Google: Gemini 3.5 Flash Lite (batch)
google/gemini-3.5-flash-lite:batch
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
According to the OpenRouter catalog, google/gemini-3.5-flash-lite:batch is a batch-oriented variant of Google's Gemini 3.5 Flash Lite, described as a high-efficiency model with upgraded agentic capabilities for focused subagent tasks. The catalog lists multimodal inputs (text, image, audio, video and files) with text-only output, a context window of roughly one million tokens, and reasoning that is mandatory and enabled by default with configurable effort. Structured outputs and tool calling are listed as supported. These are catalog-reported capabilities, not independently measured; no standalone model card was available in this source pack, so validate behavior on your own workloads.[1]
Strengths
- Multimodal input coverage: the catalog lists text, image, audio, video and file inputs alongside a context window of roughly one million tokens.[1]
- Configurable reasoning effort (minimal through high) plus listed support for structured outputs, response formats, seed and tool calling.[1]
- The catalog description positions it as a high-efficiency model aimed at focused subagent work inside multi-agent workflows.[1]
Limitations
- Evidence is catalog-only from OpenRouter; no independent model card was in this source pack, so all capability claims are source-reported and unverified.[1]
- Per the catalog, reasoning is mandatory and enabled by default, so it cannot be switched off even at the minimal effort level.[1]
- Knowledge cutoff is not provided and real-world performance is unestablished in this evidence; validate quality and cost on your workload.[1]
Where to use it
- Batch pipelines over long or multimodal inputs, suggested by the variant's batch designation and the listed input modalities.[1]
- Focused subagent steps in multi-agent workflows, matching the catalog's own positioning; suitability is a suggestion, not a measured result.[1]
- High-volume structured extraction or classification using the listed structured-output and tool support.[1]
Sources
- [1] OpenRouter catalog · Google: Gemini 3.5 Flash Lite (batch)Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Gemini 3.5 Flash Lite is a high-efficiency model from Google with upgraded agentic capabilities. It is suited for subagents that execute focused tasks within complex, multi-agent workflows.
Specifications
- Model ID
- google/gemini-3.5-flash-lite:batch
- Canonical ID
- google/gemini-3.5-flash-lite-20260721
- Creator
- Added to OpenRouter
- 21.07.2026
- Context length
- 1,048,576
- Modality
- text+image+file+audio+video->text
- Input modalities
- text, image, video, file, audio
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $0.150 / out $1.25
- 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 | CC — below the B band | reasoning: mandatory · default minimal · efforts: high, medium, low, minimal · parameters: include_reasoning, reasoning, reasoning_effort |
| Coding | BB — next 30% of the cohort | — |
| Agents | BB — next 30% of the cohort | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: mandatory · default minimal · efforts: high, medium, low, minimal · 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
| Source | Benchmark | Value | Grade | Data retrieved |
|---|---|---|---|---|
| Artificial Analysis | Intelligence index | 11.7 | CC — below the B band | 13.11.2026 |
| Artificial Analysis | Coding index | 49.3 | BB — next 30% of the cohort | 13.11.2026 |
| Artificial Analysis | Agentic index | 14.3 | BB — next 30% of the cohort | 13.11.2026 |
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 | $0.150 | $1.25 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.