Google: Gemini 4 Hydrogen (batch)
google/gemini-4-hydrogen:batch
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
According to its OpenRouter catalog entry, google/gemini-4-hydrogen:batch is the batch variant of Google's Gemini 4 Hydrogen, described there as a high-efficiency model aimed at high-throughput agentic workflows, coding, and multi-model routing. The listing reports multimodal inputs (text, image, file, audio, and video) with text-only output, a roughly one-million-token context window, mandatory reasoning with adjustable effort levels, and support for tools and structured outputs. No independent model card or benchmark results were included in this source pack, so reported capabilities should be validated on real workloads.[1]
Strengths
- OpenRouter lists multimodal input support (text, image, file, audio, and video) with an approximately one-million-token context window.[1]
- The catalog reports configurable reasoning effort (from low to xhigh) plus support for tools, structured outputs, seeds, and response formatting.[1]
- Per the catalog description, it is positioned as a lower-cost, lower-latency efficiency model for high-throughput workloads; this is catalog positioning, not measured performance.[1]
Limitations
- Evidence is catalog-only: no independent model card was available in this pack and the listed benchmark fields are empty, so capability and efficiency claims require workload-level validation.[1]
- Reasoning is reported as mandatory and cannot be disabled, which may not suit tasks where minimal processing is preferred.[1]
- Output is limited to text; the catalog does not list a knowledge cutoff or batch-variant specifics such as delivery latency or throughput guarantees.[1]
Where to use it
- Potentially a fit for high-throughput agentic and coding pipelines, per the catalog's stated positioning; validate quality and latency before production use.[1]
- Batch-style jobs over large or multimodal inputs, such as document or media understanding, given the reported input modalities and long context.[1]
- Routing tiers in multi-model systems where an efficiency-oriented model is wanted, as described in the catalog.[1]
Sources
- [1] OpenRouter catalog · Google: Gemini 4 Hydrogen (batch)Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Gemini 4 Hydrogen is the high-efficiency workhorse model of the Gemini 4 family from Google, built for high-throughput agentic workflows, coding and multi-model routing at lower cost and latency than...
Specifications
- Model ID
- google/gemini-4-hydrogen:batch
- Canonical ID
- google/gemini-4-hydrogen-20261112
- Creator
- Added to OpenRouter
- 12.11.2026
- Context length
- 1,048,576
- Modality
- text+image+file+audio+video->text
- Input modalities
- audio, file, image, text, video
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $0.750 / out $3.75
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | reasoning: mandatory · default medium · efforts: xhigh, high, medium, low · parameters: include_reasoning, reasoning, reasoning_effort |
| Coding | No measurement | — |
| Agents | No measurement | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: mandatory · default medium · efforts: xhigh, high, medium, low · parameters: include_reasoning, reasoning, reasoning_effort |
| Document analysis | No measurement | input: file |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | input: audio |
| Video | No measurement | input: video |
| Embeddings | No measurement | — |
Evaluations
No evaluations are supplied for this model.
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| 1,048,576 | $0.750 | $3.75 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.