google

Google: Gemini 3 Flash Preview (batch)

google/gemini-3-flash-preview:batch

Our take

AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.

According to OpenRouter's catalog, google/gemini-3-flash-preview:batch is a Google preview model listed for batch use. It accepts text, images, files, audio, and video, and produces text. The catalog describes it as a fast, cost-conscious thinking model for agentic workflows, multi-turn chat, and coding assistance; these are positioning claims, not verified here. Optional reasoning effort levels, tool calling, structured outputs, and a very large context window are listed. Only catalog data was supplied, so confirm behavior on your workloads.[1]

Strengths

Multimodal inputs can produce text across text, image, file, audio, and video.[1]
Optional reasoning is configurable across several effort levels, with medium listed as the default.[1]
The catalog lists tool calling, structured outputs, and a very large context window.[1]

Limitations

Only OpenRouter catalog data was supplied; an independent model card was not available in this source pack.[1]
Measured evidence is limited to selected design-arena categories; no broad benchmark suite or production evaluation was provided.[1]
Batch execution semantics, output limits, and knowledge cutoff are unspecified; validate representative workloads before adoption.[1]

Where to use it

Evaluate for agentic or coding-assistant prototypes that need tools and configurable reasoning.[1]
Consider for multimodal document, media, or file analysis where only text output is required.[1]
If batch processing is required, run a small pilot to confirm queueing and latency needs.[1]

Sources

[1] OpenRouter catalog · Google: Gemini 3 Flash Preview (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 Flash Preview is a high speed, high value thinking model designed for agentic workflows, multi turn chat, and coding assistance. It delivers near Pro level reasoning and tool...

Specifications

Model ID: google/gemini-3-flash-preview:batch
Canonical ID: google/gemini-3-flash-preview-20251217
Creator: google
Added to OpenRouter: 17.12.2025
Context length: 1,048,576
Modality: text+image+file+audio+video->text
Input modalities: text, image, file, audio, video
Output modalities: text
Token pricing: USD per 1M tokens: in $0.250 / out $1.5
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: optional · default medium · efforts: high, medium, low, minimal, none · 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: optional · default medium · efforts: high, medium, low, minimal, none · 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
Design Arena	agents · agenticslideswin rate 39.3% · rank 8	1,073Elo	—Not rated	13.11.2026
Design Arena	agents · agenticslides(python-pptx)win rate 39.3% · rank 8	1,075Elo	—Not rated	13.11.2026
Design Arena	agents · androidnativewin rate 47.7% · rank 41	1,034Elo	CC — below the B band	13.11.2026
Design Arena	agents · fullstackwin rate 47.4% · rank 35	1,041Elo	CC — below the B band	13.11.2026
Design Arena	agents · godotgamedevwin rate 50.6% · rank 17	1,161Elo	BB — next 30% of the cohort	13.11.2026
Design Arena	agents · mobileappswin rate 46.6% · rank 44	1,084Elo	CC — below the B band	13.11.2026
Design Arena	agents · python-pptxslideswin rate 38.3% · rank 30	1,036Elo	CC — below the B band	13.11.2026
Design Arena	agents · webappswin rate 48.5% · rank 39	1,092Elo	CC — below the B band	13.11.2026
Design Arena	models · 3dwin rate 62.7% · rank 63	1,166Elo	BB — next 30% of the cohort	13.11.2026
Design Arena	models · codecategorieswin rate 57.6% · rank 68	1,180Elo	BB — next 30% of the cohort	13.11.2026
Design Arena	models · gamedevwin rate 58.3% · rank 74	1,157Elo	BB — next 30% of the cohort	13.11.2026
Design Arena	models · websitewin rate 57% · rank 68	1,189Elo	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)
Google	1,048,576	$0.250	$1.5	—	—	—

Provider data retrieved: 13.11.2026

No published articles identify this model yet.