whatmodel.sh / Gemini 2.0 Flash-Lite Preview (02-05)
Gemini 2.0 Flash-Lite Preview (02-05)
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Gemini 2.0 Flash-Lite Preview (02-05) is a closed-weights language model from Google, released February 2025.
Catalogue identity notes
Comparison-only. Arena entry 'gemini-2.0-flash-lite-preview-02-05' (text, vision). LMArena's leaderboard table (arena-leaderboard space @6f2eeeb) labels 'gemini-2.0-flash-lite-preview-02-05' as 'Gemini-2.0-Flash-Lite' (Google, Proprietary), linking https://aistudio.google.com/prompts/new_chat?model=gemini-2.0-flash-lite. Released 2025-02: Gemini API changelog, February 5, 2025: 'Released gemini-2.0-flash-lite-preview-02-05'. Gemini API deprecations: shut down December 9, 2025.
$ how it compares
The LLMs ranked either side of Gemini 2.0 Flash-Lite Preview (02-05), out of 828 with a score, then more from Google.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 241 |  Qwen3-VL 30B-A3B Thinking | 60±1 | api $0.75/M +local | ||
| 242 |  Mistral Small 4 (119B-A6.5B) | 60±2 | api $0.26/M +local | ||
| 243 | Gemini 2.0 Flash-Lite Preview (02-05) | 60±3 | comparison only | ||
| 244 | QwQ-32B | 59±1 | local | ||
| 245 |  OpenReasoning-Nemotron-32B | 59±2 | 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▁▁▁▃▅▄▆█▇▇▇▃ #181 of 463 * · 56% of its score · 1 test
Beats MiniMax-M2, MiniCPM5 2B, Granite 4.2 30B here, though they rank higher overall. Trails LFM2.5 1.2B Thinking, LFM2.5 8B-A1B, LFM2.5 2.6B here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| LMArena (text) | 1353.5 ✎ | ▁▁▁▂▃▃▃▆▆▇█▃ beats 198/379 | 56% |
vision & documents▁▁▃▃▂▃▅▄▇▇█▃ #122 of 182 * · 39% of its score · 1 test
Beats DeepSeek V4 Flash Vision (Exp) here, though they rank higher overall. Trails Llama 4 Maverick (402B-A17B), GPT-4o (2024-05-13), GPT-4o (2024-11-20) here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Arena vision (style controlled) | 1136.0 ✎ | ▁▁▂▂▂▂▄▅▅▆██ beats 41/145 | 39% |
other tests1 not in a task · 2.3% of its score
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Vectara hallucination leaderboard, 2025 dataset (HHEM-2.3, factual consistency rate) | 98.8% ✎ | ▁▁▂▃▄▄█▆▃▂▃▁ beats 135/140 | 2.3% |
$ where to run it
No verified API or download recorded yet · add one
$ how the score was worked out · LMArena leaderboard dataset 95%, Vectara hallucination leaderb… 2%
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 | 95% |
 Vectara hallucination leaderboard (vectara/hallucination-leaderboard repository) | 1 | 2% |
| prior · pull toward the middle | 3% | |
| weighted average | = 59.5 |
$ 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