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Gemini 3.5 Flash-Lite

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Gemini 3.5 Flash-Lite is a closed-weights language model from Google, released July 2026.

68.7±0.9#97 of 719 LLMsfrom 11 benchmark results across 4 sources

$ how it compares

The LLMs ranked either side of Gemini 3.5 Flash-Lite, out of 828 with a score, then more from Google.

#	model	score	where	RAM	released
104	Qwen3.5 Plus Alibaba	69±2	api $0.90/M		2026-02
105	Qwen3.5 122B-A10B Alibaba	69±1	api $1.10/M +local	~75GB	2026-02
106	Gemini 3.5 Flash-Lite Google	69±1	api $0.85/M		2026-07
107	GLM-4.7 Z.ai	69±1	api $1.00/M +local	~58GB	2025-12
108	GPT-5.5 Instant OpenAI	69±1	comparison only		2026-05
	more from Google
9	Gemini 4 Argon (limited preview) Google	82±1	limited preview		2026-09
23	Gemini 3.8 Flash Google	77±1	api $1.50/M		2026-09
32	Gemini 3.7 Flash Google	76±1	api $1.50/M		2026-08

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$ what it's good at

coding▁▁▁▃▆██▇▆▄▃▁ #66 of 458 * · 13% of its score · 1 test

Beats DeepSeek V4 Flash Vision (Exp), GPT-5.2, GPT-5 here, though they rank higher overall.

test	result	vs the others in its run	difficulty	counts	why
Arena WebDev (Code Arena)	1439.7 ✎	▁▂▄▃▅█▄▇▆▄▁▁ beats 59/119	avg 981	▇▇▇▇▇ 13%	sharp

chat & writing▁▁▁▃▅▄▅█▆▆▇▃ #49 of 393 * · 7.2% of its score · 1 test

Beats MiMo-V2.6-Flash (309B-A15B), GPT-6 Luna, GPT-5.6 Luna here, though they rank higher overall. Trails Claude Sonnet 4.5 here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
LMArena (text)	1455.0 ✎	▁▁▁▂▃▃▃▆▆▇█▃ beats 322/379	avg 1268	▇▇▇ 7.2%	blunt

math▁▂▃▅▆▅▄█▄▁▁▁ #136 of 398 · 46% of its score · 3 tests

Beats Claude Sonnet 4.6, MiniMax-M3, MiMo-V2.5 (310B-A15B) here, though they rank higher overall. Trails Olmo 3 32B Think, Olmo 3.1 32B Think, Nemotron-Cascade-8B 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 17/82	very hard · avg 1.2%	▇▇▇▇▇▇▇▇▇▇▇▇▇ 31%	sharp · at its level
FrontierMath tier 4 v2	0.0% ✎	▃▂▁▂█▅▂▂▁▁▁▁ beats 2/63	very hard · avg 0.1%	▇▇▇▇ 10%	sharp · too hard for it
OTIS mock AIME 2024–2025	71.1% ✎	▃▃▄▃▃▃▇▇█▃▂▅ beats 104/193	very hard · avg 8.5%	▇▇ 4.2%	sharp · noisy

vision & documents▁▁▃▂▁▃▄▂▆▇█▄ #40 of 147 * · 15% of its score · 2 tests

Beats MiMo-V2.6-Pro, MiMo-V2.6-Flash (309B-A15B), DeepSeek V4 Flash Vision (Exp) here, though they rank higher overall. Trails Qwen3.6 Flash here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
CharXiv (reasoning questions) lab	74.5% ✎	▃·▃·▃▃▃·▃▃█▅ beats 4/11	medium · avg 40%	▇▇▇▇ 10%	typical
Arena vision (style controlled)	1264.4 ✎	▁▁▂▂▂▂▄▅▅▆██ beats 112/145	avg 1068	▇▇ 5.0%	blunt

other tests4 not in a task · 19% of its score

test	result	vs the others in its run	difficulty	counts	why
GPQA Diamond	83.3% ✎	▁▁▁▁▂▄▆▄▅▇█▅ beats 138/208	hard · avg 40%	▇▇▇▇ 10%	sharp
Mystery Game Puzzles (Epoch)	19.0% ✎	█··▂▃▇▄█▂▃▁▁ beats 32/74	very hard · avg 9.4%	▇ 3.7%	sharp · too hard for it · noisy
Chess Puzzles (Epoch)	22.0% ✎	█▁▁▁▁▂▁▄▂▂▁▁ beats 89/135	very hard · avg 5.9%	▇ 3.4%	sharp · noisy
Icelandic LLM Leaderboard average (Miðeind, Sept 2026 suite)	49.6% ✎	▁▁▃▂▂▄▁▃▄▄▄█ beats 19/38	very hard · avg 14%	▇ 2.4%	at its level

$ where to run it

Through an API

api · $0.85/M · $0.3 in / $2.5 out per 1M tokens · 1M context · ai.google.dev ↗ · price sourceStandard base token rate from models.dev. Provider-specific tiers, long-context surcharges, caching and promotions may differ.

$ how the score was worked out · Epoch AI — internal evaluatio… 62%, LMArena leaderboard dataset 25%, Google DeepMind Gemini model… 10% and 1 more

Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The 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's added up by who ran the tests. How it works

source	results	share of the score	licence
Epoch AI — internal evaluations	6	▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 62%	CC BY 4.0
LMArena leaderboard dataset	3	▇▇▇▇▇▇▇ 25%	CC BY 4.0
Google DeepMind Gemini model page and model cards (lab-reported scores) · lab-reported	1	▇▇▇ 10%	Factual vendor-reported score (not licensed content)
Miðeind Icelandic LLM Leaderboard	1	▇ 2%	CC BY 4.0
prior · pull toward the middle		▇ 0%
weighted average		= 68.7