Head-to-Head Model Comparison

Amazon Nova Micro vs Gemini 4 Argon

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Проверено исследовательской группой GetInfoUsПоследняя проверка: October 2026Редакционная политика
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Compare Amazon Nova Micro by Amazon against Gemini 4 Argon by Google across real-world coding, reasoning, token economics, and latency.

Прямое сравнение (VS)

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Popular Matchups:
Amazon

Amazon Nova Micro

Высокопроизводительный ИИ

Amazon Nova Micro от Amazon — передовая модель искусственного интеллекта с контекстным окном 128K токенов и стоимостью API $0.035/1M входящих и $0.14/1M исходящих токенов для программирования, аналитики и автоматизации.

Intelligence Index34 / 100
Input Token:

$0.04 / 1M

Output Token:

$0.14 / 1M

Context Window:

128K tokens

SWE-bench Verified:

23%

Google

Gemini 4 Argon

Модель глубокого рассуждения

Gemini 4 Argon от Google — передовая модель искусственного интеллекта с контекстным окном 1M токенов и стоимостью API $2/1M входящих и $10/1M исходящих токенов для программирования, аналитики и автоматизации.

Intelligence Index97 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

81.9%

Ключевые отличия кратко

  • Amazon Nova Micro is 63.3x cheaper for API usage (input + output tokens combined).
  • Gemini 4 Argon has a larger context window (1M vs 128K tokens).
  • Amazon Nova Micro is faster at 175 tok/s vs 115 tok/s.
  • Gemini 4 Argon leads on SWE-bench coding (81.9% vs 23.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureAmazon Nova MicroGemini 4 Argon
Intelligence Index
Composite reasoning & knowledge score (0-100)
3497
Provider
AmazonGoogle
Input Price
Cost per million input tokens
$0.04 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$0.14 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.03 / 1M$1.47 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
8K1000K
Throughput Speed
Tokens generated per second
175 tok/s115 tok/s
SWE-bench Verified
Real-world software engineering
23%81.9%
GPQA Diamond
Graduate-level reasoning
33.5%81.5%
Cached Input Price
Prompt caching discount per 1M tokens
$0.01 / 1M$0.10 / 1M

Кто лидирует в каждой категории?

At-a-glance decision framework
Coding
Gemini 4 Argon
+58.9% SWE-bench lead
Cost
Amazon Nova Micro
63.3x cheaper monthly runtime
Speed
Amazon Nova Micro
+52% faster generation
Context
Gemini 4 Argon
1M tokens window

Результаты проверенных бенчмарков

Official evaluation metrics verified by independent third-party research labs.

Amazon Nova MicroGemini 4 Argon
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

23%vs81.9%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

33.5%vs81.5%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

52%vs90.8%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1195ptsvs1525pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

2.8%vs18.9%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

15.2%vs57.4%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

16%vs56.4%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

26%vs80.5%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

30.5%vs94.8%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

60%vs96.4%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

175 tok/s vs115 tok/s

Задержка и скорость ответа

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
Amazon Nova Micro0.18s
Gemini 4 Argon0.85s
Est. End-to-End Response (500 tokens)TTFT + generation time
Amazon Nova Micro3.04s
Gemini 4 Argon5.20s

Интерактивный калькулятор стоимости токенов

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Amazon Nova Micro Monthly API Bill
$0.19 / month
$0.035/1M in · $0.14/1M out
Gemini 4 Argon Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
Amazon Nova Micro saves approximately $11.96 / month (98%) under this workload.63.3x Savings

Amazon Nova Micro · Strengths & Key Advantages

  • Современная архитектура Ultra-Fast Text-Only Dense Transformer от Amazon с поддержкой до 128K токенов контекста
  • Оптимальная стоимость использования ($0.035/1M вход, $0.14/1M выход) и высокая скорость генерации
  • Высокие результаты в задачах написания кода, логического мышления и многоязычной обработки
Considerations & Trade-offs
  • При работе с максимальным контекстом требуется контроль расхода токенов
  • Для узкоспециализированных задач рекомендуется точная настройка системных промптов

Gemini 4 Argon · Strengths & Key Advantages

  • Современная архитектура Pathways Multimodal Sparse Mixture-of-Experts от Google с поддержкой до 1M токенов контекста
  • Оптимальная стоимость использования ($2/1M вход, $10/1M выход) и высокая скорость генерации
  • Высокие результаты в задачах написания кода, логического мышления и многоязычной обработки
Considerations & Trade-offs
  • При работе с максимальным контекстом требуется контроль расхода токенов
  • Для узкоспециализированных задач рекомендуется точная настройка системных промптов

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricAmazon Nova MicroGemini 4 Argon
Cost per Task
Estimated USD to finish one task
$0.03$2.45
Output Tokens / Task
Tokens generated per task
15K75K
Reasoning Tokens / Task
Thinking tokens burned per task
0K36K

Технические характеристики

Architecture, release timeline, capabilities, and modalities.

FeatureAmazon Nova MicroGemini 4 Argon
Official API Model ID (SDK)nova-micromodels/gemini-4-argon
API ProtocolAmazon REST API (OpenAI-Compatible)Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date2024-122026-09
Knowledge CutoffOctober 2024June 2026
ArchitectureUltra-Fast Text-Only Dense TransformerPathways Multimodal Sparse Mixture-of-Experts
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.035/1M in) across full 128K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.009/1M tokensImplicit + Explicit Context Caching at $0.1/1M with configurable TTL
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsBuilt-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationVertex AI Supervised Adapter Tuning & Context Distillation
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)
Quantization & Min GPU VRAMCloud-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 ClassificationAmazon Production Safety & Alignment VerifiedGoogle DeepMind Frontier Safety Framework Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestexttext, vision, audio, video
Output Modalitiestexttext

Amazon Nova Micro vs Gemini 4 Argon: Быстрые ответы (FAQ)

Which is more intelligent, Amazon Nova Micro or Gemini 4 Argon?

Gemini 4 Argon is more intelligent. It scores 97 compared with 34 on the composite Intelligence Index.

Which model is faster?

Amazon Nova Micro is faster, generating 175 tokens per second compared with 115 tokens per second.

Which model is cheaper to run?

Amazon Nova Micro is cheaper at $0.03 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Amazon Nova Micro has lower latency, with a time to first token of 0.18s compared with 0.85s.

Which model has a larger context window?

Gemini 4 Argon has a larger context window, supporting 1M tokens compared with 128K tokens.

Вердикт

Choose Amazon Nova Micro for корпоративной автоматизации, разработки по, ии-агентов и продуктовых решений на базе amazon, or choose Gemini 4 Argon for корпоративной автоматизации, разработки по, ии-агентов и продуктовых решений на базе google.

Часто задаваемые вопросы (FAQ)

Which is cheaper: Amazon Nova Micro or Gemini 4 Argon?+

Amazon Nova Micro costs $0.035/1M input and $0.14/1M output tokens, while Gemini 4 Argon costs $2/1M input and $10/1M output tokens.

Which model has a larger context window: Amazon Nova Micro or Gemini 4 Argon?+

Amazon Nova Micro supports 128K tokens whereas Gemini 4 Argon supports 1M tokens.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

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.

Официальные источники: Amazon & Google Official Documentation