Head-to-Head Model Comparison

o4-mini vs o3-mini

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: October 2026Política editorial

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o4-miniProfile

o3-miniProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

OpenAI

o4-mini

Motor de Raciocínio Profundo

O o4-mini da OpenAI é um modelo de IA projetado para raciocínio lógico profundo, matemática avançada e análise científica passo a passo, oferecendo janela de contexto de 200K, velocidade de 105 tokens/s, índice de inteligência de 50/100 e t

Intelligence Index50 / 100

Input Token:

$1.10 / 1M

Output Token:

$4.40 / 1M

Context Window:

200K tokens

SWE-bench Verified:

57.5%

OpenAI

o3-mini

Motor de Raciocínio Profundo

O o3-mini da OpenAI é um modelo de IA projetado para raciocínio lógico profundo, matemática avançada e análise científica passo a passo, oferecendo janela de contexto de 200K, velocidade de 85 tokens/s, índice de inteligência de 51/100 e ta

Intelligence Index51 / 100

Input Token:

$1.10 / 1M

Output Token:

$4.40 / 1M

Context Window:

200K tokens

SWE-bench Verified:

49%

Principais Diferenças em Resumo

o4-mini is 1.1x cheaper for API usage (input + output tokens combined).
o4-mini is faster at 105 tok/s vs 85 tok/s.
o4-mini leads on SWE-bench coding (57.5% vs 49.0%).

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

Feature	o4-mini	o3-mini
Intelligence Index Composite reasoning & knowledge score (0-100)	50	51
Provider	OpenAI	OpenAI
Input Price Cost per million input tokens	$1.10 / 1M	$1.10 / 1M
Output Price Cost per million output tokens	$4.40 / 1M	$4.40 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.85 / 1M	$1.05 / 1M
Context Window Maximum input + output tokens	200K tokens~300 A4 pages of text	200K tokens~300 A4 pages of text
Max Output Tokens Per single request	100K	100K
Throughput Speed Tokens generated per second	105 tok/s	85 tok/s
SWE-bench Verified Real-world software engineering	57.5%	49%
GPQA Diamond Graduate-level reasoning	73%	79.7%
Cached Input Price Prompt caching discount per 1M tokens	$0.28 / 1M	$0.55 / 1M

Quem vence em cada categoria?

At-a-glance decision framework

Coding

o4-mini

+8.5% SWE-bench lead

Cost

o4-mini

1.1x cheaper monthly runtime

Speed

o4-mini

+24% faster generation

Context

Tied

200K tokens window

Pontuações de Benchmarks Verificadas

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

o4-minio3-mini

SWE-bench Verified (Autonomous Coding)

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

57.5%vs49%

GPQA Diamond (Doctorate-Level Science & Math)

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

73%vs79.7%

MMLU-Pro (Multi-task Language Understanding)

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

83%vs82.4%

LMSYS Chatbot Arena Elo

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

1325ptsvs1310pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

11.2%vs12.8%

Terminal-Bench (Agentic Coding & Terminal Use)

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

36%vs32.3%

SciCode (Scientific Computing)

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

38.5%vs29.4%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

65%vs51.6%

AIME (Advanced Math Competition)

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

89.5%vs91.7%

Long-Context Reasoning

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

74.5%vs74.2%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

105 tok/s vs85 tok/s

Latência e Tempo de Resposta

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

o4-mini1.80s

o3-mini1.40s

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

o4-mini6.56s

o3-mini7.28s

Simulador Interativo de Custo de Tokens

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)

o4-mini Monthly API Bill

$6.02 / month

$1.1/1M in · $4.4/1M out

o3-mini Monthly API Bill

$6.44 / month

$1.1/1M in · $4.4/1M out

o4-mini saves approximately $0.41 / month (6%) under this workload.1.1x Savings

o4-mini · Strengths & Key Advantages

Janela de contexto de 200K com limite máximo de saída de 100K tokens (SWE-bench Verified 57.5% · GPQA Diamond 73%)
Taxa de transferência rápida de 105 tokens/segundo com latência inicial (TTFT) de 1800 ms
Economia de API competitiva ($1.1/$4.4 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

o3-mini · Strengths & Key Advantages

Janela de contexto de 200K com limite máximo de saída de 100K tokens (SWE-bench Verified 49% · GPQA Diamond 79.7%)
Taxa de transferência rápida de 85 tokens/segundo com latência inicial (TTFT) de 1400 ms
Economia de API competitiva ($1.1/$4.4 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	o4-mini	o3-mini
Cost per Task Estimated USD to finish one task	$0.72	$1.30
Output Tokens / Task Tokens generated per task	45K	45K
Reasoning Tokens / Task Thinking tokens burned per task	25K	25K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

Feature	o4-mini	o3-mini
Official API Model ID (SDK)	o4-mini	o3-mini
API Protocol	OpenAI Responses API & Chat Completions v1	OpenAI Responses API & Chat Completions v1
Release Date	2025-04	2025-01
Knowledge Cutoff	June 2024	October 2023
Architecture	Compact reasoning transformer	Chain-of-Thought Reasoning Dense
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)	Flat rate ($1.1/1M in) across full 200K window	Flat rate ($1.1/1M in) across full 200K window
Prompt Cache Policy & TTL	Automatic prefix caching at $0.275/1M (no extra cache-write fee)	Automatic prefix caching at $0.55/1M (no extra cache-write fee)
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	Native Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning Support	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
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	OpenAI Preparedness Framework Audited & System Card Published
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

o4-mini vs o3-mini: Respostas Rápidas (FAQ)

Which is more intelligent, o4-mini or o3-mini?

o3-mini is more intelligent. It scores 51 compared with 50 on the composite Intelligence Index.

Which model is faster?

o4-mini is faster, generating 105 tokens per second compared with 85 tokens per second.

Which model is cheaper to run?

o4-mini is cheaper at $0.85 per 1M tokens blended, compared with $1.05 (7:2:1 cache:input:output ratio).

Which model has lower latency?

o3-mini has lower latency, with a time to first token of 1.40s compared with 1.80s.

Veredito

Tanto o4-mini (Indicado para raciocínio lógico profundo, matemática avançada e análise científica passo a passo, arquiteturas RAG corporativas e integração escalável via API.) quanto o3-mini (Indicado para raciocínio lógico profundo, matemática avançada e análise científica passo a passo, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: o3-mini lidera em inteligência geral e programação, o4-mini oferece geração mais rápida e o4-mini apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, o4-mini ou o3-mini?+

Nas avaliações de inteligência e código, o3-mini leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, o4-mini ou o3-mini?+

O o4-mini custa $1.10 / $4.40 por 1M de tokens (entrada/saída) e o o3-mini custa $1.10 / $4.40. No custo combinado, o4-mini é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O o4-mini suporta 200K tokens de contexto contra 200K tokens do o3-mini, enquanto o4-mini entrega maior velocidade de geração.

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)

o4-mini vs o3-mini

Troque e Compare Qualquer Modelo

o4-mini

o3-mini

Quem vence em cada categoria?

Pontuações de Benchmarks Verificadas

Latência e Tempo de Resposta

Simulador Interativo de Custo de Tokens

o4-mini · Strengths & Key Advantages

Considerations & Trade-offs

o3-mini · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificações Técnicas

o4-mini vs o3-mini: Respostas Rápidas (FAQ)

Veredito

Perguntas Frequentes (FAQ)

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