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Google: Gemini 3.6 Flash (batch)

google/gemini-3.6-flash:batch

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Gemini 3.6 Flash is a high-efficiency model from Google for coding, agentic workflows, and web and app development. It is designed to produce polished outputs with fewer unnecessary edits and less hedging, while reducing token use and the number of model calls needed to complete a task.

Modalities
In / Out Price
$0.375 / $1.875per 1M
Context
1.0M
Released
Jul 21, 2026
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ProvidersPricingPerformanceUptimeBenchmarksAppsActivityFAQExplore

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick — Balanced (price + speed), Nitro (fastest), or Floor (cheapest).

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Benchmarks

Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.

Benchmark score summary for Google: Gemini 3.6 Flash (batch) (Artificial Analysis, Design Arena and Vals AI)
SourceBenchmarkScore
Artificial AnalysisGemini 3.6 Flash (High) Intelligence Index34.0
Artificial AnalysisGemini 3.6 Flash (High) Coding Index69.2
Artificial AnalysisGemini 3.6 Flash (High) Agentic Index29.0
Artificial AnalysisGemini 3.6 Flash (High) GPQA Diamond92.8%
Artificial AnalysisGemini 3.6 Flash (High) HLE40.8%
Artificial AnalysisGemini 3.6 Flash (High) AA-LCR80.0%
Artificial AnalysisGemini 3.6 Flash (High) τ-Bench Banking29.9%
Artificial AnalysisGemini 3.6 Flash (High) GDPval-AA39.3%
Artificial AnalysisGemini 3.6 Flash (High) CritPt10.6%
Artificial AnalysisGemini 3.6 Flash (High) SciCode53.4%
Artificial AnalysisGemini 3.6 Flash (High) Terminal-Bench 4.07.1%
Artificial AnalysisGemini 3.6 Flash (High) Terminal-Bench 2.177.5%
Artificial AnalysisGemini 3.6 Flash (High) AA-Omniscience Accuracy50.0%
Artificial AnalysisGemini 3.6 Flash (High) AA-Omniscience Non-Hallucination Rate44.4%
Design ArenaGemini 3.6 Flash Agents Arena Agenticgamedev Elo1142
Design ArenaGemini 3.6 Flash Agents Arena Androidnative Elo1201
Design ArenaGemini 3.6 Flash Agents Arena Blender3d Elo1176
Design ArenaGemini 3.6 Flash Agents Arena Full Stack Elo1181
Design ArenaGemini 3.6 Flash Agents Arena Htmlslides Elo1045
Design ArenaGemini 3.6 Flash Agents Arena Mobile Apps Elo1196
Design ArenaGemini 3.6 Flash Agents Arena Python-Pptxslides Elo1097
Design ArenaGemini 3.6 Flash Agents Arena Spreadsheet Elo1082
Design ArenaGemini 3.6 Flash Agents Arena Webapps Elo1197
Design ArenaGemini 3.6 Flash Models Arena 3D Elo1269
Design ArenaGemini 3.6 Flash Models Arena Asciiart Elo1277
Design ArenaGemini 3.6 Flash Models Arena Code Categories Elo1288
Design ArenaGemini 3.6 Flash Models Arena Data Visualization Elo1290
Design ArenaGemini 3.6 Flash Models Arena Game Development Elo1262
Design ArenaGemini 3.6 Flash Models Arena UI Component Elo1292
Design ArenaGemini 3.6 Flash Models Arena Website Elo1299
Vals AIGemini 3.6 Flash Code Migration30.9%
Vals AIGemini 3.6 Flash CorpFin v263.3%
Vals AIGemini 3.6 Flash CyberBench v1.145.4%
Vals AIGemini 3.6 Flash EMB65.4%
Vals AIGemini 3.6 Flash Finance Agent (v2)56.3%
Vals AIGemini 3.6 Flash GPQA Diamond93.4%
Vals AIGemini 3.6 Flash Harvey's Legal Agent Benchmark v13.3%
Vals AIGemini 3.6 Flash IOI35.1%
Vals AIGemini 3.6 Flash LiveCodeBench88.1%
Vals AIGemini 3.6 Flash LegalBench86.7%
Vals AIGemini 3.6 Flash Legal Research Bench25.0%
Vals AIGemini 3.6 Flash MedCode53.2%
Vals AIGemini 3.6 Flash MedScribe79.7%
Vals AIGemini 3.6 Flash MMLU Pro89.3%
Vals AIGemini 3.6 Flash MMMU Pro88.4%
Vals AIGemini 3.6 Flash MortgageTax67.6%
Vals AIGemini 3.6 Flash ProgramBench0.0%
Vals AIGemini 3.6 Flash ProofBench v136.0%
Vals AIGemini 3.6 Flash SAGE48.7%
Vals AIGemini 3.6 Flash SWE-bench79.6%
Vals AIGemini 3.6 Flash Tax Agent Bench18.0%
Vals AIGemini 3.6 Flash TaxEval v274.9%
Vals AIGemini 3.6 Flash Terminal-Bench 2.173.8%
Vals AIGemini 3.6 Flash Vals Index55.4%
Vals AIGemini 3.6 Flash Vals Multimodal Index65.1%
Vals AIGemini 3.6 Flash Vibe Code Bench v1.164.0%

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

Activity

Token volume and request traffic to this model over time.

API

Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.

Google: Gemini Flash versions

Not currently available through EU in-region routing. In-region routing docs

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AutoExacto benchmarks
GPQA DiamondTAU-BenchGoogle AI Studio93.3%77.3%auto-routing92.3%78.0%Google Vertex93.4%76.0%Google Vertex93.3%76.0%

Not enough uptime data to display yet.

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.

Not enough data for apps using this model yet.

Frequently asked questions

Gemini 3.6 Flash is a high-efficiency model from Google for coding, agentic workflows, and web and app development. It is designed to produce polished outputs with fewer unnecessary edits and less hedging, while reducing token use and the number of model calls needed to complete a task.

Gemini 3.6 Flash (batch) costs $0.375/M input tokens and $1.875/M output tokens, with separate rates for Cache Read at $0.0375/M tokens, Cache Write at $0.04167/M tokens, Image Input at $0.375/M tokens, Input Audio at $0.375/M tokens, Input Audio Cache at $0.0375/M tokens, and Web Search at $14.00/1K calls.

Gemini 3.6 Flash (batch) has a 1,048,576 token context window. It supports up to 65,536 completion tokens.

Yes. Gemini 3.6 Flash (batch) accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.

Gemini 3.6 Flash (batch) accepts text, images, video, files such as PDFs, and audio as input and returns text.

Gemini 4 Argon, Nano Banana 2.1, Gemini 3.8 Flash and 26 more are other text models from Google.

Gemini 3.6 Flash (batch) was released on July 21, 2026.