45.3
avg score
Rank #123
Better than 47% of all models
Context
1.0M tokens (~524 books)
Input $/1M
$0.07
Output $/1M
$0.30
Type
multimodal
License
Proprietary
Benchmarks
5 tested
Data updated today
About
Gemini 2.0 Flash Lite offers a significantly faster time to first token (TTFT) compared to [Gemini Flash 1.5](/google/gemini-flash-1.5), while maintaining quality on par with larger models like [Gemini Pro 1.5](/google/gemini-pro-1.5),...
Tested on 5 benchmarks with 64.2% average. Top scores: HELM — IFEval (82.4%), HELM — WildBench (79.0%), HELM — MMLU-Pro (72.0%).
Looking for similar performance at lower cost?
Qwen3 235B A22B Instruct 2507 scores 45.7 (101% as good) at $0.07/1M input · 5% cheaper
Qwen3 235B A22B Instruct 2507 scores 45.7 (101% as good) at $0.07/1M input · 5% cheaper
Capabilities
reasoning
79.0
#11 globally
math
37.4
#110 globally
knowledge
61.0
#43 globally
language
82.4
#43 globally
Benchmark Scores
Compare AllTested on 5 benchmarks · Ranked across 4 categories
Score Distribution (all 233 models)
0255075100
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reasoningCompare reasoning →
HELM — WildBench
79.0—Stanford HELM WildBench evaluation. Tests reasoning on challenging real-world tasks.
mathCompare math →
HELM — Omni-MATH
37.4—Stanford HELM evaluation of mathematical reasoning across diverse problem types.
knowledgeCompare knowledge →
HELM — MMLU-Pro
72.0—Stanford HELM evaluation of MMLU-Pro. Tests broad knowledge with increased difficulty.
Excellent (85+) Good (70-85) Average (50-70) Below (<50)
Links
Research
Documentation
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BenchGecko API
gemini-2-0-flash-lite-001
Specifications
- Typemultimodal
- Context1.0M tokens (~524 books)
- ReleasedFeb 2025
- LicenseProprietary
- StatusActive
- Cost / Message~$0.000
Available On
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Frequently Asked Questions
Gemini 2.0 Flash Lite is a proprietary multimodal AI model by Google DeepMind, released in February 2025. It has an average benchmark score of 45.3. Context window: 1M tokens.