Head to head · LLM inference · October 2026 research run

Gemini 4 Hydrogen vs Vertex AI (Gemini Enterprise Agent Platform)

Vertex AI (Gemini Enterprise Agent Platform) scores 91.2 (AA) on agent readiness against Gemini 4 Hydrogen's 64.9 (B), and leads in every scored category. Both do llm inference.

Best model APIs and inference for AI agents · All 1044 models comparisons

Which one, for what

Gemini 4 Hydrogen B

Best for Agents doing everyday coding, tool calls and document work at volume on the Gemini API, including ones that need to start on a free key, or as the executor beside Carbon or Argon.

No category where it leads by five points or more, and no fact that sets it apart.

Watch for

temperature, top_p and top_k are ignored, and thinking_budget, MINIMAL, penalties and extra candidates return a 400

Vertex AI (Gemini Enterprise Agent Platform) AA

Best for Google Cloud customers who need Gemini with residency, VPC-SC, provisioned throughput and an SLA, or Claude under a Google bill.

Ahead on

  • Reliability, 99 against 45
  • Schema & documentation, 94 against 85
  • Agent ergonomics, 97 against 90
  • Security & auth, 97 against 50
  • Payments & pricing, 60 against 40
  • Maintenance & community, 91 against 85
  • Transparency & trust, 90 against 72

Also in its favour

  • Agent-ready, a grade of BB or better
  • Free to start without a card

Watch 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

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

Reliability Vertex AI (Gemini Enterprise Agent Platform) +54

Gemini 4 Hydrogen 45

Model reading for gemini-4-hydrogen on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Status page at aistudio.google.com/status with no readable components or history (10 of 20) and no readable incident record (5 of 30). Rate-limit tiers and spend limits published, per-model limits in AI Studio (5 of 15). Backoff guidance for 429 and 503 and SDK retries (15). No SLA (0). Google Cloud's release notes and model page call Hydrogen generally available, a short-term release, under the same model ID; the Gemini API pages read don't name a stage, so full marks rest on Cloud's statement (10, a judgement call; Carbon, with no stage stated anywhere, got 5). 10 + 5 + 5 + 15 + 0 + 10 = 45.

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.

Security & auth Vertex AI (Gemini Enterprise Agent Platform) +47

Gemini 4 Hydrogen 50

Model reading for gemini-4-hydrogen on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Keys bound to a service account and restricted to the Gemini API, with no scopes and a token accepted in the URL (15 of 30, the platform's deduction). Hydrogen is on the free tier, where Google's terms say content is used to improve products and may be read by humans; paid-tier content isn't (10 of 20, the platform's reading; Carbon, paid tier only, got 15). Abuse retention has no number and new paid projects store requests by default since 26 October; Google's prompt-injection figure (2.3 times more resilient on Gray Swan's benchmark) is its own, and the model card says jailbreak resistance is still being improved (5 of 15). Request logs for billed projects (15). security.txt and a reward programme, no certification naming the API (5 of 20). 15 + 10 + 5 + 15 + 5 = 50.

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).

Payments & pricing Vertex AI (Gemini Enterprise Agent Platform) +20

Gemini 4 Hydrogen 40

Model reading for gemini-4-hydrogen on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. No machine payment protocol (0). Prices published in Google's announcement without a login, $1.50 input and $7.50 output per million tokens, flat across the window; the Gemini API pricing page, now at aistudio.google.com, is still to be read for Hydrogen's row (20). A free tier with no card: Google's announcement puts Hydrogen on all tiers of the Gemini API, and the free tier needs no billing account per the gemini-api listing; its limits for Hydrogen are on that pricing page (20). A Google account and AI Studio for a key (0). 0 + 20 + 20 + 0 = 40.

Vertex AI (Gemini Enterprise Agent Platform) 60

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). Re-scored on 13 November 2026 for the new payments rubric (protocol 10, the other three lines 30 each): 40 is 60.

Transparency & trust Vertex AI (Gemini Enterprise Agent Platform) +18

Gemini 4 Hydrogen 72

Model reading for gemini-4-hydrogen on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Closed service with clear terms, SDKs Apache-2.0 (15). Free-tier content is used to improve products, paid-tier content isn't, abuse retention has no number, and request storage is on by default for new paid projects; the statements agree with each other (20 of 30). Deprecations table, and a stated 45-day minimum on Cloud (15 of 20). Data may be cached anywhere Google has facilities; no subprocessor list checked (5 of 20). A DeepMind model card gives a March 2026 knowledge cutoff, automated safety results and Frontier Safety Framework outcomes, with the full safety report marked coming soon. Every benchmark figure is Google's own. 15 + 20 + 15 + 5 = 55.

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).

Schema & documentation Vertex AI (Gemini Enterprise Agent Platform) +9

Gemini 4 Hydrogen 85

Model reading for gemini-4-hydrogen on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Discovery document for GenerateContent (20 of 25). llms.txt with Markdown twins (10). The Cloud developer guide says what Hydrogen takes, every parameter that's ignored or returns 400, the thought-signature rules and how to migrate from Gemini 3.8 Flash, though it doesn't document forced calls (15 of 20). Structured output to a JSON Schema with some keywords not enforced (10 of 15). Examples and an errors page (15). Dated changelog and model versions (15). 20 + 10 + 15 + 10 + 15 + 15 = 85.

Vertex AI (Gemini Enterprise Agent Platform) 94

Model reading. Keyless discovery document for the Agent Platform API v1, revision 20260930, with 1,128 methods and 1,493 schemas (25). No llms.txt, but every docs page answers as Markdown at .md.txt, counted as for vertex-ai-tuning (10). Model cards give limits, capabilities and retirement dates, and the 3.8 Flash card says when to use 3.7 Flash instead, but the docs mix the Vertex AI and Agent Platform names, and the OpenAI page tells new users to call the Gemini Developer API instead (16 of 20). Structured output with response_schema and response_mime_type: application/json always follows the schema per the docs, and complex schemas fail with a 400 (15). Examples on every page and a 429 guide, but we found no full error code list for generateContent (13 of 15). Versioned v1 and v1beta1 APIs and release notes with entries on most working days, newest 5 November 2026 (15).

Agent ergonomics Vertex AI (Gemini Enterprise Agent Platform) +7

Gemini 4 Hydrogen 90

Model reading for gemini-4-hydrogen on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Function calling, with forced calls by FunctionCallingConfig on the API (20). Structured output to a response_schema, listed as supported on the Cloud model page (13 of 15). Implicit caching on prefixes of 4,096 tokens or more with durable caching on by default and explicit caches not supported, per the Cloud model page; the announcement names no cached-input price (12 of 15). 1,048,576 tokens shared between input and output, with background long decode up to 1M (15). Batch at half price on the platform (10). Python and JavaScript SDKs, and an OpenAI-compatible Chat Completions surface (10). Error codes with backoff guidance (10 of 15). 20 + 13 + 12 + 15 + 10 + 10 + 10 = 90.

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).

Score by category

CategoryWeight this runGemini 4 HydrogenVertex AI (Gemini Enterprise Agent Platform)Edge
Reliability16%204599Vertex AI (Gemini Enterprise Agent Platform) +54
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.28594Vertex AI (Gemini Enterprise Agent Platform) +9
Agent ergonomics13%16.29097Vertex AI (Gemini Enterprise Agent Platform) +7
Security & auth14%17.55097Vertex AI (Gemini Enterprise Agent Platform) +47
Payments & pricing10%12.54060Vertex AI (Gemini Enterprise Agent Platform) +20
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88591Vertex AI (Gemini Enterprise Agent Platform) +6
Transparency & trust7%8.87290Vertex AI (Gemini Enterprise Agent Platform) +18
Negative events≤1500
TotalB 64.9/100AA 91.2/100

Facts side by side

FactGemini 4 HydrogenVertex AI (Gemini Enterprise Agent Platform)
KindModel APIModel API
VendorGoogleGoogle Cloud
Hosted endpointhttps://generativelanguage.googleapis.com/v1betahttps://aiplatform.googleapis.com/v1
TransportsHTTP
AuthAPI keyOAuth or key
PricingPay per usePay per use
x402nono
LicenceClosed model, used through the Gemini API and Google's apps under Google's termsProprietary service under the Google Cloud Platform terms. Partner models carry their providers' terms. The Google Gen AI SDKs are Apache-2.0
Read-only variant documentednono
llms.txtyesno
Last release2026-11-122026-11-05
Terms last updated2026-04-282026-09-02
Privacy policy last updated2026-10-012026-10-01
Customer content may train modelsyesyes
Terms restrict automated accessyesnot found in the text
Terms restrict benchmarkingyesnot found in the text
Terms or service can change without noticenot found in the textnot found in the text
Arbitration or class-action waivernot found in the textnot found in the text
Popularitynone20.9M PyPI/wk

How the scores have moved

Verdicts

Gemini 4 Hydrogen

Google's fast Gemini 4 model, on every tier of the Gemini API including the free one, at $1.50 and $7.50 per million tokens with a 1M-token budget, four thinking levels, function calling and structured output. Sampling parameters are ignored, explicit caching isn't supported, it's a short-term release with 45 days' notice on Cloud, and the benchmarks are Google's.

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.

Before you call either

Gemini 4 Hydrogen

  1. Call generateContent at https://generativelanguage.googleapis.com/v1beta with model gemini-4-hydrogen and an x-goog-api-key
  2. Set thinking_level instead of thinking_budget; the default is HIGH, so set MEDIUM to keep 3.8 Flash's latency
  3. Don't send temperature, top_p, top_k, penalties or candidate_count above 1
  4. Pass every thought_signature back in its original part, on the first parallel functionCall only, or the call returns a 400
  5. Put static content of 4,096 tokens or more first so implicit caching applies, and keep confidential prompts off the free tier

Vertex AI (Gemini Enterprise Agent Platform)

  1. Call the global location on aiplatform.googleapis.com unless data residency requires a Region. The 429 guide says it spreads load and reduces errors
  2. Back off exponentially on 429 Resource exhausted. On Standard PayGo it means shared capacity is busy, not a fixed quota
  3. Send response_schema with response_mime_type: application/json. JSON mode alone doesn't guarantee valid output
  4. Set store to false on Interactions API calls. It defaults to true and keeps prompts and responses
  5. 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

Questions

Which is better for AI agents, Gemini 4 Hydrogen or Vertex AI (Gemini Enterprise Agent Platform)?

Vertex AI (Gemini Enterprise Agent Platform) scores 91.2 (AA) on agent readiness against Gemini 4 Hydrogen's 64.9 (B), and leads in every scored category.

Do Gemini 4 Hydrogen and Vertex AI (Gemini Enterprise Agent Platform) need an API key?

Gemini 4 Hydrogen needs an API key. Vertex AI (Gemini Enterprise Agent Platform) takes an API key or an OAuth sign-in.

Can an agent call Gemini 4 Hydrogen and Vertex AI (Gemini Enterprise Agent Platform) without installing anything?

Yes. Gemini 4 Hydrogen has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta and Vertex AI (Gemini Enterprise Agent Platform) at https://aiplatform.googleapis.com/v1.

Other comparisons with Gemini 4 Hydrogen or Vertex AI (Gemini Enterprise Agent Platform)

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