[whatmodel.sh](../../README.md) / Gemini 3.5 Flash-Lite # Gemini 3.5 Flash-Lite Google · released 2026-07 · closed weights **score 67.8** ±0.8 · #101 of 732 · from 11 benchmark results across 4 sources Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only. ## What it's good at _{● marks Gemini 3.5 Flash-Lite among every model on that task or test, worst to best.}

task                vs the others         rank  counts  tests
coding              ▁▁▁▃▅▇█▇▅●▃▁   #80 of 469*     13%      1
chat & writing      ▁▁▁▃▆▄▆█▆▇●▃   #47 of 402*    7.3%      1
math                ▁▁▃▅█▆▄●▄▂▁▁   #142 of 431     45%      3
vision & documents  ▁▁▂▂▁▃▄▂▆▇●▄   #40 of 153*     15%      2

coding · #80 of 469 · 13% of its score

Beats [GPT-5.2](gpt-5-2.md), [GPT-5](gpt-5.md), [Grok 4.20 (0309 reasoning)](grok-4-20.md) here, though they rank higher overall. Trails [Llama 3.1 Nemotron Ultra 253B v1](llama-3-1-nemotron-ultra-253b.md) here, though they rank lower overall.

test                       result  vs the others in its run   difficulty  counts  why
Arena WebDev (Code Arena)  1434.1  ▁▁▃▂▅●▃▆▅▅▁▂ beats 53/129  avg 981        13%  sharp

chat & writing · #47 of 402 · 7.3% of its score

Beats [MiMo-V2.6-Flash (309B-A15B)](mimo-v2-6-flash.md), [Claude Haiku 5.5](claude-haiku-5-5.md), [GPT-6 Luna](gpt-6-luna.md) here, though they rank higher overall.

test            result  vs the others in its run    difficulty  counts  why
LMArena (text)  1455.7  ▁▁▁▂▃▃▃▆▆▇●▃ beats 328/385  avg 1260      7.3%  blunt

math · #142 of 431 · 45% of its score

Beats [Claude Sonnet 4.6](claude-sonnet-4-6.md), [MiniMax-M3](minimax-m3.md), [MiMo-V2.5 (310B-A15B)](mimo-v2-5.md) here, though they rank higher overall. Trails [Olmo 3 32B Think](olmo-3-32b-think.md), [Nemotron-Cascade-8B](nemotron-cascade-8b.md), [Olmo 3.1 32B Think](olmo-3-1-32b-think.md) here, though they rank lower overall.

test                       result  vs the others in its run    difficulty            counts  why
FrontierMath tiers 1–3 v2   26.0%  ▂··▁▁▃●▄█▆▄▃ beats 17/86    very hard · avg 1.2%     31%  sharp · at its level
FrontierMath tier 4 v2       0.0%  ●▂▁▂█▅▂▃▂▁▁▁ beats 2/67     very hard · avg 0.1%     10%  sharp
OTIS mock AIME 2024–2025    71.1%  ▃▃▄▃▃▃▇●█▃▂▅ beats 104/197  very hard · avg 7.2%    3.4%  sharp · noisy

vision & documents · #40 of 153 · 15% of its score

Beats [MiMo-V2.6-Pro](mimo-v2-6-pro.md), [MiMo-V2.6-Flash (309B-A15B)](mimo-v2-6-flash.md), [DeepSeek V4.1 Flash](deepseek-v4-1-flash.md) here, though they rank higher overall. Trails [Qwen3.6 Flash](qwen3-6-flash.md) here, though they rank lower overall.

test                                result  vs the others in its run    difficulty        counts  why
CharXiv (reasoning questions) (ma…   74.5%  ▃·▃·▃▃●·▃▃█▅ beats 4/11     medium · avg 38%     10%  typical
Arena vision (style controlled)     1266.9  ▁▁▂▂▂▂▃▄▅▅●▇ beats 122/152  avg 1061            4.9%  blunt

other tests (4)

test                                result  vs the others in its run    difficulty            counts  why
GPQA Diamond                         83.3%  ▁▁▁▁▂▄▆▄▅●█▅ beats 138/211  hard · avg 39%          9.3%  sharp
Mystery Game Puzzles (Epoch)         19.0%  █··▂▃●▄█▂▄▂▁ beats 32/77    very hard · avg 9.4%    4.3%  sharp · too hard for it · noisy
Chess Puzzles (Epoch)                22.0%  █▁▁▁▁▂▃●▃▂▁▁ beats 89/137   very hard · avg 5.8%    3.7%  sharp · noisy
Icelandic LLM Leaderboard average…   49.6%  ▁▁▃▂▂▄▁▃●▄▄█ beats 19/38    very hard · avg 14%     2.6%  at its level

## How the score was worked out Each result implies a score on its own, after adjusting for how hard that test is and who ran it. The model's score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its *counts* column above; here it is added up by who ran the tests. [Method](../method.md)

source                                    results  share of the score
Epoch AI                                        6   62% ▇▇▇▇▇▇▇
LMArena leaderboard dataset                     3   25% ▇▇▇
Google DeepMind Gemini model page and m…        1   10% ▇
Miðeind Icelandic LLM Leaderboard               1    3% ▇
prior: pull toward the middle                        0% ▇
weighted average                                   = 67.8

_{Licences: Epoch AI ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Miðeind Icelandic LLM Leaderboard ([CC BY 4.0](../../licenses/mideind-icelandic-llm-leaderboard-CC-BY-4.0.txt))} ## How to run it ### Through an API api (Google) · $0.85/M blended · $0.3 in / $2.5 out per 1M tokens · [ai.google.dev](https://ai.google.dev/gemini-api/docs/models) _{[price source](https://github.com/anomalyco/models.dev/blob/a668908cfe7073faa0363699486fc41a3ff52412/providers/google/models/gemini-3.5-flash-lite.toml): Standard base token rate from models.dev. Provider-specific tiers, long-context surcharges, caching and promotions may differ. · [context source](https://github.com/anomalyco/models.dev/blob/a668908cfe7073faa0363699486fc41a3ff52412/models/google/gemini-3.5-flash-lite.toml)} [interactive version](https://whatmodel.sh/model/gemini-3-5-flash-lite) · [JSON](https://whatmodel.sh/api?format=json&all=1)