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Gemini 2.5 Flash-Lite vs Llama-3.3 Nemotron Super 49B v1
Comprehensive side-by-side LLM comparison
Llama-3.3 Nemotron Super 49B v1 leads with 2.0% higher average benchmark score. Gemini 2.5 Flash-Lite supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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Gemini 2.5 Flash-Lite is a multimodal language model developed by Google. The model shows competitive results across 13 benchmarks. It excels particularly in FACTS Grounding (84.1%), Global-MMLU-Lite (81.1%), MMMU (72.9%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.
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NVIDIA
Llama-3.3 Nemotron Super 49B v1 is a language model developed by NVIDIA. This model demonstrates exceptional performance with an average score of 81.0% across 7 benchmarks. It excels particularly in MATH-500 (96.6%), MT-Bench (91.7%), MBPP (91.3%). Released in 2025, it represents NVIDIA's latest advancement in AI technology.
3 months newer
Llama-3.3 Nemotron Super 49B v1
NVIDIA
2025-03-18
Gemini 2.5 Flash-Lite
2025-06-17
Performance Metrics
Context window and performance specifications
Average performance across 18 common benchmarks
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Gemini 2.5 Flash-Lite
Average Score:29.5%
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Llama-3.3 Nemotron Super 49B v1
Average Score:31.5%(+2.0%)
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Knowledge Cutoff
Training data recency comparison
Llama-3.3 Nemotron Super 49B v1
2023-12-31
Gemini 2.5 Flash-Lite
2025-01-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Gemini 2.5 Flash-Lite
1 providers
Throughput: 5.69 tok/s
Latency: 0.44ms
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Llama-3.3 Nemotron Super 49B v1
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Gemini 2.5 Flash-Lite
Avg Score:29.5%
Providers:1
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Llama-3.3 Nemotron Super 49B v1
Avg Score:31.5%(+2.0%)
Providers:0