Gemini 3.1 Flash Lite (batch)
Google · released May 7, 2026
Gemini 3.1 Flash Lite is Google’s GA high-efficiency multimodal model optimized for low-latency, high-volume workloads. It supports text, image, video, audio, and PDF inputs, and is designed for lightweight agentic...
Specification
- Context window
- 1.05M
- Max output
- 66K
- Knowledge cutoff
- Not stated
- Parameters
- Undisclosed
- Licence
- Proprietary
- Serving providers
- 1
- Moderated
- No
Intelligence
25.6
68th percentile
Coding
34.7
Coding Index
Agentic
6.5
Agentic Index
Output speed
287 t/s
Median across providers
Latency
4.34s
Time to first token
Cost per task
$0.07
Estimated
Benchmarks
Where the score comes from
The Intelligence Index is a composite. These are the underlying evaluations this model was actually measured on.
Evaluation scores
Percentage correct · higher is better
- GPQA Diamond82.2%
- IFBench77.2%
- AA-LCR (long context)71.3%
- SciCode41.9%
- τ²-bench (Telecom)31.3%
- Terminal-Bench Hard24.2%
- Humanity's Last Exam17.2%
An evaluation missing from this list was not run for this model — it is not a zero.
View as table
| Evaluation | Score |
|---|---|
| GPQA Diamond | 82.2% |
| IFBench | 77.2% |
| AA-LCR (long context) | 71.3% |
| SciCode | 41.9% |
| τ²-bench (Telecom) | 31.3% |
| Terminal-Bench Hard | 24.2% |
| Humanity's Last Exam | 17.2% |
Against its peers
Intelligence Index · this model highlighted, nearest peers in grey
- Claude Opus 4Anthropic26.0
- Claude Sonnet 4Anthropic26.0
- Gemini 2.5 ProGoogle25.9
- GPT-5 MiniOpenAI25.8
- Gemini 3.1 Flash Lite (batch)Google25.6
- Gemini 3.1 Flash LiteGoogle25.6
- 25.6
- V3.2DeepSeek25.1
Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.
View as table
| Model | Intelligence |
|---|---|
| Claude Opus 4 | 26.0 |
| Claude Sonnet 4 | 26.0 |
| Gemini 2.5 Pro | 25.9 |
| GPT-5 Mini | 25.8 |
| Gemini 3.1 Flash Lite (batch) | 25.6 |
| Gemini 3.1 Flash Lite | 25.6 |
| Gemini 3.1 Flash Lite Preview | 25.6 |
| V3.2 | 25.1 |
Percentile among all indexed models
Pricing
What it costs to run
List prices per million tokens, plus what one representative task works out to.
List price
- Input / 1M tokens
- $0.125
- Output / 1M tokens
- $0.75
- Cached input / 1M
- $0.013
- Blended 3:1
- $0.281
One task, estimated
$0.07
- Input tokens
- 50,000
- Output tokens
- 80,000
- Profile
- Reasoning
Estimated from list pricing: 50K input tokens plus 80K output tokens for reasoning models (25K for non-reasoning).
Serving providers
Speed and latency figures are medians across these providers, so a widely-served model reports a blend rather than any single endpoint.