Head-to-Head Model Comparison

GPT-4.1 nano vs Amazon Nova Micro

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs 연구팀 검토 완료최종 검토일: October 2026편집 정책

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GPT-4.1 nanoProfile

Amazon Nova MicroProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

OpenAI

GPT-4.1 nano

경량 고효율 가성비 모델

OpenAI의 GPT-4.1 nano 모델은 극대화된 토큰당 비용 효율성과 빠른 프로덕션 추론 처리에 최적화된 AI 모델로, 1.0M 컨텍스트 윈도우, 초당 220 토큰의 생성 속도, 종합 지능 지수 26/100점(1M 토큰당 입력 $0.1 / 출력 $0.4)을 제공합니다.

Intelligence Index26 / 100

Input Token:

$0.10 / 1M

Output Token:

$0.40 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

24%

Amazon

Amazon Nova Micro

경량 고효율 가성비 모델

Amazon의 Amazon Nova Micro 모델은 극대화된 토큰당 비용 효율성과 빠른 프로덕션 추론 처리에 최적화된 AI 모델로, 128K 컨텍스트 윈도우, 초당 175 토큰의 생성 속도, 종합 지능 지수 34/100점(1M 토큰당 입력 $0.035 / 출력 $0.14)을 제공합니다.

Intelligence Index34 / 100

Input Token:

$0.04 / 1M

Output Token:

$0.14 / 1M

Context Window:

128K tokens

SWE-bench Verified:

23%

한눈에 보는 핵심 차이점

Amazon Nova Micro is 2.9x cheaper for API usage (input + output tokens combined).
GPT-4.1 nano has a larger context window (1M vs 128K tokens).
GPT-4.1 nano is faster at 220 tok/s vs 175 tok/s.
GPT-4.1 nano leads on SWE-bench coding (24.0% vs 23.0%).

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Feature	GPT-4.1 nano	Amazon Nova Micro
Intelligence Index Composite reasoning & knowledge score (0-100)	26	34
Provider	OpenAI	Amazon
Input Price Cost per million input tokens	$0.10 / 1M	$0.04 / 1M
Output Price Cost per million output tokens	$0.40 / 1M	$0.14 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.08 / 1M	$0.03 / 1M
Context Window Maximum input + output tokens	1.05M tokens~1,571 A4 pages of text	128K tokens~192 A4 pages of text
Max Output Tokens Per single request	33K	8K
Throughput Speed Tokens generated per second	220 tok/s	175 tok/s
SWE-bench Verified Real-world software engineering	24%	23%
GPQA Diamond Graduate-level reasoning	38%	33.5%
Cached Input Price Prompt caching discount per 1M tokens	$0.03 / 1M	$0.01 / 1M

부문별 우위 모델

At-a-glance decision framework

Coding

GPT-4.1 nano

+1.0% SWE-bench lead

Cost

Amazon Nova Micro

2.9x cheaper monthly runtime

Speed

GPT-4.1 nano

+26% faster generation

Context

GPT-4.1 nano

1.05M tokens window

검증된 벤치마크 점수 비교

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

GPT-4.1 nanoAmazon Nova Micro

SWE-bench Verified (Autonomous Coding)

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

24%vs23%

GPQA Diamond (Doctorate-Level Science & Math)

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

38%vs33.5%

MMLU-Pro (Multi-task Language Understanding)

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

55.5%vs52%

LMSYS Chatbot Arena Elo

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

1195ptsvs1195pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

4.4%vs2.8%

Terminal-Bench (Agentic Coding & Terminal Use)

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

12.5%vs15.2%

SciCode (Scientific Computing)

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

15%vs16%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

25.5%vs26%

AIME (Advanced Math Competition)

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

30.5%vs30.5%

Long-Context Reasoning

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

48%vs60%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

220 tok/s vs175 tok/s

지연 시간(Latency) 및 응답 속도

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

GPT-4.1 nano0.22s

Amazon Nova Micro0.18s

Est. End-to-End Response (500 tokens)TTFT + generation time

GPT-4.1 nano2.49s

Amazon Nova Micro3.04s

실시간 API 토큰 비용 시뮬레이터

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

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% cached

0% (Cold)50%90% (Warm)

GPT-4.1 nano Monthly API Bill

$0.55 / month

$0.1/1M in · $0.4/1M out

Amazon Nova Micro Monthly API Bill

$0.19 / month

$0.035/1M in · $0.14/1M out

Amazon Nova Micro saves approximately $0.36 / month (65%) under this workload.2.9x Savings

GPT-4.1 nano · Strengths & Key Advantages

1.0M 컨텍스트 윈도우 및 최대 33K 출력 토큰 생성 지원 (SWE-bench Verified 24% · GPQA Diamond 38%)
초당 220 토큰의 빠른 처리 속도와 220ms에 불과한 첫 토큰 지연 시간(TTFT)
합리적인 API 요금 체계(1M 토큰당 입력 $0.1 / 출력 $0.4)와 프롬프트 캐싱, 함수 호출 및 정형화된 JSON 출력 완벽 지원

Considerations & Trade-offs

독점 클라우드 전용 모델로 로컬 오프라인 서버에 가중치를 다운로드하여 실행할 수 없습니다
초고난도 학술 연구 및 수학 증명 과제에서는 상위 대형 추론 특화 모델이 더 깊은 분석을 제공할 수 있습니다

Amazon Nova Micro · Strengths & Key Advantages

128K 컨텍스트 윈도우 및 최대 8K 출력 토큰 생성 지원 (SWE-bench Verified 23% · GPQA Diamond 33.5%)
초당 175 토큰의 빠른 처리 속도와 180ms에 불과한 첫 토큰 지연 시간(TTFT)
합리적인 API 요금 체계(1M 토큰당 입력 $0.035 / 출력 $0.14)와 프롬프트 캐싱, 함수 호출 및 정형화된 JSON 출력 완벽 지원

Considerations & Trade-offs

독점 클라우드 전용 모델로 로컬 오프라인 서버에 가중치를 다운로드하여 실행할 수 없습니다
초고난도 학술 연구 및 수학 증명 과제에서는 상위 대형 추론 특화 모델이 더 깊은 분석을 제공할 수 있습니다

Token Use & Task Economics

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

Metric	GPT-4.1 nano	Amazon Nova Micro
Cost per Task Estimated USD to finish one task	$0.04	$0.03
Output Tokens / Task Tokens generated per task	42K	15K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

기술 사양 (Specifications)

Architecture, release timeline, capabilities, and modalities.

Feature	GPT-4.1 nano	Amazon Nova Micro
Official API Model ID (SDK)	gpt-4-1-nano	nova-micro
API Protocol	OpenAI Responses API & Chat Completions v1	Amazon REST API (OpenAI-Compatible)
Release Date	2025-04	2024-12
Knowledge Cutoff	June 2024	October 2024
Architecture	Dense multimodal transformer (nano)	Ultra-Fast Text-Only Dense 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)	Flat rate ($0.1/1M in) across full 1048K window	Flat rate ($0.035/1M in) across full 128K window
Prompt Cache Policy & TTL	Automatic prefix caching at $0.025/1M (no extra cache-write fee)	Cached input at $0.009/1M 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	Native Web Search tool + Hosted Code Interpreter & File Search RAG	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning Support	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)	API Prompt Engineering & RAG Distillation
Multimodal Token Billing	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)	Text BPE (~4 chars/token)
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	OpenAI Preparedness Framework Audited & System Card Published	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	text
Output Modalities	text	text

GPT-4.1 nano vs Amazon Nova Micro: 핵심 요약 문답 (FAQ)

Which is more intelligent, GPT-4.1 nano or Amazon Nova Micro?

Amazon Nova Micro is more intelligent. It scores 34 compared with 26 on the composite Intelligence Index.

Which model is faster?

GPT-4.1 nano is faster, generating 220 tokens per second compared with 175 tokens per second.

Which model is cheaper to run?

Amazon Nova Micro is cheaper at $0.03 per 1M tokens blended, compared with $0.08 (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 0.22s.

Which model has a larger context window?

GPT-4.1 nano has a larger context window, supporting 1.05M tokens compared with 128K tokens.

종합 평가

GPT-4.1 nano(극대화된 토큰당 비용 효율성과 빠른 프로덕션 추론 처리, 엔터프라이즈 RAG 지식베이스 및 대규모 프로덕션 API 연동에 최적.)와 Amazon Nova Micro(극대화된 토큰당 비용 효율성과 빠른 프로덕션 추론 처리, 엔터프라이즈 RAG 지식베이스 및 대규모 프로덕션 API 연동에 최적.) 모두 뛰어난 성능을 자랑합니다. 고난도 추론과 코딩 벤치마크에서는 Amazon Nova Micro가 앞서며, 토큰 생성 속도에서는 GPT-4.1 nano가 빠르고, 대규모 API 운영 비용 면에서는 Amazon Nova Micro가 더 경제적입니다.

자주 묻는 질문 (FAQ)

코딩과 복잡한 추론에는 GPT-4.1 nano와 Amazon Nova Micro 중 어느 모델이 더 나은가요?+

종합 지능 지수 및 코딩 벤치마크에서는 Amazon Nova Micro가 우위를 보입니다. 상단의 SWE-bench 및 GPQA 점수를 함께 확인해 보세요.

GPT-4.1 nano와 Amazon Nova Micro의 API 요금 차이는 얼마인가요?+

GPT-4.1 nano는 100만 토큰당 입력 $0.10 / 출력 $0.40이며, Amazon Nova Micro는 입력 $0.04 / 출력 $0.14입니다. 혼합 비용 기준으로는 Amazon Nova Micro가 더 저렴합니다.

어느 모델이 더 큰 컨텍스트 윈도우와 빠른 속도를 제공하나요?+

컨텍스트 길이는 GPT-4.1 nano가 1.05M 토큰, Amazon Nova Micro가 128K 토큰를 지원하며, 출력 속도 면에서는 GPT-4.1 nano가 더 빠릅니다.

AI Terminology & Guide

Explore Glossary →

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

Tokens & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

GPT-4.1 nano vs Amazon Nova Micro

원하는 AI 모델 선택 및 실시간 비교

GPT-4.1 nano

Amazon Nova Micro

부문별 우위 모델

검증된 벤치마크 점수 비교

지연 시간(Latency) 및 응답 속도

실시간 API 토큰 비용 시뮬레이터

GPT-4.1 nano · Strengths & Key Advantages

Considerations & Trade-offs

Amazon Nova Micro · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

기술 사양 (Specifications)

GPT-4.1 nano vs Amazon Nova Micro: 핵심 요약 문답 (FAQ)

종합 평가

자주 묻는 질문 (FAQ)

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