)\n- [Amazon Bedrock vs BlockRun.AI](https://www.anchorterminal.com/compare/amazon-bedrock-vs-blockrun-ai.md)\n- [Amazon Bedrock vs Cerebras Inference](https://www.anchorterminal.com/compare/amazon-bedrock-vs-cerebras-inference.md)\n- [Amazon Bedrock vs Cloudflare AI Gateway](https://www.anchorterminal.com/compare/amazon-bedrock-vs-cloudflare-ai-gateway.md)\n- [Amazon Bedrock vs Cloudflare Workers AI](https://www.anchorterminal.com/compare/amazon-bedrock-vs-cloudflare-workers-ai.md)\n- [Amazon Bedrock vs Cohere Chat API (Command models)](https://www.anchorterminal.com/compare/amazon-bedrock-vs-cohere-chat.md)\n- [Amazon Bedrock vs DeepInfra](https://www.anchorterminal.com/compare/amazon-bedrock-vs-deepinfra.md)\n- [Amazon Bedrock vs DeepSeek API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-deepseek-api.md)\n- [Amazon Bedrock vs Eden AI](https://www.anchorterminal.com/compare/amazon-bedrock-vs-eden-ai.md)\n- [Amazon Bedrock vs Glimpse](https://www.anchorterminal.com/compare/amazon-bedrock-vs-elorian-glimpse.md)\n- [Amazon Bedrock vs Fireworks AI Inference](https://www.anchorterminal.com/compare/amazon-bedrock-vs-fireworks-inference.md)\n- [Amazon Bedrock vs Gemini Developer API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-api.md)\n- [Amazon Bedrock vs GroqCloud](https://www.anchorterminal.com/compare/amazon-bedrock-vs-groq.md)\n- [Amazon Bedrock vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/amazon-bedrock-vs-hugging-face-inference-providers.md)\n- [Amazon Bedrock vs Inkling 2 Small](https://www.anchorterminal.com/compare/amazon-bedrock-vs-inkling-2-small.md)\n- [Amazon Bedrock vs Jais 3](https://www.anchorterminal.com/compare/amazon-bedrock-vs-jais-3.md)\n- [Amazon Bedrock vs Meta Model API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-meta-model-api.md)\n- [Amazon Bedrock vs MiniMax API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-minimax-api.md)\n- [Amazon Bedrock vs Mistral AI API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-mistral-api.md)\n- [Amazon Bedrock vs Muse Spark Open](https://www.anchorterminal.com/compare/amazon-bedrock-vs-muse-spark-open.md)\n- [Amazon Bedrock vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/amazon-bedrock-vs-nemotron-3-5-super-vl.md)\n- [Amazon Bedrock vs Novita AI](https://www.anchorterminal.com/compare/amazon-bedrock-vs-novita-ai.md)\n- [Amazon Bedrock vs OpenAI API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-openai-api.md)\n- [Amazon Bedrock vs OpenRouter](https://www.anchorterminal.com/compare/amazon-bedrock-vs-openrouter.md)\n- [Amazon Bedrock vs Prism Inference](https://www.anchorterminal.com/compare/amazon-bedrock-vs-prism-inference.md)\n- [Amazon Bedrock vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/amazon-bedrock-vs-ramp-router.md)\n- [Amazon Bedrock vs Beam 1.0](https://www.anchorterminal.com/compare/amazon-bedrock-vs-reflection-beam.md)\n- [Amazon Bedrock vs RouterPlus](https://www.anchorterminal.com/compare/amazon-bedrock-vs-routerplus.md)\n- [Amazon Bedrock vs SambaCloud](https://www.anchorterminal.com/compare/amazon-bedrock-vs-sambanova.md)\n- [Amazon Bedrock vs SiliconFlow](https://www.anchorterminal.com/compare/amazon-bedrock-vs-siliconflow.md)\n- [Amazon Bedrock vs Simplismart](https://www.anchorterminal.com/compare/amazon-bedrock-vs-simplismart.md)\n- [Amazon Bedrock vs StepFun API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-stepfun-api.md)\n- [Amazon Bedrock vs SWE-2 Flash](https://www.anchorterminal.com/compare/amazon-bedrock-vs-swe-2-flash.md)\n- [Amazon Bedrock vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/amazon-bedrock-vs-tencent-tokenhub.md)\n- [Amazon Bedrock vs Together AI Inference](https://www.anchorterminal.com/compare/amazon-bedrock-vs-together-inference.md)\n- [Amazon Bedrock vs Vercel AI Gateway](https://www.anchorterminal.com/compare/amazon-bedrock-vs-vercel-ai-gateway.md)\n- [Amazon Bedrock vs xAI API (Grok)](https://www.anchorterminal.com/compare/amazon-bedrock-vs-xai-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 Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/antseed-vs-vertex-ai.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 Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/blockrun-ai-vs-vertex-ai.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 Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-vertex-ai.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 Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/cohere-chat-vs-vertex-ai.md)\n- [DeepInfra vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/deepinfra-vs-vertex-ai.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 Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/eden-ai-vs-vertex-ai.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 Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/fireworks-inference-vs-vertex-ai.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 Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/groq-vs-vertex-ai.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 Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/inkling-2-small-vs-vertex-ai.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 Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/meta-model-api-vs-vertex-ai.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 Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/mistral-api-vs-vertex-ai.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- [Novita AI vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/novita-ai-vs-vertex-ai.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 Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/openrouter-vs-vertex-ai.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 Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/ramp-router-vs-vertex-ai.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 Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/routerplus-vs-vertex-ai.md)\n- [SambaCloud vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/sambanova-vs-vertex-ai.md)\n- [SiliconFlow vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/siliconflow-vs-vertex-ai.md)\n- [Simplismart vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/simplismart-vs-vertex-ai.md)\n- [StepFun API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/stepfun-api-vs-vertex-ai.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": "Amazon Bedrock vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "" } ], "description": "Vertex AI scores 88.7 (AA) to Amazon Bedrock's 81.7 (A) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Amazon Bedrock A 81.7", "Vertex AI (Gemini Enterprise Agent Platform) AA 88.7", "scores" ], "h1": "Amazon Bedrock vs Vertex AI (Gemini Enterprise Agent Platform)", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/amazon-bedrock-vs-vertex-ai", "published": "2026-10-01", "section": "tools", "title": "Amazon Bedrock vs Vertex AI for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-vertex-ai" }, "tokens": { "markdown": 7000, "slim": 3180 }, "version": 1 }