Gemini 2.0 Flash-Lite vs Amazon Nova Lite
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Gemini 2.0 Flash-Lite da Google e Amazon Nova Lite da Amazon são dois modelos de IA de destaque. O Gemini 2.0 Flash-Lite oferece uma janela de contexto de 1.05M tokens a $0.07/$0.30 por milhão de tokens, enquanto o Amazon Nova Lite oferece 300K tokens de contexto a $0.06/$0.24 por milhão de tokens. Veja abaixo a comparação completa de benchmarks, latência e custos.
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Gemini 2.0 Flash-Lite
Modelo Leve e EconômicoO Gemini 2.0 Flash-Lite da Google é um modelo de IA projetado para máxima economia por token e alto desempenho em escala de produção, oferecendo janela de contexto de 1.0M, velocidade de 280 tokens/s, índice de inteligência de 48/100 e tari
$0.07 / 1M
$0.30 / 1M
1.05M tokens
N/A
Amazon Nova Lite
IA Multimodal NativaO Amazon Nova Lite da Amazon é um modelo de IA projetado para compreensão multimodal nativa de texto e imagem e leitura visual de documentos, oferecendo janela de contexto de 300K, velocidade de 135 tokens/s, índice de inteligência de 38/10
$0.06 / 1M
$0.24 / 1M
300K tokens
31.2%
Principais Diferenças em Resumo
- Amazon Nova Lite is 1.3x cheaper for API usage (input + output tokens combined).
- Gemini 2.0 Flash-Lite has a larger context window (1M vs 300K tokens).
- Gemini 2.0 Flash-Lite is faster at 280 tok/s vs 135 tok/s.
| Feature | Gemini 2.0 Flash-Lite | Amazon Nova Lite |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 48 | 38 |
Provider | Amazon | |
Input Price Cost per million input tokens | $0.07 / 1M | $0.06 / 1M |
Output Price Cost per million output tokens | $0.30 / 1M | $0.24 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.06 / 1M | $0.05 / 1M |
Context Window Maximum input + output tokens | 1.05M tokens~1,573 A4 pages of text | 300K tokens~450 A4 pages of text |
Max Output Tokens Per single request | 8K | 8K |
Throughput Speed Tokens generated per second | 280 tok/s | 135 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 31.2% |
GPQA Diamond Graduate-level reasoning | N/A | 42% |
Cached Input Price Prompt caching discount per 1M tokens | $0.02 / 1M | $0.01 / 1M |
Quem vence em cada categoria?
At-a-glance decision frameworkEvaluations ongoing
Pontuações de Benchmarks Verificadas
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latência e Tempo de Resposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interativo de Custo de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Gemini 2.0 Flash-Lite · Strengths & Key Advantages
- Janela de contexto de 1.0M com limite máximo de saída de 8K tokens (MMLU-Pro 72.5% · Arena Elo 1305)
- Taxa de transferência rápida de 280 tokens/segundo com latência inicial (TTFT) de 290 ms
- Economia de API competitiva ($0.075/$0.3 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas
Considerations & Trade-offs
- Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
- Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade
Amazon Nova Lite · Strengths & Key Advantages
- Janela de contexto de 300K com limite máximo de saída de 8K tokens (SWE-bench Verified 31.2% · GPQA Diamond 42%)
- Taxa de transferência rápida de 135 tokens/segundo com latência inicial (TTFT) de 280 ms
- Economia de API competitiva ($0.06/$0.24 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas
Considerations & Trade-offs
- Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
- Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Gemini 2.0 Flash-Lite | Amazon Nova Lite |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.25 | $0.06 |
Output Tokens / Task Tokens generated per task | 6K | 19K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
Especificações Técnicas
Architecture, release timeline, capabilities, and modalities.
| Feature | Gemini 2.0 Flash-Lite | Amazon Nova Lite |
|---|---|---|
| Official API Model ID (SDK) | models/gemini-2-0-flash-lite | nova-lite |
| API Protocol | Google Gemini API (generateContent) + OpenAI-Compatible SDK | Amazon REST API (OpenAI-Compatible) |
| Release Date | 2025-02 | 2024-12 |
| Knowledge Cutoff | August 2024 | October 2024 |
| Architecture | Distilled lightweight multimodal transformer | High-Speed Multimodal Foundation Transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens | Flat rate ($0.06/1M in) across full 300K window |
| Prompt Cache Policy & TTL | Implicit + Explicit Context Caching at $0.01875/1M with configurable TTL | Cached input at $0.015/1M tokens |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Built-in Google Search Grounding + Managed Python Code Execution Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Vertex AI Supervised Adapter Tuning & Context Distillation | API Prompt Engineering & RAG Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Video (~258–300 tokens/sec) |
| Quantization & Min GPU VRAM | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | Google DeepMind Frontier Safety Framework Verified | Amazon Production Safety & Alignment Verified |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text, vision, audio, video | text, vision, video |
| Output Modalities | text | text |
Gemini 2.0 Flash-Lite vs Amazon Nova Lite: Respostas Rápidas (FAQ)
Which is more intelligent, Gemini 2.0 Flash-Lite or Amazon Nova Lite?
Gemini 2.0 Flash-Lite is more intelligent. It scores 48 compared with 38 on the composite Intelligence Index.
Which model is faster?
Gemini 2.0 Flash-Lite is faster, generating 280 tokens per second compared with 135 tokens per second.
Which model is cheaper to run?
Amazon Nova Lite is cheaper at $0.05 per 1M tokens blended, compared with $0.06 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Amazon Nova Lite has lower latency, with a time to first token of 0.28s compared with 0.29s.
Which model has a larger context window?
Gemini 2.0 Flash-Lite has a larger context window, supporting 1.05M tokens compared with 300K tokens.
Veredito
Tanto Gemini 2.0 Flash-Lite (Indicado para máxima economia por token e alto desempenho em escala de produção, arquiteturas RAG corporativas e integração escalável via API.) quanto Amazon Nova Lite (Indicado para compreensão multimodal nativa de texto e imagem e leitura visual de documentos, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: Gemini 2.0 Flash-Lite lidera em inteligência geral e programação, Gemini 2.0 Flash-Lite oferece geração mais rápida e Amazon Nova Lite apresenta o melhor custo-benefício em produção.
Perguntas Frequentes (FAQ)
Qual é melhor para programação e raciocínio, Gemini 2.0 Flash-Lite ou Amazon Nova Lite?+
Nas avaliações de inteligência e código, Gemini 2.0 Flash-Lite leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.
Qual modelo tem a API mais barata, Gemini 2.0 Flash-Lite ou Amazon Nova Lite?+
O Gemini 2.0 Flash-Lite custa $0.07 / $0.30 por 1M de tokens (entrada/saída) e o Amazon Nova Lite custa $0.06 / $0.24. No custo combinado, Amazon Nova Lite é mais econômico.
Qual modelo possui maior janela de contexto e velocidade?+
O Gemini 2.0 Flash-Lite suporta 1.05M tokens de contexto contra 300K tokens do Amazon Nova Lite, enquanto Gemini 2.0 Flash-Lite entrega maior velocidade de geração.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
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Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.
Fontes oficiais: Documentação oficial de API da Google e Amazon e benchmarks independentes (2026).