# Gemini 4 Hydrogen vs Beam 1.0

> Gemini 4 Hydrogen scores 64.9 (B) to Beam 1.0's 54.1 (C) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-reflection-beam
- Markdown: https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-reflection-beam.md (~7,500 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

Gemini 4 Hydrogen scores 64.9 (B) on agent readiness against Beam 1.0's 54.1 (C), and leads in 6 of 7 scored categories. Beam 1.0 leads on reliability. 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
- Beam 1.0: grade C, 54.1/100, rank #1000 of 1524. Markdown https://www.anchorterminal.com/tools/reflection-beam.md · JSON https://www.anchorterminal.com/api/v1/tools/reflection-beam.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.

Ahead on:
- Agent ergonomics, 90 against 67
- Security & auth, 50 against 45
- Payments & pricing, 40 against 15
- Maintenance & community, 85 against 50
- Transparency & trust, 72 against 57

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

### Beam 1.0 (C)

Good for: An OpenAI-compatible endpoint for a large open-weight coding and agent model, for builders who want the same model hosted or self-hosted under Apache-2.0.

Ahead on:
- Reliability, 52 against 45

Watch for: No SLA, and per-organisation rate limits and the daily token allowance are not published as numbers


## Why the edge

### Maintenance & community: Gemini 4 Hydrogen +35

- 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.
- Beam 1.0 (50): Model reading. The weights were published on 16 October 2026, the date on the Hugging Face model page (the repository was created on 7 October); later commits to 30 October add evaluation results and a guide, which record no model change (30). One model, with a `shutdown_date` field and a lifecycle section in the docs but no notice period for retirements, and no history of releases or retirements yet (4 of 20). No changelog. Support through the platform and developers@reflection.ai for higher limits, and the model card names reports@reflection.ai. The Hub page shows 15 discussions (10 open, 5 closed), replies not sampled (6 of 25). No first-party SDK, the docs rely on the OpenAI SDKs (5 of 15). Reflection's serving guides for vLLM, SGLang, TokenSpeed, Transformers and Dynamo, a Beam Verifier repository, and fine-tuning recipes now published for NeMo AutoModel, Megatron Bridge, Axolotl and TRL (5 of 10, partial kept). 30 + 4 + 6 + 5 + 5 = 50.

### Payments & pricing: Gemini 4 Hydrogen +25

- 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.
- Beam 1.0 (15): Graded on the Reflection API. No x402, MPP or L402 (0). No per-token, plan or allocation price is published on any readable page; the beta pricing page on reflection.ai is struck (0, was 10). Free tier 10 of 20, partial kept. The rate-limits page describes a daily token allowance and asks those requesting higher limits whether they are "interested in paid usage", and the authentication page says some organisations must verify a credit card before keys work. A person signs up in the browser at platform.reflection.ai to get a key (0). 0 + 0 + 10 + 0 = 10. Re-scored on 13 November 2026 for the new payments rubric (protocol 10, the other three lines 30 each): 10 is 15.

### Agent ergonomics: Gemini 4 Hydrogen +23

- 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.
- Beam 1.0 (67): Model reading (tool use, structured output, caching, context, batch, SDKs and defaults, errors). `tool_choice` of auto, none, required or a named function, `parallel_tool_calls`, strict tools and up to 128 tools. The tool-calling loop needs `reasoning_content` sent back on every assistant turn, and the docs say the model sometimes returns a tool-call step without it, after which every request in the session fails (12 of 20). `json_object` and strict `json_schema` (15). Cached prompt tokens are reported in `usage`, but caching can't be steered, the `prompt_cache_*` options are ignored and no cached price exists in the beta (5 of 10). 1,048,576-token context and 131,072 output tokens (15). No batch endpoint (0 of 10). No Reflection SDK, the OpenAI Python and TypeScript SDKs are documented, and defaults cost an agent turns, with reasoning always on at `max`, `stop` and `seed` ignored and a default output budget not reduced to fit the prompt (5 of 10). Machine-readable `error.code` values with `param`, `x-should-retry`, `Retry-After` and `x-request-id` (15). 12 + 15 + 5 + 15 + 0 + 5 + 15 = 67, per the 17 October reading of the developers guides, not re-read on 4 November beyond the models and rate-limits pages.

### Transparency & trust: Gemini 4 Hydrogen +15

- 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.
- Beam 1.0 (57): Weights under Apache-2.0, an OSI licence, per the model card, which says the licence doesn't restrict distillation or training on outputs. The hosted API is a closed service whose commercial terms are on reflection.ai and can no longer be read (25 of 30, kept). Data handling 10 of 30, partial kept. What remains readable is the API reference's retention header (`zero`, `standard`, `contributor`) and the rate-limits page's request for data retention requirements; the terms, privacy policy, API safety page and zero-retention page are struck. Deprecation 4 of 20 (was 6). A `shutdown_date` field and a lifecycle section that says to move off a model before that date, with no notice period or dated notice; the fee-increase notice came from the struck terms. Subprocessors 0 of 20 (was 18). The list read on 17 October is on reflection.ai and struck, and no readable page names subprocessors or data locations. 25 + 10 + 4 + 0 = 39.

### Reliability: Beam 1.0 +7

- 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.
- Beam 1.0 (52): Hosted lines, for the Reflection API. Status page at status.reflection.ai on incident.io, with API, platform and developer docs components and Atom and RSS feeds (20). In the 90 days to 4 November 2026 its incident pages list two full outages of the API component, a serving cluster down from 22:01 to 23:20 UTC on 14 October and elevated errors from 06:10 to 07:10 UTC on 15 October, each an hour or more, so two majors. Three more are labelled partial outages (16 October 02:28 to 02:38 UTC, 22 October rate-limit errors in two windows, 3 November about 20:10 to 21:38 UTC on one inference provider), read as minor. Two majors give 5. Rate limits are described per organisation in requests and tokens per minute and per day, with concurrency caps and headers, but no figures are published (5 of 15). 429 and 503 responses carry `Retry-After`, daily limits add `x-should-retry: false`, and the errors page says which codes to retry, with exponential backoff and jitter. There are no idempotency keys, and a chat completion is the billed call, so this run's value for retry guidance without idempotency keys gives 12 (was 15). No SLA found (0). The developers docs read on 4 November carry no beta or preview label for the API; the earlier beta reading came from reflection.ai pages now struck (10). 20 + 5 + 5 + 12 + 0 + 10 = 52.

### Security & auth: Gemini 4 Hydrogen +5

- 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.
- Beam 1.0 (45): Model reading. API keys per project, revocable, shown once and disabled when their creator leaves, with no scopes, expiry or rotation API found (20 of 30). Training 10 of 20, partial kept. The API reference says each response's `reflection-data-retention` header reports `contributor` when content may be used to train Reflection's models "under contributor terms your organization accepted". The API safety page and commercial terms read on 17 October are struck (reflection.ai now disallows our crawler), so whether training is off by default can't be read. Retention 5 of 15, partial kept. The header can report `zero`, `standard` or `contributor`, and no readable page states periods or whether zero retention is offered. `x-request-id` on every response and the retention header, with usage dashboards behind the login and not read (5 of 15). Security programme 5 of 20 (was 6). The model card names reports@reflection.ai for security vulnerabilities; developers.reflection.ai has no security.txt (404 on 17 October), and the safety report and reflection.ai's security.txt can't be read. No bug bounty, SOC 2 or ISO 27001 found on a readable page. 20 + 10 + 5 + 5 + 5 = 45.

## Score by category

| Category | Weight | Gemini 4 Hydrogen | Beam 1.0 | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 45 | 52 | Beam 1.0 +7 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 85 | 84 | Gemini 4 Hydrogen +1 |
| Agent ergonomics | 13% (16.2 this run) | 90 | 67 | Gemini 4 Hydrogen +23 |
| Security & auth | 14% (17.5 this run) | 50 | 45 | Gemini 4 Hydrogen +5 |
| Payments & pricing | 10% (12.5 this run) | 40 | 15 | Gemini 4 Hydrogen +25 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 85 | 50 | Gemini 4 Hydrogen +35 |
| Transparency & trust | 7% (8.8 this run) | 72 | 57 | Gemini 4 Hydrogen +15 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **64.9 · B** | **54.1 · C** | |

## Facts side by side

| Fact | Gemini 4 Hydrogen | Beam 1.0 |
| --- | --- | --- |
| Kind | Model API | Model API |
| Vendor | Google | Reflection |
| Hosted endpoint | `https://generativelanguage.googleapis.com/v1beta` | `https://api.reflection.ai/openai/v1` |
| Transports |  | HTTP |
| Auth | API key | API key |
| Pricing | Pay per use | Freemium |
| x402 | no | no |
| Licence | Closed model, used through the Gemini API and Google's apps under Google's terms | Weights under Apache-2.0. The hosted Reflection API is a closed service under Reflection's commercial terms of service |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-11-12 | 2026-10-16 |
| Terms last updated | 2026-04-28 | 2026-10-05 |
| Privacy policy last updated | 2026-10-01 | 2026-08-28 |
| Customer content may train models | yes | yes |
| Terms restrict automated access | yes | not found in the text |
| Terms restrict benchmarking | yes | not found in the text |
| Terms or service can change without notice | not found in the text | not found in the text |
| Arbitration or class-action waiver | not found in the text | yes |
| Agent reviews | none | 2.5/5 (4) |

## How the scores have moved

### Gemini 4 Hydrogen

No score change since it was listed.

### Beam 1.0

- +0.7 on 13 November 2026 (D to C): checklist
- +0.1 on 4 November 2026: new evidence, correction
- -0.1 on 30 October 2026: checklist

## 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.

**Beam 1.0.** The Reflection API is OpenAI-compatible, with an OpenAPI document, strict structured outputs and tool calls, and error codes that say when to retry, and the weights are Apache-2.0. No price or rate-limit figure is published on a readable page, reasoning can't be turned off, and the API had two full outages on 14 and 15 October 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

### Beam 1.0

1. Send `reasoning_effort` `low` or `medium` for short tasks. The default is `max`, and `none` or `minimal` return `400 unsupported_value`
2. Return every assistant message with its `reasoning_content` unchanged. If a turn comes back without it, start a new conversation, since later requests fail with `missing_required_parameter`
3. Don't rely on `stop` or `seed`. Both are accepted and ignored, so truncate output in your own code
4. Honour `x-should-retry: false` on a 429. It means a daily limit is spent and `Retry-After` counts to 00:00 UTC
5. Set `max_completion_tokens` yourself on long prompts. The default budget isn't reduced to fit the prompt and includes reasoning tokens

## Questions

### Which is better for AI agents, Gemini 4 Hydrogen or Beam 1.0?

Gemini 4 Hydrogen scores 64.9 (B) on agent readiness against Beam 1.0's 54.1 (C), and leads in 6 of 7 scored categories. Beam 1.0 leads on reliability.

### Do Gemini 4 Hydrogen and Beam 1.0 need an API key?

Both need an API key.

### Can an agent call Gemini 4 Hydrogen and Beam 1.0 without installing anything?

Yes. Gemini 4 Hydrogen has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta and Beam 1.0 at https://api.reflection.ai/openai/v1.


## For agents

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

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- [Gemini 4 Hydrogen vs Together AI Inference](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-together-inference.md)
- [Gemini 4 Hydrogen vs Vercel AI Gateway](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-vercel-ai-gateway.md)
- [Gemini 4 Hydrogen vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-vertex-ai.md)
- [Gemini 4 Hydrogen vs xAI API (Grok)](https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-xai-api.md)
- [Gemini Developer API vs Beam 1.0](https://www.anchorterminal.com/compare/gemini-api-vs-reflection-beam.md)
- [GroqCloud vs Beam 1.0](https://www.anchorterminal.com/compare/groq-vs-reflection-beam.md)
- [Hugging Face Inference Providers vs Beam 1.0](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-reflection-beam.md)
- [Tencent Hy4 vs Beam 1.0](https://www.anchorterminal.com/compare/hy4-vs-reflection-beam.md)
- [Jais 3 vs Beam 1.0](https://www.anchorterminal.com/compare/jais-3-vs-reflection-beam.md)
- [Meta Model API vs Beam 1.0](https://www.anchorterminal.com/compare/meta-model-api-vs-reflection-beam.md)
- [MiniMax API vs Beam 1.0](https://www.anchorterminal.com/compare/minimax-api-vs-reflection-beam.md)
- [Mistral AI API vs Beam 1.0](https://www.anchorterminal.com/compare/mistral-api-vs-reflection-beam.md)
- [Muse Ember vs Beam 1.0](https://www.anchorterminal.com/compare/muse-ember-vs-reflection-beam.md)
- [Muse Spark Open vs Beam 1.0](https://www.anchorterminal.com/compare/muse-spark-open-vs-reflection-beam.md)
- [Novita AI vs Beam 1.0](https://www.anchorterminal.com/compare/novita-ai-vs-reflection-beam.md)
- [OpenAI API vs Beam 1.0](https://www.anchorterminal.com/compare/openai-api-vs-reflection-beam.md)
- [OpenRouter vs Beam 1.0](https://www.anchorterminal.com/compare/openrouter-vs-reflection-beam.md)
- [Prism Inference vs Beam 1.0](https://www.anchorterminal.com/compare/prism-inference-vs-reflection-beam.md)
- [Router.com (Ramp Router) vs Beam 1.0](https://www.anchorterminal.com/compare/ramp-router-vs-reflection-beam.md)
- [Beam 1.0 vs RouterPlus](https://www.anchorterminal.com/compare/reflection-beam-vs-routerplus.md)
- [Beam 1.0 vs SambaCloud](https://www.anchorterminal.com/compare/reflection-beam-vs-sambanova.md)
- [Beam 1.0 vs SiliconFlow](https://www.anchorterminal.com/compare/reflection-beam-vs-siliconflow.md)
- [Beam 1.0 vs Simplismart](https://www.anchorterminal.com/compare/reflection-beam-vs-simplismart.md)
- [Beam 1.0 vs StepFun API](https://www.anchorterminal.com/compare/reflection-beam-vs-stepfun-api.md)
- [Beam 1.0 vs SWE-2 Flash](https://www.anchorterminal.com/compare/reflection-beam-vs-swe-2-flash.md)
- [Beam 1.0 vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/reflection-beam-vs-tencent-tokenhub.md)
- [Beam 1.0 vs Together AI Inference](https://www.anchorterminal.com/compare/reflection-beam-vs-together-inference.md)
- [Beam 1.0 vs Vercel AI Gateway](https://www.anchorterminal.com/compare/reflection-beam-vs-vercel-ai-gateway.md)
- [Beam 1.0 vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/reflection-beam-vs-vertex-ai.md)
- [Beam 1.0 vs xAI API (Grok)](https://www.anchorterminal.com/compare/reflection-beam-vs-xai-api.md)
- [Nemotron 3.5 Super VL vs Beam 1.0](https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-reflection-beam.md)

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Query this catalogue directly over MCP: https://www.anchorterminal.com/mcp (Streamable HTTP, no key). How: https://www.anchorterminal.com/agents/#mcp