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 by Google and Amazon Nova Lite by Amazon represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Amazon Nova Lite holds a notable pricing advantage for token ingestion. On output generation, Amazon Nova Lite is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Gemini 2.0 Flash-Lite provides an expanded memory horizon with 1,049K tokens. In latency-sensitive production environments, Gemini 2.0 Flash-Lite leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
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Gemini 2.0 Flash-Lite
高性能 AI モデルGoogle が提供する Gemini 2.0 Flash-Lite は、最大 1.0M トークンのコンテキストウィンドウを備え、入力 $0.075/100万トークン・出力 $0.3/100万トークンで利用可能な、コーディング・推論・業務自動化向け AI モデルです。
$0.07 / 1M
$0.30 / 1M
1.05M tokens
N/A
Amazon Nova Lite
高性能 AI モデルAmazon が提供する Amazon Nova Lite は、最大 300K トークンのコンテキストウィンドウを備え、入力 $0.06/100万トークン・出力 $0.24/100万トークンで利用可能な、コーディング・推論・業務自動化向け AI モデルです。
$0.06 / 1M
$0.24 / 1M
300K tokens
31.2%
ひと目でわかる主な違い
- 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 |
分野別勝者スコアカード
At-a-glance decision frameworkEvaluations ongoing
検証済みベンチマークスコア比較
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.
レイテンシ＆応答時間
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
リアルタイムAPIトークン料金シミュレーター
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Gemini 2.0 Flash-Lite · Strengths & Key Advantages
- Google の高度な Distilled lightweight multimodal transformer アーキテクチャと 1.0M トークンのコンテキスト処理能力
- 優れたコストパフォーマンス（入力 $0.075/1M、出力 $0.3/1M）と安定した応答速度
- プログラミング、論理的推論、多言語タスクにおいて高いベンチマーク精度を実現
Considerations & Trade-offs
- 大規模な長文コンテキスト処理時はトークン消費量の最適化が必要
- 専門領域のタスクでは適切なプロンプト設計や RAG の併用が推奨される
Amazon Nova Lite · Strengths & Key Advantages
- Amazon の高度な High-Speed Multimodal Foundation Transformer アーキテクチャと 300K トークンのコンテキスト処理能力
- 優れたコストパフォーマンス（入力 $0.06/1M、出力 $0.24/1M）と安定した応答速度
- プログラミング、論理的推論、多言語タスクにおいて高いベンチマーク精度を実現
Considerations & Trade-offs
- 大規模な長文コンテキスト処理時はトークン消費量の最適化が必要
- 専門領域のタスクでは適切なプロンプト設計や RAG の併用が推奨される
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 |
技術仕様・スペック
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: よくある質問 (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.
総合評価
Verdict & Model Selection Recommendation: Choose Gemini 2.0 Flash-Lite if your priority is High-volume classification, extraction, and edge routing. Its performance in demanding tasks justifies its operational token cost. Choose Amazon Nova Lite if your workflow prioritizes AWS enterprise workloads, automated customer support, document digitization, and video scene analysis. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
よくある質問 (FAQ)
How does Gemini 2.0 Flash-Lite compare to Amazon Nova Lite in API token pricing and cost per token?+
Gemini 2.0 Flash-Lite costs $0.07 per 1M input tokens and $0.30 per 1M output tokens, whereas Amazon Nova Lite costs $0.06 input and $0.24 output. Overall, Amazon Nova Lite is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: Gemini 2.0 Flash-Lite or Amazon Nova Lite?+
Gemini 2.0 Flash-Lite supports a context window of 1,049K tokens (~786k words), while Amazon Nova Lite supports 300K tokens (~225k words). Therefore, Gemini 2.0 Flash-Lite can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Gemini 2.0 Flash-Lite or Amazon Nova Lite?+
Gemini 2.0 Flash-Lite scores at the frontier of coding benchmarks, while Amazon Nova Lite scores 31.2%. For complex autonomous debugging and agentic engineering, Amazon Nova Lite provides robust code generation and tool calling.
What is the difference in reasoning capability and extended thinking between Gemini 2.0 Flash-Lite and Amazon Nova Lite?+
Gemini 2.0 Flash-Lite is optimized for low-latency direct generation. In contrast, Amazon Nova Lite focuses on standard fast inference.
How does inference speed (tokens per second) compare between Gemini 2.0 Flash-Lite and Amazon Nova Lite?+
Gemini 2.0 Flash-Lite generates approximately 280 tokens per second, while Amazon Nova Lite delivers 135 tokens per second. In latency-sensitive production environments, Gemini 2.0 Flash-Lite provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Gemini 2.0 Flash-Lite and Amazon Nova Lite to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Amazon Nova Lite to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Gemini 2.0 Flash-Lite. This tiered routing pattern cuts overall API bills by up to 70%.
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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- Amazon Nova Lite vs Amazon Nova Micro: Benchmarks, Pricing & Speed Comparison比較
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- Aion-3.0 vs Gemini 3.6 Flash: Benchmarks, Pricing & Speed Comparison比較
- Aion-Mini vs Laguna XS 2.1: Benchmarks, Pricing & Speed Comparison比較
- Aya Expanse 32B vs Llama 3.2 90B Vision: Benchmarks, Pricing & Speed Comparison比較
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.
公的ソース: GetInfoUs Independent AI Benchmarks & Official API Specs