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Google · AI model

Gemini 3.1 Flash-Lite

Low-cost Gemini 3 Flash-Lite model (GA May 2026) for high-frequency, lightweight tasks such as translation, transcription, classification and extraction. Text, image, video, audio and PDF input, text output.

Last verified Available 8 sources

Key specs

Provider
Google
Family
Gemini 3
API identifier
gemini-3.1-flash-lite
Availability
Available
Release date
2026-05-07
License
Proprietary (Gemini API Additional Terms of Service)
Context window
1,048,576 tokens
Max output
65,536 tokens
API access
Yes
Consumer app
Unknown

Capabilities

Inputs

  • Text input Yes
  • Image input Yes
  • Audio input Yes
  • Video input Yes
  • File input Yes PDF input

Outputs

  • Text output Yes
  • Image output No Image generation: not supported
  • Audio output No Audio generation: not supported

Features

  • Reasoning Optional Thinking supported; thinking_level is configurable (model page example uses high). The model is not in the thinking-levels table, so its default level and whether thinking can be turned off are not documented
  • Tool calling Yes Function calling supported
  • Web search Yes Grounding with Google Search supported (billed per search request)

"Unknown" means we have not verified this capability yet; it does not mean the model lacks it.

DimensionTierPriceSinceVerifiedSource
Input tokens base $0.25 per 1M tokens 2026-10-12 2026-10-25 Gemini Developer API pricing Standard, paid tier; text / image / video
Cached input tokens base $0.025 per 1M tokens 2026-10-12 2026-10-25 Gemini Developer API pricing Context caching price for text / image / video
Cache storage base $1.00 per 1M tokens per hour 2026-10-12 2026-10-25 Gemini Developer API pricing Context caching storage price (per 1M tokens per hour), Standard
Output tokens base $1.50 per 1M tokens 2026-10-12 2026-10-25 Gemini Developer API pricing Includes thinking tokens
Batch input tokens base $0.125 per 1M tokens 2026-10-12 2026-10-25 Gemini Developer API pricing Batch API price as listed on pricing page (50% of Standard); text / image / video
Batch output tokens base $0.75 per 1M tokens 2026-10-12 2026-10-25 Gemini Developer API pricing Batch API price as listed on pricing page (50% of Standard), includes thinking tokens
Audio input tokens base $0.50 per 1M tokens 2026-10-12 2026-10-25 Gemini Developer API pricing Standard, paid tier; audio input
Tool and search requests Grounding with Google Maps $14.00 per 1,000 requests 2026-10-12 2026-10-25 Gemini Developer API pricing Paid tier: 5,000 free requests per month (shared across all Gemini 3 and newer models), then USD 14 per 1,000 search queries
Grounding with Google Search $14.00 per 1,000 requests 2026-10-12 2026-10-25 Gemini Developer API pricing Paid tier: 5,000 free search requests per month (shared across all Gemini 3 and newer models), then this price; each Google Search query triggered by a request is charged
Other Batch audio input tokens $0.25 per 1M units 2026-10-12 2026-10-25 Gemini Developer API pricing Batch API price for audio input as listed on the pricing page (50% of Standard)
Cached audio input tokens $0.05 per 1M units 2026-10-12 2026-10-25 Gemini Developer API pricing Context caching price for audio input, Standard

Prices are shown in the currency the provider publishes; we never convert currencies.

Price history (11 entries)
DimensionTierPriceFromUntil
Input tokensbase$0.25 per 1M tokens 2026-10-12current
Cached input tokensbase$0.025 per 1M tokens 2026-10-12current
Cache storagebase$1.00 per 1M tokens per hour 2026-10-12current
Output tokensbase$1.50 per 1M tokens 2026-10-12current
Batch input tokensbase$0.125 per 1M tokens 2026-10-12current
Batch output tokensbase$0.75 per 1M tokens 2026-10-12current
Audio input tokensbase$0.50 per 1M tokens 2026-10-12current
Tool and search requestsGrounding with Google Maps$14.00 per 1,000 requests 2026-10-12current
Tool and search requestsGrounding with Google Search$14.00 per 1,000 requests 2026-10-12current
OtherBatch audio input tokens$0.25 per 1M units 2026-10-12current
OtherCached audio input tokens$0.05 per 1M units 2026-10-12current

Benchmarks

BenchmarkSettingScoreReported byMeasuredVerifiedSource
CharXiv Reasoning accuracy %, higher is better reasoning questions; no tools; high effort 73.2 % Self-reported — 2026-10-25 Gemini 3.1 Flash-Lite model card - Google DeepMind
reasoning questions; with tools (search and code execution); effort not stated 75.6 % Self-reported — 2026-10-25 Gemini 3.5 Flash-Lite model card - Google DeepMind
FrontierMath Tiers 1-3 (v2) accuracy %, higher is better Tiers 1-3 v2; high effort; Epoch harness (Python tool) 27.7 % Third party 2026-08-30 2026-10-25 FrontierMath Tiers 1-3 (v2) leaderboard (Epoch AI)
Tiers 1-3 v2; low effort; Epoch harness (Python tool) 22.5 % Third party 2026-08-30 2026-10-25 FrontierMath Tiers 1-3 (v2) leaderboard (Epoch AI)
Tiers 1-3 v2; minimal effort; Epoch harness (Python tool) 21.4 % Third party 2026-08-28 2026-10-25 FrontierMath Tiers 1-3 (v2) leaderboard (Epoch AI)
GDPval-AA v2.1 Elo, higher is better v2.1; effort not shown; Artificial Analysis Stirrup agent harness 430 Elo Third party 2026-10-25 2026-10-25 GDPval-AA v2.1 Leaderboard (Artificial Analysis)
Humanity's Last Exam accuracy %, higher is better full set (text + MM), no tools; high effort 16 % Self-reported — 2026-10-25 Gemini 3.1 Flash-Lite model card - Google DeepMind
CharXiv Reasoning caveats:

There is no maintained public leaderboard (the project site says it is under construction), so almost all current numbers are self-reported by providers. Results with tools such as a code interpreter are much higher than without: Alibaba reports 83.7% without and 90.2% with tools for Qwen3.8-27B. Top models now exceed the human baseline, so differences at the top are small and may reflect label noise. Descriptive-question scores are a different metric and must not be recorded here.

FrontierMath Tiers 1-3 (v2) caveats:

FrontierMath was developed with funding from OpenAI, which has exclusive access to a subset of the problems. Scores from v1 and from Tier 4 (a separate 43-problem expansion set) are not comparable with Tiers 1-3 (v2). The best models score about 94%, so the benchmark separates mid-size models better than it separates frontier models. Epoch's numbers come from its own harness (Python tool, 1M-token limit), which can differ from providers' internal setups. Margins are about ±1.4 to ±2.6 points.

GDPval-AA v2.1 caveats:

Elo is a relative rating: values change as models are added and the scale is re-anchored, so always store the date a rating was read. For example, Anthropic's launch page gives 1846 for Claude Opus 5.5, while the leaderboard on 2026-10-12 shows 1866 (Max, Default Fallback). Earlier versions (Google cites "GDPVal-AA v2") are not comparable. Judging is done by an LLM, not by human experts. Anthropic models are listed with "Default Fallback", meaning refused steps are routed to a fallback model. AA-Briefcase and GDP.pdf are separate evaluations.

Humanity's Last Exam caveats:

Results differ a lot by setting: with tools versus without tools (Anthropic reports 45.9% without tools and 57.4% with tools for Claude Haiku 5.5), and the full set versus the text-only subset. Providers use different judge models and harnesses (Scale uses o3-mini; Alibaba states GPT-4o). Derived sets such as HLE-Verified (a third-party revision with 1,811 scored items), HLE-Rolling and HLE-Diamond are different item sets and are not comparable. The questions are public, so contamination is possible, and community reviews have reported flawed items.

One row per result, without rank numbers: each result was measured under its own setting (effort level, harness, tools, test version), as stated by the source, and scores compare only within the same setting. Self-reported results come from the provider and have not been reproduced independently.

Rankings

Derived from our published ranking snapshots; each ranking explains its criteria and weights.

Compare Gemini 3.1 Flash-Lite

Guides

About Gemini 3.1 Flash-Lite

Gemini 3.1 Flash-Lite (gemini-3.1-flash-lite) became generally available on 7 May 2026. Google positions it for translation, transcription, lightweight agentic tasks and data extraction, document processing and summarization, and model routing. It accepts text, image, video, audio and PDF input and returns text, and supports configurable thinking. The deprecations page lists 7 May 2027 as its earliest possible shutdown date, with gemini-3.5-flash-lite as the recommended replacement.

Strengths and weaknesses

Strengths

  • Lowest text/image/video input and output token prices among the Gemini text models in this catalog ($0.25 input, $1.50 output per 1M tokens)
  • 1,048,576-token input context and 65,536-token output limit
  • Supports function calling, code execution, file search, Google Search and Google Maps grounding, URL context and structured outputs
  • Available via Batch, Flex and Priority inference

Weaknesses

  • Computer use is not supported
  • Audio input costs $0.50 per 1M tokens, twice the text/image/video input price
  • The deprecations page lists 2027-05-07 as the earliest possible shutdown date and recommends Gemini 3.5 Flash-Lite as the replacement

Sources

  1. Gemini 3.1 Flash-Lite | Gemini API
  2. Gemini deprecations
  3. Gemini API Additional Terms of Service | Google AI for Developers
  4. Gemini Developer API pricing
  5. Gemini 3.1 Flash-Lite model card - Google DeepMind
  6. FrontierMath Tiers 1-3 (v2) leaderboard (Epoch AI)
  7. Gemini 3.5 Flash-Lite model card - Google DeepMind
  8. GDPval-AA v2.1 Leaderboard (Artificial Analysis)

Last verified Page updated 2026-10-27