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
- 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.
Pricing
Estimate your monthly cost →| Dimension | Tier | Price | Since | Verified | Source |
|---|---|---|---|---|---|
| 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)
| Dimension | Tier | Price | From | Until |
|---|---|---|---|---|
| Input tokens | base | $0.25 per 1M tokens | 2026-10-12 | current |
| Cached input tokens | base | $0.025 per 1M tokens | 2026-10-12 | current |
| Cache storage | base | $1.00 per 1M tokens per hour | 2026-10-12 | current |
| Output tokens | base | $1.50 per 1M tokens | 2026-10-12 | current |
| Batch input tokens | base | $0.125 per 1M tokens | 2026-10-12 | current |
| Batch output tokens | base | $0.75 per 1M tokens | 2026-10-12 | current |
| Audio input tokens | base | $0.50 per 1M tokens | 2026-10-12 | current |
| Tool and search requests | Grounding with Google Maps | $14.00 per 1,000 requests | 2026-10-12 | current |
| Tool and search requests | Grounding with Google Search | $14.00 per 1,000 requests | 2026-10-12 | current |
| Other | Batch audio input tokens | $0.25 per 1M units | 2026-10-12 | current |
| Other | Cached audio input tokens | $0.05 per 1M units | 2026-10-12 | current |
Benchmarks
| Benchmark | Setting | Score | Reported by | Measured | Verified | Source |
|---|---|---|---|---|---|---|
| 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 |
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 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.
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.
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
- #11 of 14 in Best AI for research as of 2026-10-26
- #22 of 26 in Best AI for students as of 2026-10-26
- #30 of 39 in Best AI for business as of 2026-10-26
Derived from our published ranking snapshots; each ranking explains its criteria and weights.
Compare Gemini 3.1 Flash-Lite
Guides
- AI token pricing explained: input, output, cached and batch rates
- Reasoning models explained: thinking modes, effort and cost
- Multimodal AI explained: image, audio, video and file inputs, and what they cost
- Context windows explained: limits, long-context pricing and recall
- How to choose an AI model: a practical decision framework
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
- Gemini 3.1 Flash-Lite | Gemini API
- Gemini deprecations
- Gemini API Additional Terms of Service | Google AI for Developers
- Gemini Developer API pricing
- Gemini 3.1 Flash-Lite model card - Google DeepMind
- FrontierMath Tiers 1-3 (v2) leaderboard (Epoch AI)
- Gemini 3.5 Flash-Lite model card - Google DeepMind
- GDPval-AA v2.1 Leaderboard (Artificial Analysis)
Last verified Page updated 2026-10-27