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Google: Gemini 2.5 Flash Lite (batch)

Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance...

Anyone in the Project can @-mention Google: Gemini 2.5 Flash Lite (batch) with the team's shared context - pooled credits, one chat, one memory.

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Starter is free forever - 1 Project, 100 credits/month, 1 MCP. No card.

Verdict

Gemini 2.5 Flash Lite (batch) trades real-time responsiveness for extreme cost efficiency—$0.05/Mtok input makes it the cheapest multimodal model in Google's lineup. The batch-only constraint means jobs queue for up to 24 hours, ruling out interactive use but unlocking massive-scale processing of documents, images, audio, and video. Reach for this when you're processing thousands of files overnight and cost per token matters more than latency.

Best for

Overnight batch processing of large datasets
Cost-sensitive document classification at scale
Bulk image and video content moderation
High-volume audio transcription jobs
Budget-constrained multimodal prototyping

Strengths

At $0.05/Mtok input, this is Google's most affordable multimodal option—4x cheaper than standard Flash models. The 1M token context window handles book-length documents, hours of audio, or extended video in a single pass. Native support for text, image, file, audio, and video means you can throw mixed-media datasets at it without preprocessing. Batch mode unlocks discounts that make million-token jobs economically viable for small teams.

Trade-offs

Batch-only processing introduces 24-hour maximum latency, making this unusable for real-time applications or user-facing features. Google hasn't published benchmarks yet, so quality relative to standard Flash or Pro models remains unverified—expect some capability gap given the price difference. The Lite designation suggests reduced reasoning depth compared to full Flash, though specifics aren't documented. Teams needing sub-minute responses should look elsewhere.

Specifications

Provider: google
Category: llm
Context length: 1,048,576 tokens
Max output: 65,535 tokens
Modalities: text, image, file, audio, video
License: proprietary
Released: 2025-07-22

Pricing

Input: $0.05/Mtok
Output: $0.20/Mtok
Model ID: google/gemini-2.5-flash-lite:batch

Per-token prices show what the model costs upstream. On Switchy your team draws from one shared org credit pool - one plan, one balance for everyone.

Team cost calculator

Seats5 peopleMessages / seat / day80Avg turn size2 ktokOutput share30 %

Estimated monthly spend

$1.67

17.6M tokens / month
5 seats · 80 msgs/day

Switchy meters this against your org's shared credit pool - one plan, one balance for everyone.

Providers

Provider-level routing data is not available yet for this model.

Performance

Performance snapshots are collected daily. Check back after the next ingestion run.

Benchmarks

Public benchmark scores are not available yet for this model. Check back after the next ingestion run.

Works well with

Top MCPs

Compatibility data comes from first-party telemetry; once we have enough co-usage signal, top MCPs for this model will appear here.

How Switchy teams use it

Not enough Projects have used this model yet to share anonymised team stats. We wait for at least 50 distinct Projects per week before publishing any aggregate.

Starter prompts

Classify Support Tickets

Read this CSV of support tickets. For each row, classify the issue into one of these categories: billing, technical, feature_request, account_access, other. Return a new CSV with an added 'category' column.

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Extract Invoice Data

Extract the following fields from this invoice: vendor_name, invoice_number, date, total_amount, line_items (as array). Return JSON. If a field is missing, use null.

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Summarize Video Content

Watch this video and create a bulleted summary with timestamps. For each major topic or scene change, note the timestamp and write a 1-2 sentence description of what happens.

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Moderate Image Uploads

Review this image for policy violations: nudity, violence, hate symbols, spam/scam indicators. Return JSON with a 'violations' array (empty if clean) and a 'confidence' score 0-1 for each flag.

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Transcribe Audio Logs

Transcribe this audio file. Include speaker labels if multiple voices are present. Format as plain text with timestamps every 30 seconds. Note any unclear sections with [inaudible].

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