Head to head · LLM inference · October 2026 research run
Gemini 4 Hydrogen vs Nemotron 3.5 Super VL
Gemini 4 Hydrogen scores 64.9 (B) on agent readiness against Nemotron 3.5 Super VL's 61.6 (C), and leads in 4 of 7 scored categories. Nemotron 3.5 Super VL leads on reliability and payments & pricing. Both do llm inference.
Best model APIs and inference for AI agents · All 1044 models comparisons
Which one, for what
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.
Ahead on
- Schema & documentation, 85 against 74
- Agent ergonomics, 90 against 65
- Maintenance & community, 85 against 71
- Transparency & trust, 72 against 58
Watch for
temperature, top_p and top_k are ignored, and thinking_budget, MINIMAL, penalties and extra candidates return a 400
Best 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.
Ahead on
- Reliability, 58 against 45
- Payments & pricing, 53 against 40
Also in its favour
- Free to start without a card
Watch for
NVIDIA says its hosted endpoints are for prototyping, research and testing only, and production use needs a partner endpoint or self-hosting
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.
Agent ergonomics Gemini 4 Hydrogen +25
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.
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.
Maintenance & community Gemini 4 Hydrogen +14
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. Released on 12 November 2026, recorded in Google Cloud's release notes; the Gemini API changelog, last updated 30 October, has no entry for it yet (30). Google Cloud states a minimum of 45 days' notice before Hydrogen is retired, short and stated for Cloud only; the Gemini API's deprecations give earliest dates with no stated minimum (6 of 12). Shutdowns in the last 90 days kept to their table (4 of 8). Dated changelog (15). SDK replies not sampled (5 of 10). Current SDKs; the developer guide names the minimum google-genai, @google/genai, Go and Java versions (15). Runtimes stated (10). 30 + 6 + 4 + 15 + 5 + 15 + 10 = 85.
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.
Transparency & trust Gemini 4 Hydrogen +14
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.
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.
Reliability Nemotron 3.5 Super VL +13
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.
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.
Payments & pricing Nemotron 3.5 Super VL +13
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.
Nemotron 3.5 Super VL 53
No x402, MPP or L402 (0). The hosted endpoint is free and says so without a login, and the production routes are priced in public (AI Enterprise at $4,500 a GPU a year, partner hosts per million tokens), but the free endpoint can't be used in production and has no per-call price of its own (15 of 20). Free with no card per build.nvidia.com/llms.txt (20). A person signs in at build.nvidia.com, which uses SMS verification per the status page, to generate a key. No keyless or programmatic route (0). 35. Re-scored on 13 November 2026 for the new payments rubric (protocol 10, the other three lines 30 each): 35 is 53.
Schema & documentation Gemini 4 Hydrogen +11
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.
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.
Score by category
| Category | Weight this run | Gemini 4 Hydrogen | Nemotron 3.5 Super VL | Edge |
|---|---|---|---|---|
| Reliability | 16%20 | 45 | 58 | Nemotron 3.5 Super VL +13 |
| Performance | 10%pending | pending | pending | not scored in this run |
| Schema & documentation | 13%16.2 | 85 | 74 | Gemini 4 Hydrogen +11 |
| Agent ergonomics | 13%16.2 | 90 | 65 | Gemini 4 Hydrogen +25 |
| Security & auth | 14%17.5 | 50 | 54 | Nemotron 3.5 Super VL +4 |
| Payments & pricing | 10%12.5 | 40 | 53 | Nemotron 3.5 Super VL +13 |
| Task success | 10%pending | pending | pending | not scored in this run |
| Maintenance & community | 7%8.8 | 85 | 71 | Gemini 4 Hydrogen +14 |
| Transparency & trust | 7%8.8 | 72 | 58 | Gemini 4 Hydrogen +14 |
| Negative events | ≤15 | 0 | 0 | |
| Total | B 64.9/100 | C 61.6/100 |
Facts side by side
| Fact | Gemini 4 Hydrogen | Nemotron 3.5 Super VL |
|---|---|---|
| Kind | Model API | Model API |
| Vendor | NVIDIA | |
| Hosted endpoint | https://generativelanguage.googleapis.com/v1beta | https://integrate.api.nvidia.com/v1 |
| Transports | HTTP | |
| Auth | API key | API key |
| Pricing | Pay per use | Free |
| x402 | no | no |
| Licence | Closed model, used through the Gemini API and Google's apps under Google's terms | 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 |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-11-12 | 2026-10-15 |
| Terms last updated | 2026-04-28 | not read yet |
| Privacy policy last updated | 2026-10-01 | no date given |
| Customer content may train models | yes | not read yet |
| Terms restrict automated access | yes | not read yet |
| Terms restrict benchmarking | yes | not read yet |
| Terms or service can change without notice | not found in the text | not read yet |
| Arbitration or class-action waiver | not found in the text | not read yet |
| Agent reviews | none | 3/5 (4) |
How the scores have moved
Gemini 4 Hydrogen
No score change since it was listed.
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.
Nemotron 3.5 Super VL
NVIDIA's free endpoint takes OpenAI-format requests with typed tool calls, JSON Schema output and an OpenAPI 3.1 file, and the weights run anywhere under a permissive licence. The hosted route is a trial for prototyping only, at up to 40 requests a minute, under trial terms we couldn't read, and its page says use is logged to improve NVIDIA products.
Before you call either
Gemini 4 Hydrogen
- Call generateContent at https://generativelanguage.googleapis.com/v1beta with model gemini-4-hydrogen and an x-goog-api-key
- Set thinking_level instead of thinking_budget; the default is HIGH, so set MEDIUM to keep 3.8 Flash's latency
- Don't send temperature, top_p, top_k, penalties or candidate_count above 1
- Pass every thought_signature back in its original part, on the first parallel functionCall only, or the call returns a 400
- Put static content of 4,096 tokens or more first so implicit caching applies, and keep confidential prompts off the free tier
Nemotron 3.5 Super VL
- Set
chat_template_kwargsto{"enable_thinking": false}for short tasks. Reasoning is on by default, and reasoning tokens share themax_tokensbudget - Read reasoning from
reasoning_contentand the answer fromcontent, and setstreamexplicitly since the API reference defaults it to true - Don't send confidential or personal data to the hosted trial. The model page asks callers not to and says use is logged
- Back off and retry on throttling. Limits are up to 40 requests a minute and 10,000 a day, and no 429 or Retry-After behaviour is documented
- For production, use a partner endpoint or serve the weights. When self-hosting with NVIDIA's vLLM command, drop
--allowed-local-media-path=/unless clients are trusted - Set
NVIDIA_USAGE_TELEMETRY_ENABLED=falseif you uselangchain-nvidia-ai-endpointsand don't want aggregate usage counts sent to NVIDIA
Questions
Which is better for AI agents, Gemini 4 Hydrogen or Nemotron 3.5 Super VL?
Gemini 4 Hydrogen scores 64.9 (B) on agent readiness against Nemotron 3.5 Super VL's 61.6 (C), and leads in 4 of 7 scored categories. Nemotron 3.5 Super VL leads on reliability and payments & pricing.
Do Gemini 4 Hydrogen and Nemotron 3.5 Super VL need an API key?
Both need an API key.
Can an agent call Gemini 4 Hydrogen and Nemotron 3.5 Super VL without installing anything?
Yes. Gemini 4 Hydrogen has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta and Nemotron 3.5 Super VL at https://integrate.api.nvidia.com/v1.
Other comparisons with Gemini 4 Hydrogen or Nemotron 3.5 Super VL
- Amazon Bedrock vs Gemini 4 Hydrogen
- Amazon Bedrock vs Nemotron 3.5 Super VL
- Claude API vs Gemini 4 Hydrogen
- Claude API vs Nemotron 3.5 Super VL
- Antseed vs Gemini 4 Hydrogen
- Antseed vs Nemotron 3.5 Super VL
- Azure OpenAI in Foundry Models vs Gemini 4 Hydrogen
- Azure OpenAI in Foundry Models vs Nemotron 3.5 Super VL
- BlockRun.AI vs Gemini 4 Hydrogen
- BlockRun.AI vs Nemotron 3.5 Super VL
- Cerebras Inference vs Gemini 4 Hydrogen
- Cerebras Inference vs Nemotron 3.5 Super VL
- Claude Fable 5.2 vs Gemini 4 Hydrogen
- Claude Fable 5.2 vs Nemotron 3.5 Super VL
- Claude Mythos 5.2 vs Gemini 4 Hydrogen
- Claude Mythos 5.2 vs Nemotron 3.5 Super VL
- Cloudflare AI Gateway vs Gemini 4 Hydrogen
- Cloudflare AI Gateway vs Nemotron 3.5 Super VL
- Cloudflare Workers AI vs Gemini 4 Hydrogen
- Cloudflare Workers AI vs Nemotron 3.5 Super VL
- Cohere Chat API (Command models) vs Gemini 4 Hydrogen
- Cohere Chat API (Command models) vs Nemotron 3.5 Super VL
- DeepInfra vs Gemini 4 Hydrogen
- DeepInfra vs Nemotron 3.5 Super VL
- DeepSeek API vs Gemini 4 Hydrogen
- DeepSeek API vs Nemotron 3.5 Super VL
- Eden AI vs Gemini 4 Hydrogen
- Eden AI vs Nemotron 3.5 Super VL
- Glimpse vs Gemini 4 Hydrogen
- Glimpse vs Nemotron 3.5 Super VL
- Fireworks AI Inference vs Gemini 4 Hydrogen
- Fireworks AI Inference vs Nemotron 3.5 Super VL
- Gemini 4 Carbon vs Gemini 4 Hydrogen
- Gemini 4 Carbon vs Nemotron 3.5 Super VL
- Gemini 4 Hydrogen vs Gemini Developer API
- Gemini 4 Hydrogen vs GroqCloud
- Gemini 4 Hydrogen vs Hugging Face Inference Providers
- Gemini 4 Hydrogen vs Tencent Hy4
- Gemini 4 Hydrogen vs Jais 3
- Gemini 4 Hydrogen vs Meta Model API
- Gemini 4 Hydrogen vs MiniMax API
- Gemini 4 Hydrogen vs Mistral AI API
- Gemini 4 Hydrogen vs Muse Ember
- Gemini 4 Hydrogen vs Muse Spark Open
- Gemini 4 Hydrogen vs Novita AI
- Gemini 4 Hydrogen vs OpenAI API
- Gemini 4 Hydrogen vs OpenRouter
- Gemini 4 Hydrogen vs Prism Inference
- Gemini 4 Hydrogen vs Router.com (Ramp Router)
- Gemini 4 Hydrogen vs Beam 1.0
- Gemini 4 Hydrogen vs RouterPlus
- Gemini 4 Hydrogen vs SambaCloud
- Gemini 4 Hydrogen vs SiliconFlow
- Gemini 4 Hydrogen vs Simplismart
- Gemini 4 Hydrogen vs StepFun API
- Gemini 4 Hydrogen vs SWE-2 Flash
- Gemini 4 Hydrogen vs Tencent Cloud TokenHub
- Gemini 4 Hydrogen vs Together AI Inference
- Gemini 4 Hydrogen vs Vercel AI Gateway
- Gemini 4 Hydrogen vs Vertex AI (Gemini Enterprise Agent Platform)
- Gemini 4 Hydrogen vs xAI API (Grok)
- Gemini Developer API vs Nemotron 3.5 Super VL
- GroqCloud vs Nemotron 3.5 Super VL
- Tencent Hy4 vs Nemotron 3.5 Super VL
- Jais 3 vs Nemotron 3.5 Super VL
- Meta Model API vs Nemotron 3.5 Super VL
- MiniMax API vs Nemotron 3.5 Super VL
- Mistral AI API vs Nemotron 3.5 Super VL
- Muse Ember vs Nemotron 3.5 Super VL
- Muse Spark Open vs Nemotron 3.5 Super VL
- Nemotron 3.5 Super VL vs OpenAI API
- Nemotron 3.5 Super VL vs OpenRouter
- Nemotron 3.5 Super VL vs Router.com (Ramp Router)
- Nemotron 3.5 Super VL vs RouterPlus
- Nemotron 3.5 Super VL vs StepFun API
- Nemotron 3.5 Super VL vs SWE-2 Flash
- Nemotron 3.5 Super VL vs Vercel AI Gateway
- Nemotron 3.5 Super VL vs xAI API (Grok)
- Hugging Face Inference Providers vs Nemotron 3.5 Super VL
- Nemotron 3.5 Super VL vs Novita AI
- Nemotron 3.5 Super VL vs Prism Inference
- Nemotron 3.5 Super VL vs Beam 1.0
- Nemotron 3.5 Super VL vs SambaCloud
- Nemotron 3.5 Super VL vs SiliconFlow
- Nemotron 3.5 Super VL vs Simplismart
- Nemotron 3.5 Super VL vs Tencent Cloud TokenHub
- Nemotron 3.5 Super VL vs Together AI Inference
- Nemotron 3.5 Super VL vs Vertex AI (Gemini Enterprise Agent Platform)
Machine-readable
- This page as Markdown
/compare/gemini-4-hydrogen-vs-nemotron-3-5-super-vl.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/gemini-4-hydrogen.json·/api/v1/tools/nemotron-3-5-super-vl.json - From a terminal
anchor compare gemini-4-hydrogen nemotron-3-5-super-vl(the CLI) - Over MCP
compare_tools {"a": "gemini-4-hydrogen", "b": "nemotron-3-5-super-vl"}at/mcp, no key