Head to head · LLM inference · October 2026 research run

Tencent Hy4 vs Vertex AI (Gemini Enterprise Agent Platform)

Vertex AI (Gemini Enterprise Agent Platform) scores 91.2 (AA) on agent readiness against Tencent Hy4's 64 (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

Tencent Hy4 B

Best for Long-context agent work, coding and office or finance tasks on a 1M-token context with images, for teams already on Tencent Cloud or happy to verify an account there.

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

Watch for

Weights, licence and system card are promised but not published; tencent/Hy4 didn't answer on Hugging Face on 11 November

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 46
  • Schema & documentation, 94 against 73
  • Agent ergonomics, 97 against 86
  • Security & auth, 97 against 71
  • Payments & pricing, 60 against 45
  • Maintenance & community, 91 against 73
  • Transparency & trust, 90 against 52

Also in its favour

  • Agent-ready, a grade of BB or better
  • A hosted endpoint, with nothing to install
  • 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) +53

Tencent Hy4 46

Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. No public status page (0) and so no incident record to read (5 of 30). Per-model rate limits only in the console and DescribeModelQuota (8 of 15). Six 429 codes, Retry-After and backoff advice (13 of 15). The TokenHub SLA promises 99.5% a month, and Hy4 is Tencent's own model, so the third-party exclusion doesn't apply (10). Released as hy4 on 4 November, a separate id from hy4-preview, with no preview label (10). 0 + 5 + 8 + 13 + 10 + 10 = 46.

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.

Transparency & trust Vertex AI (Gemini Enterprise Agent Platform) +38

Tencent Hy4 52

Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. Closed service under the TokenHub terms, but Tencent's release headline calls Hy4 open source while the weights and system card are only promised 'in the coming days', with no licence stated, and tencent/Hy4 didn't answer on Hugging Face on 11 November (14 of 30). Terms and FAQ agree inputs aren't used for training; the privacy policy renders only with JavaScript and wasn't read (15 of 30). Dated retirement notices and shutdown fields (13 of 20). Processing generally in mainland China for the China site, Singapore for the international one (13 of 20). Every benchmark in the release is Tencent's own or a partner's. 14 + 15 + 13 + 13 = 55.

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).

Security & auth Vertex AI (Gemini Enterprise Agent Platform) +26

Tencent Hy4 71

Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. Bearer keys limited by model, service, IP range and token quota, long-lived with no rotation (26 of 30). The terms say inputs aren't used to train Tencent Cloud's own models, and Hy4 is first party, so no third party's terms apply (14 of 20). Retention only as long as the service needs, no periods (7 of 15). Per-call audit logs and optional full logs to the customer's CLS (14 of 15). No security.txt; Tencent's TSRC bounty covers Tencent Cloud; no certification checked (10 of 20). 26 + 14 + 7 + 14 + 10 = 71.

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).

Schema & documentation Vertex AI (Gemini Enterprise Agent Platform) +21

Tencent Hy4 73

Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. No OpenAPI file for inference; field pages for the OpenAI and Anthropic formats as TokenHub implements them (12 of 25). llms.txt with Markdown copies (10). The model list, updated 9 November, gives hy4's context, input and output limits and marks thinking, structured output, function calling, caching and image understanding; computer use, which Tencent's release names, isn't marked (13 of 20). Typed field pages (10 of 15). Examples in five languages and an error page of 30 codes (14 of 15). Dated release notes, with hy4 added on 4 November (14 of 15). 12 + 10 + 13 + 10 + 14 + 14 = 73.

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).

Maintenance & community Vertex AI (Gemini Enterprise Agent Platform) +18

Tencent Hy4 73

Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. Added on 4 November 2026 per the release notes; the model list and price page were updated on 9 November (30). Retirement notices of 21 to 33 days, no minimum written (7 of 12). Heavy retirement churn on the platform (3 of 8). Dated release notes and announcements, round-the-clock support (13 of 15). CLI replies not sampled (3 of 10). Control-plane SDKs and CLI, no inference SDK of its own (12 of 15). CLI runtime stated, CI not checked (5 of 10). 30 + 7 + 3 + 13 + 3 + 12 + 5 = 73. The model is a week old, so these lines are TokenHub's habits more than Hy4's record.

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.

Payments & pricing Vertex AI (Gemini Enterprise Agent Platform) +15

Tencent Hy4 45

Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. No machine payment protocol (0). The price page, updated 9 November, lists ¥6 input, ¥0.3 cached and ¥18 output per million tokens, with Hy4 billed at 50% until 31 December 2026 (20). TokenHub's campaign of 1M free tokens per language model, read on 1 November, isn't confirmed for hy4 on the price page, so half (10 of 20, a judgement call). A person signs up with real-name verification (0). 0 + 20 + 10 + 0 = 30. Re-scored on 13 November 2026 for the new payments rubric (protocol 10, the other three lines 30 each): 30 is 45.

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.

Score by category

CategoryWeight this runTencent Hy4Vertex AI (Gemini Enterprise Agent Platform)Edge
Reliability16%204699Vertex AI (Gemini Enterprise Agent Platform) +53
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27394Vertex AI (Gemini Enterprise Agent Platform) +21
Agent ergonomics13%16.28697Vertex AI (Gemini Enterprise Agent Platform) +11
Security & auth14%17.57197Vertex AI (Gemini Enterprise Agent Platform) +26
Payments & pricing10%12.54560Vertex AI (Gemini Enterprise Agent Platform) +15
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.87391Vertex AI (Gemini Enterprise Agent Platform) +18
Transparency & trust7%8.85290Vertex AI (Gemini Enterprise Agent Platform) +38
Negative events≤1500
TotalB 64/100AA 91.2/100

Facts side by side

FactTencent Hy4Vertex AI (Gemini Enterprise Agent Platform)
KindModel APIModel API
VendorTencent (Hy team)Google Cloud
Hosted endpointno (local only)https://aiplatform.googleapis.com/v1
TransportsHTTPHTTP
AuthAPI keyOAuth or key
PricingPay per usePay per use
x402nono
LicenceHosted model under the Tencent Cloud TokenHub terms. Tencent says weights and a system card will follow; no licence is stated yetProprietary 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 release2026-11-042026-11-05
Terms last updatedcouldn't be read2026-09-02
Privacy policy last updatedcouldn't be read2026-10-01
Customer content may train modelscouldn't be readyes
Terms restrict automated accesscouldn't be readnot found in the text
Terms restrict benchmarkingcouldn't be readnot found in the text
Terms or service can change without noticecouldn't be readnot found in the text
Arbitration or class-action waivercouldn't be readnot found in the text
Popularitynone20.9M PyPI/wk

How the scores have moved

Verdicts

Tencent Hy4

Tencent's flagship model is on TokenHub as hy4, with a 1M-token context, image understanding, function calling and caching, at ¥6 input and ¥18 output per million tokens, half price until the end of 2026. The weights it is called open source for aren't published yet, and every benchmark is Tencent's own.

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

Tencent Hy4

  1. Use model id hy4 on TokenHub's OpenAI- or Anthropic-compatible endpoints; hy4-preview is a separate, older model
  2. Keep input under 960K tokens and expect at most 64K output
  3. Reuse prompt prefixes: cached input is ¥0.3 against ¥6
  4. Check the price page for the end of the 50% discount on 31 December 2026 before budgeting
  5. Read rate limits from the console or DescribeModelQuota; the public docs don't give them for chat models

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, Tencent Hy4 or Vertex AI (Gemini Enterprise Agent Platform)?

Vertex AI (Gemini Enterprise Agent Platform) scores 91.2 (AA) on agent readiness against Tencent Hy4's 64 (B), and leads in every scored category.

Do Tencent Hy4 and Vertex AI (Gemini Enterprise Agent Platform) need an API key?

Tencent Hy4 needs an API key. Vertex AI (Gemini Enterprise Agent Platform) takes an API key or an OAuth sign-in.

Can an agent call Tencent Hy4 and Vertex AI (Gemini Enterprise Agent Platform) without installing anything?

No hosted endpoint is listed for Tencent Hy4. Vertex AI (Gemini Enterprise Agent Platform) has a hosted endpoint at https://aiplatform.googleapis.com/v1.

Other comparisons with Tencent Hy4 or Vertex AI (Gemini Enterprise Agent Platform)

Machine-readable

For companies

Do agents find, use and choose your tools?

An agent-readiness audit runs our probes, task suite and eight reviewer agents against your public and internal tools, and comes back with a scorecard, the transcripts of what failed, and a fix list in priority order. From $2,500, re-run included. We never take payment to move a rank. We do help companies earn one.