Intelligence
25
score
Gemini 3.1 Flash-Lite scores 25 on the Artificial Analysis Intelligence Index, placing it above …
vs class avg: 15
Google•Open weights•March 3, 2026
Gemini 3.1 Flash-Lite
Intelligence, Performance & Price Analysis
Source:Artificial Analysis scrapeType:Open weights
Speed
339.0
output tokens/sec
Gemini 3.1 Flash-Lite generates output at 339.0 tokens per second (based on Google's API), which is …
Latency
5.32s
TTFT
Gemini 3.1 Flash-Lite has a time to first token (TTFT) of 5.32s (based on Google's API), which is …
Input Price
$0.25
/ 1M tokens
Gemini 3.1 Flash-Lite costs $0.25 per 1M input tokens (better than average, median: $0.25) and $1. …
Output Price
$1.50
/ 1M tokens
Gemini 3.1 Flash-Lite costs $0.25 per 1M input tokens (better than average, median: $0.25) and $1. …
Decision Overview
Ethen's intelligence-driven routing assessment for this model
Overall verdict
Strong general-purpose model
Suitable for most production tasks, but high-volume or repetitive work should still be compared against cheaper routes.
Best for
- Code generation
- Content analysis
- Structured extraction
- Customer-facing chat
- Low-latency chat
Weak or unsuitable
- Extremely long-context tasks
- Ultra-low-latency requirements
- Predictable high-volume throughput
Routing recommendation
1
Cheaper routes for predictable extraction, labeling, or summarization
2
Cache-backed reuse for repeated prompts
Cost pressure
Moderate pricing — $0.25 / M input, $1.50 / M output. Costs are manageable, but volume should still be reviewed.
Model-fit matrix
Use this model where capability pays for itself; route away where volume, latency, or budget dominate.
| Use case | Fit | Reason | Routing note |
|---|---|---|---|
| Complex reasoning & agentic workflows | Strong | Intelligence score 25 supports capable reasoning, but very hard tasks may benefit from higher-tier models. | Good for most complex tasks; consider a frontier model for the hardest 10%. |
| High-volume chat & customer-facing | Excellent | Output speed 339.0 tokens/sec and capable intelligence make this suitable for real-time chat at scale. | Ideal for interactive chat; enable caching for repeated queries. |
| Latency-sensitive applications | Moderate | TTFT 5.32s — latency may be noticeable in interactive use. | Consider routing latency-critical paths to faster models. |
| Cost-sensitive pipelines | Strong | Output pricing at $1.50 is reasonable for moderate volume. | Suitable for production; review costs as volume grows. |
Cost pressure
MediumPricing is moderate — input $0.25, output $1.50. Costs accumulate at volume but are manageable for valuable tasks.
Cheaper substitutes
- Cheaper routes for predictable extraction, labeling, or summarization
Route away when
- Predictable high-volume throughput
- Non-critical classification and extraction
Highlights
Key benchmark results at a glance.
Intelligence
Intelligence position
Artificial Analysis Intelligence Index · Higher is better · Evaluation results measured independently by Artificial Analysis
Gemini 3.1 Flash-Lite scores 25 on the Artificial Analysis Intelligence Index, placing it above average among other reasoning models in a similar price tier (median: 15).
Speed
Speed position
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Gemini 3.1 Flash-Lite generates output at 339.0 tokens per second (based on Google's API), which is well above average compared to other reasoning models in a similar price tier (median: 99.1 t/s).
Context, Cost & Pricing
Price/value position
Weighted average cost (USD) per Intelligence Index task · Lower is better · Evaluation results measured independently by Artificial Analysis
Pricing is moderate — input $0.25, output $1.50. Costs accumulate at volume but are manageable for valuable tasks.
Intelligence & Quality
Benchmark scores and quality indices measuring model capability.
AA-Omniscience Index
AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct. · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Bars intentionally show many models at once so the page feels like a benchmark report rather than a dashboard.
Artificial Analysis Intelligence Index by Open Weights / Proprietary
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Intelligence
Artificial Analysis Intelligence Index · Higher is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Speed & Throughput
Output tokens per second and generation throughput.
Output Speed
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Speed should be read together with latency and cost; fast output does not always mean better user-perceived performance.
Speed
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Speed should be read together with latency and cost; fast output does not always mean better user-perceived performance.
Latency & Response Time
Time to first token and end-to-end response latency.
End-to-End Response Time
Seconds to output 500 tokens, including reasoning model 'thinking' time · Lower is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Bars intentionally show many models at once so the page feels like a benchmark report rather than a dashboard.
Latency: Time To First Answer Token
Seconds to first answer token received · Accounts for reasoning model 'thinking' time · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Latency includes thinking / reasoning time when applicable. Lower is better for interactive use cases.
Context, Cost & Pricing
Context window size, cost per task, and token pricing.
Context Window
Context window: tokens limit · Higher is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Larger context windows enable complex multi-turn tasks but may increase latency and cost for long inputs.
Cost per Intelligence Index Task
Weighted average cost (USD) per Artificial Analysis Intelligence Index task, segmented by token type. Lower is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Ethen Gateway should route away from this model when the task is simple, repetitive, or likely to generate many output tokens.
Cost per Task
Weighted average cost (USD) per Intelligence Index task · Lower is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Ethen Gateway should route away from this model when the task is simple, repetitive, or likely to generate many output tokens.
Cost to Run Artificial Analysis Intelligence Index
Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Ethen Gateway should route away from this model when the task is simple, repetitive, or likely to generate many output tokens.
Pricing: Cache Hit, Input, and Output
Price (USD per M Tokens) · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Bars intentionally show many models at once so the page feels like a benchmark report rather than a dashboard.
Time per Intelligence Index Task
Weighted average decode time (minutes) per task; excludes TTFT and overhead time · Lower is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Additional Benchmarks
Further benchmark and comparison data.
AA-Briefcase Elo
AA-Briefcase is an agentic knowledge work benchmark developed by Artificial Analysis. AA-Briefcase Elo is a combined metric that aggregates rubric pass rate, analytical quality Elo and presentation Elo · Higher is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Bars intentionally show many models at once so the page feels like a benchmark report rather than a dashboard.
Output Tokens per Intelligence Index Task
Weighted average number of output tokens used to run one task in the Artificial Analysis Intelligence Index · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Specifications
Technical Specifications
Gemini 3.1 Flash-Lite scores 25 on the Artificial Analysis Intelligence Index, placing it above average among other reasoning models in a similar price tier (median: 15). Gemini 3.1 Flash-Lite generates output at 339.0 tokens per second (based on Google's API), which is well above average compared to other reasoning models in a similar price tier (median: 99.1 t/s). Gemini 3.1 Flash-Lite costs $0.25 per 1M input tokens (better than average, median: $0.25) and $1.50 per 1M output tokens (somewhat higher than average, median: $0.87), based on Google's API.
Gemini 3.1 Flash-Lite
- Model type
- Open weights
- Reasoning
- Yes
- Input modalities
- Gemini 3.1 Flash-Lite supports text, image, speech, and video input.
- Output modalities
- Gemini 3.1 Flash-Lite supports text output.
- Context window
- Gemini 3.1 Flash-Lite has a context window of 1.0M tokens. This determines how much text and conversation history the model can process in a single request.
- Open weights / source
- No, Gemini 3.1 Flash-Lite is proprietary. The model weights are not publicly available.
- Parameters
- Gemini 3.1 Flash-Lite is a proprietary model and Google has not disclosed the model size or parameter count.
- Knowledge cutoff
- Gemini 3.1 Flash-Lite has a knowledge cutoff of January 2025. The model's training data includes information up to this date.
- API availability
- Yes, Gemini 3.1 Flash-Lite is available via API through 1 provider.
Methodology & Provenance
This page is rendered from the normalized profile and page JSON for Gemini 3.1 Flash-Lite.
Benchmark values are preserved as normalized; only layout, disclosure ordering, and typography are adjusted for readability.
Source file: md/scrape/artificial_analysis_model_pages/artificialanalysis_ai__models__gemini-3-1-flash-lite-preview__3e2c02fb9f.html · Canonical URL: https://artificialanalysis.ai/models/gemini-3-1-flash-lite-preview
Normalized at: 2026-07-08T03:24:56+00:00 Technical specs, comparison summary, and FAQs are passed through from the normalized data without rewriting.
Ranks shown on summary cards come directly from the normalized profile. No rank or class display is synthesized in the renderer.
Visible FAQ answers and FAQ JSON-LD are emitted from the same normalized FAQ array, so structured data stays aligned with the rendered accordion.
Time per Intelligence Index Task: https://artificialanalysis.ai/models/gemini-3-1-flash-lite-preview
Frequently Asked Questions
Gemini 3.1 Flash-Lite was released on March 3, 2026.
Gemini 3.1 Flash-Lite was created by Google.
Gemini 3.1 Flash-Lite scores 25 on the Artificial Analysis Intelligence Index, placing it above average among other reasoning models in a similar price tier (median: 15).