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Gemini 2.5 Flash-Lite Preview (09-2025)
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Gemini 2.5 Flash-Lite Preview (09-2025) is a closed-weights language model from Google, released September 2025.
Catalogue identity notes
Comparison-only. Arena entry 'gemini-2.5-flash-lite-preview-09-2025-no-thinking' (text, vision). Released 2025-09: Gemini API changelog: 'Launched following preview models: ... gemini-2.5-flash-lite-preview-09-2025'. The only Arena entry is the '-no-thinking' setting (thinking off). Gemini API changelog: 'The gemini-2.5-flash-lite-preview-09-2025 model has been shut down'.
$ how it compares
The LLMs ranked either side of Gemini 2.5 Flash-Lite Preview (09-2025), out of 1132 with a score, then more from Google.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 230 |  o1-preview | 63±1 | comparison only | ||
| 231 | Gemini 2.5 Flash Preview (04-17) | 63±1 | comparison only | ||
| 232 | Gemini 2.5 Flash-Lite Preview (09-2025) | 63±3 | comparison only | ||
| 233 |  GLM-4.5-Air | 63±1 | api $0.42/M +local | ||
| 234 |  Qwen3.5 9B | 63±1 | api $0.11/M +local | ||
| more from Google | |||||
| 9 | Gemini 4 Argon (limited preview) | 82±1 | limited preview | ||
| 23 | Gemini 3.8 Flash | 77±1 | api $1.50/M | ||
| 32 | Gemini 3.7 Flash | 76±1 | api $1.50/M | ||
$ what it's good at
chat & writing▁▁▁▃▅▅▆█▆▆▆▂ #171 of 579 * · 57% of its score · 1 test
Beats LongCat 2.0 (1.6T-A48B), o3-mini, K-EXAONE (236B-A23B) here, though they rank higher overall. Trails LFM2.5 8B-A1B, LFM2.5 2.6B, Nemotron-Cascade-8B here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| LMArena (text) | 1379.4 ✎ | ▁▁▁▂▃▃▃▆▆▇█▃ beats 220/379 | 57% |
vision & documents▁▁▃▃▂▃▅▅▇▇█▃ #109 of 199 * · 40% of its score · 1 test
Beats DeepSeek V4 Flash Vision (Exp), Hunyuan-Vision-1.5-Thinking here, though they rank higher overall. Trails Mistral Small 4 (119B-A6.5B), Qwen3-VL 32B Instruct, GPT-4.1 mini here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Arena vision (style controlled) | 1174.5 ✎ | ▁▁▂▂▂▂▄▅▅▆██ beats 59/145 | 40% |
$ where to run it
No verified API or download recorded yet · add one
$ how the score was worked out · LMArena leaderboard dataset 97%
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 |
|---|---|---|
 LMArena leaderboard dataset | 2 | 97% |
| prior · pull toward the middle | 3% | |
| weighted average | = 62.8 |
$ improve this page
Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.
data updated · sources and licences · json