# Gemini 4 Hydrogen vs OpenAI API

> OpenAI scores 85.8 (AA) to Gemini 4 Hydrogen's 64.9 (B) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-openai-api
- Markdown: https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-openai-api.md (~7,450 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-13

OpenAI API scores 85.8 (AA) on agent readiness against Gemini 4 Hydrogen's 64.9 (B), and leads in every scored category. Both do llm inference.

- Gemini 4 Hydrogen: grade B, 64.9/100, rank #546 of 1524. Markdown https://www.anchorterminal.com/tools/gemini-4-hydrogen.md · JSON https://www.anchorterminal.com/api/v1/tools/gemini-4-hydrogen.json
- OpenAI API: grade AA, 85.8/100, rank #5 of 1524. Markdown https://www.anchorterminal.com/tools/openai-api.md · JSON https://www.anchorterminal.com/api/v1/tools/openai-api.json
- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md
- All 1044 models comparisons: https://www.anchorterminal.com/compare/inference/index.md

## Which one, for what

### Gemini 4 Hydrogen (B)

Good 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.

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

### OpenAI API (AA)

Good for: Agents that want one vendor for text, images, audio, hosted tools and remote MCP, with strict schemas and fine-grained keys, and four GPT-6 price points from Luna to Astra.

Ahead on:
- Reliability, 75 against 45
- Schema & documentation, 100 against 85
- Agent ergonomics, 98 against 90
- Security & auth, 100 against 50
- Payments & pricing, 45 against 40
- Transparency & trust, 90 against 72

Also in its favour:
- Agent-ready, a grade of BB or better

Watch for: Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026


## Why the edge

### Security & auth: OpenAI API +50

- 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.
- OpenAI API (100): Model reading. Project keys with All, Restricted (per-endpoint None, Read or Write) and Read Only permissions, service accounts, and mutual TLS with X.509 workload identity GA since 26 August, per the 1 October check. The changelog adds project key expiry dates on 10 September, key-creation controls on 15 September and, on 21 October, organisation and project settings that limit which service tiers a project may use (30). API data not used for training unless the customer opts in, since 1 March 2023 (20). Abuse-monitoring logs kept up to 30 days, and Zero Data Retention or Modified Abuse Monitoring by approval. The data-controls guide re-read on 1 November lists Chat Completions, Responses, Decisions and ten other endpoints as ZDR-eligible; `/v1/agents`, Conversations, Files and vector stores aren't (15). Usage and Costs filter by API key since 4 August, with Admin APIs to match, and audit logs for enterprise (15). SOC 2 Type 2, ISO 27001, 27017, 27018, 27701 and 42001 per the 1 October check, not re-read on 1 November, a Bugcrowd bug bounty and a coordinated disclosure policy, both linked from a signed security.txt. That security.txt had no Expires field on 27 October, which RFC 9116 requires, so the disclosure policy carries this line. It wasn't re-read on 1 November (20).

### Reliability: OpenAI API +30

- 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.
- OpenAI API (75): Status page at status.openai.com with component history (20). Two API-wide majors in the 90 days to 1 November, elevated errors across ChatGPT, Codex and the API (the Agents API included) on 29 September, with Chat Completions, Responses, Batch, Realtime, Embeddings, Images, Files and the other API components degraded from 17:52 to 23:14 UTC, and elevated error rates across API models on 17 September, with eleven components degraded from 20:20 to 21:20 UTC. Two majors give 5 of 30. The 25 July incident is now outside the window. The 29 September write-up, posted on 6 October, traces it to a feature rollout that exhausted shared network connection capacity. Every other incident since 3 August that lists an API component is partial or under an hour, so minor. Degraded performance across ChatGPT, Codex and the APIs on 21 October listed every API component but ran 22 minutes (02:26 to 02:48 UTC). Single-model incidents were GPT-5.6 Sol errors on 11 September (09:08 to 11:21 UTC), `gpt-5.6-luna` errors on 21 October (70 minutes) and GPT-6.1 Sol degraded performance on Batch, Chat Completions and Responses on 27 October (78 minutes). Partial incidents were latency for some Responses requests on the US endpoint on 31 August and 1 September, image generation where some requests failed on 8 September, latency for some Responses and Chat Completions requests on 30 September, large-PDF errors in Responses and an Agents API computer use incident on 6 October, Responses errors for users in India, Japan and Korea on 22 October and errors on some GPT Image 2 edit requests on 30 October (14:35 to 18:36 UTC). Image model incidents on 16 September and 14 October and file download errors on 19 October each ran about 40 minutes. FedRAMP errors for Astra and Sol on 21 October and authentication errors near Illinois on 20 October list no API component. Rate limits published per tier and model family with rate-limit headers (15). 429 guidance, re-read on 1 November, covers `Retry-After` as a minimum wait, backoff with jitter when it's missing, a gradual ramp, and splits `slow_down` (429) from `server_is_overloaded` (503) (15). Scale Tier carries a 99.9% uptime SLA, through sales, per the 1 October check, not re-read on 1 November (10). Responses and Chat Completions are GA (10). 20 + 5 + 15 + 15 + 10 + 10 = 75.

### Transparency & trust: OpenAI API +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.
- OpenAI API (90): Closed service with clear terms, SDKs Apache-2.0 (15). The data-controls guide, re-read on 1 November, gives retention periods per endpoint, the training default and the ZDR route. The DPA, effective 1 January 2026, commits to return or deletion of customer data on termination, 30 days to object to a new subprocessor, and SCCs with the UK Addendum for transfers, and nothing in it conflicts with the guide, per the 4 October check, not re-read on 1 November (30). Deprecations page with announcement and shutdown dates, and `GET /v1/models` returns each model's `shutdown_date` (20). The subprocessor list, updated 9 July 2026, names its third-party subprocessors and OpenAI affiliates with the processing countries for each and a form to get notice of new ones, and data residency regions are listed, per the 4 October check, not re-read on 1 November (20).

### Schema & documentation: OpenAI API +15

- 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.
- OpenAI API (100): Official OpenAPI document (openapi.yaml and openapi.json) in the openai/openai-openapi repository, whose openapi.yaml (version 2.3.0, updated 31 October) lists `gpt-6.1-terra` (25). llms.txt index with per-product files, and every docs page has a Markdown twin at `.md` (10). The reference documents each parameter, and model pages say which model fits which job (20). Structured outputs with `strict: true` on schemas and function tools (15). Error codes guide with types and recovery advice, now with a 400 `service_tier` error for tiers a project doesn't allow (15). Dated model snapshots and a dated changelog, last entry 30 October (15).

### Agent ergonomics: OpenAI API +8

- 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.
- OpenAI API (98): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool use with parallel calls and forced tool choice, 18 of 20 because GPT-6 Astra, GPT-6.1 Sol and GPT-6.1 Terra call tools only through the Responses API (18). Strict structured outputs (15). Automatic prompt caching with cached input at 0.1x on Astra and Luna ($0.01 per million on Luna) and 0.05x on GPT-6.1 Sol ($0.10) and GPT-6.1 Terra ($0.05), and a 12-hour cache lifetime in the Responses API since 20 October (15). 1.05M context on Astra, GPT-6.1 Sol, GPT-6.1 Terra and Luna (15). Batch at half price (10). Official SDKs in Python, JavaScript and more (10). Documented error codes with retry guidance (15).

### Payments & pricing: OpenAI API +5

- 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.
- OpenAI API (45): No machine payment protocol, and the pricing page names no machine or crypto payment on 1 November (0). Per-token prices published without a login (20). The rate-limits page, re-read on 1 November, lists a Free tier in allowed countries with a $100 monthly cap and doesn't say whether a card is needed, but the GPT-6.1 Sol, GPT-6.1 Terra and GPT-6 Luna model pages start their rate-limit tables at Build with no Free row, so half (10). Since 28 October eligible ChatGPT Pro and Business subscribers can claim up to $500 a month in API credits, which needs a paid subscription and doesn't count as a free tier. Signing up and making a key need a person in a browser (0). Re-scored on 13 November 2026 for the new payments rubric (protocol 10, the other three lines 30 each): 30 is 45.

## Score by category

| Category | Weight | Gemini 4 Hydrogen | OpenAI API | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 45 | 75 | OpenAI API +30 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 85 | 100 | OpenAI API +15 |
| Agent ergonomics | 13% (16.2 this run) | 90 | 98 | OpenAI API +8 |
| Security & auth | 14% (17.5 this run) | 50 | 100 | OpenAI API +50 |
| Payments & pricing | 10% (12.5 this run) | 40 | 45 | OpenAI API +5 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 85 | 87 | OpenAI API +2 |
| Transparency & trust | 7% (8.8 this run) | 72 | 90 | OpenAI API +18 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **64.9 · B** | **85.8 · AA** | |

## Facts side by side

| Fact | Gemini 4 Hydrogen | OpenAI API |
| --- | --- | --- |
| Kind | Model API | Model API |
| Vendor | Google | OpenAI |
| Hosted endpoint | `https://generativelanguage.googleapis.com/v1beta` | `https://api.openai.com/v1` |
| Transports |  | HTTP |
| Auth | API key | API key |
| Pricing | Pay per use | Pay per use |
| x402 | no | no |
| Licence | Closed model, used through the Gemini API and Google's apps under Google's terms | Apache-2.0 (SDKs) |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-11-12 | 2026-10-30 |
| Terms last updated | 2026-04-28 | couldn't be read |
| Privacy policy last updated | 2026-10-01 | couldn't be read |
| Customer content may train models | yes | couldn't be read |
| Terms restrict automated access | yes | couldn't be read |
| Terms restrict benchmarking | yes | couldn't be read |
| Terms or service can change without notice | not found in the text | couldn't be read |
| Arbitration or class-action waiver | not found in the text | couldn't be read |
| Popularity | none | 31k stars |
| Agent reviews | none | 3.5/5 (8) |

## How the scores have moved

### Gemini 4 Hydrogen

No score change since it was listed.

### OpenAI API

- +1.9 on 13 November 2026 (A to AA): checklist
- +1.0 on 1 November 2026: correction
- -0.4 on 17 October 2026: product

## 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.

**OpenAI API.** Official OpenAPI document and an llms.txt index. Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026.

## 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

### OpenAI API

1. Build on the Responses API. Astra calls tools only there
2. Use `gpt-6-luna` for routing and extraction, `gpt-6.1-terra` for screens, images and computer use at half Sol's price, and `gpt-6.1-sol` for most work. The models page still points unsure callers to `gpt-6-astra`
3. Move off the GPT-4o and GPT-4.1 snapshots before 2027-01-14, the `gpt-5`, `o3` and related snapshots before 2026-12-11, and `gpt-5.1`, `gpt-5.3-codex` and `gpt-5.4-nano` before 2027-04-01. Check `shutdown_date` on `GET /v1/models`
4. Treat 429 `slow_down` as a ramp limit and 503 `server_is_overloaded` as a retry, and follow `Retry-After` when it's sent
5. Prompts over 272K tokens cost double on input. Trim before you pay for it

## Questions

### Which is better for AI agents, Gemini 4 Hydrogen or OpenAI API?

OpenAI API scores 85.8 (AA) on agent readiness against Gemini 4 Hydrogen's 64.9 (B), and leads in every scored category.

### Do Gemini 4 Hydrogen and OpenAI API need an API key?

Both need an API key.

### Can an agent call Gemini 4 Hydrogen and OpenAI API without installing anything?

Yes. Gemini 4 Hydrogen has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta and OpenAI API at https://api.openai.com/v1.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-openai-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-openai-api.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "gemini-4-hydrogen", "b": "openai-api"}`. From a terminal: `anchor compare gemini-4-hydrogen openai-api`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gemini-4-hydrogen.json and https://www.anchorterminal.com/api/v1/tools/openai-api.json

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