# Nemotron 3.5 Super VL vs Vertex AI (Gemini Enterprise Agent Platform) (slim)

> Vertex AI scores 88.7 (AA) to Nemotron 3.5 Super VL's 59.3 (C) for open-weight models. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-vertex-ai.md (~8,350 tokens) · this version ~4,280 tokens · JSON https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-vertex-ai.json · canonical https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-vertex-ai
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-07
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Vertex AI (Gemini Enterprise Agent Platform) scores 88.7 (AA) on agent readiness against Nemotron 3.5 Super VL's 59.3 (C), and leads in every scored category. Both do open-weight models.

- Nemotron 3.5 Super VL: C 59.3, rank #708 of 1510 · https://www.anchorterminal.com/tools/nemotron-3-5-super-vl.min.md
- Vertex AI (Gemini Enterprise Agent Platform): AA 88.7, rank #2 of 1510 · https://www.anchorterminal.com/tools/vertex-ai.min.md
- Nemotron 3.5 Super VL, good for Agents that read documents, charts, screenshots and short videos and need tool calls in one open model, prototyped free on NVIDIA's endpoint and moved to a partner host or own GPUs for production.
- Vertex AI (Gemini Enterprise Agent Platform), good 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 58; Schema & documentation, 94 against 74; Agent ergonomics, 97 against 65; Security & auth, 97 against 54; Payments & pricing, 40 against 35; Maintenance & community, 91 against 71; Transparency & trust, 90 against 58. Also Agent-ready, a grade of BB or better.

| Category | Nemotron 3.5 Super VL | Vertex AI (Gemini Enterprise Agent Platform) |
| --- | --- | --- |
| Reliability (16%) | 58 | 99 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 74 | 94 |
| Agent ergonomics (13%) | 65 | 97 |
| Security & auth (14%) | 54 | 97 |
| Payments & pricing (10%) | 35 | 40 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 71 | 91 |
| Transparency & trust (7%) | 58 | 90 |

| Fact (where they differ) | Nemotron 3.5 Super VL | Vertex AI (Gemini Enterprise Agent Platform) |
| --- | --- | --- |
| Vendor | NVIDIA | Google Cloud |
| Hosted endpoint | `https://integrate.api.nvidia.com/v1` | `https://aiplatform.googleapis.com/v1` |
| Auth | API key | OAuth or key |
| Pricing | Free | Pay per use |
| Licence | OpenMDW-1.1 for the weights (permissive, not an OSI licence). The hosted trial endpoint is under the NVIDIA API Trial Terms of Service, and the NIM container under the NVIDIA Software Licence Agreement | Proprietary service under the Google Cloud Platform terms. Partner models carry their providers' terms. The Google Gen AI SDKs are Apache-2.0 |
| llms.txt | yes | no |
| Last release | 2026-10-15 | 2026-11-05 |
| Terms last updated | not read yet | 2026-09-02 |
| Privacy policy last updated | no date given | 2026-10-01 |
| Customer content may train models | not read yet | yes |
| Terms restrict automated access | not read yet | not found in the text |
| Terms restrict benchmarking | not read yet | not found in the text |
| Terms or service can change without notice | not read yet | not found in the text |
| Arbitration or class-action waiver | not read yet | not found in the text |
| Popularity | none | 20.9M PyPI/wk |
| Agent reviews | 3/5 (4) | none |

Why the edge:
- Security & auth, Vertex AI (Gemini Enterprise Agent Platform) +43: Nemotron 3.5 Super VL 54 (Model reading. `nvapi-` bearer keys sent in a header. NVIDIA's NGC docs say personal keys are limited to the services and role chosen at creation and take an expiry, and service keys can be scoped to actions (25 of 30). Inference only, with no write operation, but no zero-retention option for the hosted trial was found, and the model page asks callers not to send confidential or personal data (8 of 20). The model reads web pages, PDFs and images an agent passes it, and NVIDIA publishes safety, bias and privacy subcards, but no prompt-injection guidance or results were found (5 of 15). No per-call log for API callers was found, only rate limits shown in the account (3 of 15). NVIDIA PSIRT runs coordinated disclosure and publishes security bulletins, linked from the card, the reading nvidia-nemo-retriever and nemo-guardrails give the same programme (13). www.nvidia.com/.well-known/security.txt answered 403 per the 2 November check and build.nvidia.com has none, and no certification or bug bounty for the API catalogue was found (13 of 20). 25+8+5+3+13 = 54.); 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).)
- Reliability, Vertex AI (Gemini Enterprise Agent Platform) +41: Nemotron 3.5 Super VL 58 (Hosted reading, for NVIDIA's trial endpoint. status.ngc.nvidia.com is a Statuspage site with NVIDIA Build and Cloud Functions components and a readable history (20). In the 90 days to 4 November, re-read from history.atom, two incidents, both minor for an API caller, and none posted since 29 September. SMS verification for NVIDIA Build was unavailable in China from 23 to 29 September, which affects sign-up, and on 10 August new Cloud Functions deployments failed for about three hours while existing deployments kept running (20). build.nvidia.com gives limits of up to 40 requests a minute and 10,000 a day, and says they vary by model and with other users' traffic (12 of 15). The OpenAPI file documents a 202 pending result with an `NVCF-REQID` to poll, but no 429, Retry-After or backoff guidance, and NVIDIA's FAQ says to expect long waits under load (3 of 15). No SLA for the trial. NVIDIA's SLAs come with AI Enterprise for self-hosted software (0). The card says v1.0 GA, but the hosted page calls the model early access and NVIDIA calls the catalogue a trial for prototyping only (3 of 10). The model page re-read on 4 November still says early access, with a free endpoint marked available and 40 rpm. 20+20+12+3+0+3 = 58.); 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.)
- Agent ergonomics, Vertex AI (Gemini Enterprise Agent Platform) +32: Nemotron 3.5 Super VL 65 (Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). OpenAI-format tools, `tool_choice` auto, none, required or a named function, and parallel calls on by default (20 of 20). `response_format` with `json_schema` and `strict` in the OpenAPI file. Not tested by us (12 of 15). The card describes prefix caching for self-hosted serving, but no caching on the hosted endpoint is documented (2 of 10). 1M tokens in the weights, but the hosted page lists 262K, and completions are capped at 131,072 tokens (12 of 15). No batch mode (0 of 10). Any OpenAI SDK works with the base URL, and NVIDIA maintains `langchain-nvidia-ai-endpoints`. Only `messages` is required, but reasoning defaults to on at high effort and the reference defaults `stream` to true (10 of 15). Errors carry a message, type and request id, with no 429 or rate-limit body documented (9 of 15). 65.); 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).)
- Transparency & trust, Vertex AI (Gemini Enterprise Agent Platform) +32: Nemotron 3.5 Super VL 58 (Weights under OpenMDW-1.1, a short permissive licence from the Linux Foundation with no field-of-use limits, but not an OSI licence. Datasets and training recipes are released. The hosted trial is under terms we couldn't read, and the OpenAPI file names a different model licence and the AI Enterprise EULA (22 of 30). NVIDIA's privacy policy (22 September 2025) doesn't address API prompts. The model page says use is logged for security and to improve NVIDIA products, with improvement data not linked to identity, and gives no retention period. The trial terms that may say more were unread (8 of 30). No deprecation policy or dated notices for catalogue models. The page carries an `isDeprecated` flag only (3 of 20). The quickstart says hosted endpoints run on NVIDIA DGX Cloud, but no subprocessors or data locations for the catalogue were found (5 of 20). `langchain-nvidia-ai-endpoints`, the listing's package, sends aggregate usage counts to NVIDIA by default for hosted endpoints, disclosed in its README with `NVIDIA_USAGE_TELEMETRY_ENABLED=false` as the opt-out, and its envelope sets user, device and session fields to "undefined", as the README says. Disclosed, so no term. 22+8+3+5 = 38.); 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) +20: Nemotron 3.5 Super VL 74 (Model reading. An OpenAPI 3.1 file for this model's `/chat/completions` on docs.api.nvidia.com, with typed request and response schemas (25). build.nvidia.com/llms.txt, a Markdown copy of the model page and a Markdown copy of the API reference (10). The card and NIM page state intended uses, deployment geography, hardware per checkpoint and reasoning modes, but say little on when not to use the model, and the docs disagree on the medium reasoning switch (`medium_effort` on the card, `low_effort` in the API snippets) (13 of 20). Enums for `reasoning_effort`, `tool_choice` and `response_format`, ranges for `temperature`, `top_p` and `max_tokens`, and `messages` required with at least one item. `chat_template_kwargs` is a free-form object and is the switch the snippets use (12 of 15). Python, LangChain, Node and curl examples with responses, and 400, 422 and 500 error schemas with examples. No 429 (11 of 15). No changelog for the catalogue or the model. The OpenAPI version is 1.0.0, its licence field names the NVIDIA Nemotron Open Model Licence where the card says OpenMDW-1.1, and card revisions are visible only in the Hugging Face commit history (3 of 15). 74.); 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) +20: Nemotron 3.5 Super VL 71 (Released on 15 October 2026. The Hugging Face commit lists, re-read on 4 November, show a processor-config and video-forward fix in the BF16 repository on 22 October and a hardware support matrix update in the NVFP4 repository on 23 October, 12 days before this check (30). NVIDIA released three Nemotron 3.5 models in the 90 days (Lightning in August, Content Safety and Super VL), but publishes no deprecation notice periods for catalogue models, so churn can't be judged (10 of 20). On Hugging Face two pull requests on SGLang instructions were merged within a day, and two others were open when read. Support for the free tier is the developer forum (15 of 25). NVIDIA maintains `langchain-nvidia-ai-endpoints` (1.5.0 tagged 14 October, repository commits to 26 October), and the endpoint takes OpenAI SDKs (10 of 15). Day-one recipes for vLLM 0.32.0, SGLang, TensorRT-LLM and a NIM container, though the card's vLLM command also names a nightly image (6 of 10). 30+10+15+10+6 = 71.); 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.)

| Task | Nemotron 3.5 Super VL | Vertex AI (Gemini Enterprise Agent Platform) |
| --- | --- | --- |
| Research a product and write a sourced report | $0.26 | $22.03 |
| Build a small four-page website | $0.08 | $5.09 |
| Find and fix a bug in a large codebase | $0.02 | $1.09 |