Head-to-Head Model Comparison

Claude 3.5 Haiku vs Gemini 2.0 Flash

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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

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Claude 3.5 HaikuProfile

Gemini 2.0 FlashProfile

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Popular Matchups:

Anthropic

Claude 3.5 Haiku

IA Agêntica e Uso de Ferramentas

O Claude 3.5 Haiku da Anthropic é um modelo de IA projetado para fluxos de trabalho agênticos autônomos, chamada de ferramentas e automação, oferecendo janela de contexto de 200K, velocidade de 130 tokens/s, índice de inteligência de 36/100

Intelligence Index36 / 100

Input Token:

$0.80 / 1M

Output Token:

$4.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

40.6%

Google

Gemini 2.0 Flash

Inferência Ultrarrápida

O Gemini 2.0 Flash da Google é um modelo de IA projetado para respostas em tempo real com latência ultrabaixa e roteamento de alto volume, oferecendo janela de contexto de 1.0M, velocidade de 240 tokens/s, índice de inteligência de 40/100 e

Intelligence Index40 / 100

Input Token:

$0.10 / 1M

Output Token:

$0.40 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

42%

Principais Diferenças em Resumo

Gemini 2.0 Flash is 9.0x cheaper for API usage (input + output tokens combined).
Gemini 2.0 Flash has a larger context window (1M vs 200K tokens).
Gemini 2.0 Flash is faster at 240 tok/s vs 130 tok/s.
Gemini 2.0 Flash leads on SWE-bench coding (42.0% vs 40.6%).

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

Feature	Claude 3.5 Haiku	Gemini 2.0 Flash
Intelligence Index Composite reasoning & knowledge score (0-100)	36	40
Provider	Anthropic	Google
Input Price Cost per million input tokens	$0.80 / 1M	$0.10 / 1M
Output Price Cost per million output tokens	$4.00 / 1M	$0.40 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.62 / 1M	$0.08 / 1M
Context Window Maximum input + output tokens	200K tokens~300 A4 pages of text	1.05M tokens~1,573 A4 pages of text
Max Output Tokens Per single request	8K	8K
Throughput Speed Tokens generated per second	130 tok/s	240 tok/s
SWE-bench Verified Real-world software engineering	40.6%	42%
GPQA Diamond Graduate-level reasoning	41.6%	55.4%
Cached Input Price Prompt caching discount per 1M tokens	$0.08 / 1M	$0.03 / 1M

Quem vence em cada categoria?

At-a-glance decision framework

Coding

Gemini 2.0 Flash

+1.4% SWE-bench lead

Cost

Gemini 2.0 Flash

9.0x cheaper monthly runtime

Speed

Gemini 2.0 Flash

+85% faster generation

Context

Gemini 2.0 Flash

1.05M tokens window

Pontuações de Benchmarks Verificadas

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

Claude 3.5 HaikuGemini 2.0 Flash

SWE-bench Verified (Autonomous Coding)

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

40.6%vs42%

GPQA Diamond (Doctorate-Level Science & Math)

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

41.6%vs55.4%

MMLU-Pro (Multi-task Language Understanding)

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

69.2%vs71%

LMSYS Chatbot Arena Elo

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

1260ptsvs1302pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

6.7%vs8.9%

Terminal-Bench (Agentic Coding & Terminal Use)

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

26.8%vs27.7%

SciCode (Scientific Computing)

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

24.4%vs25.2%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

43.6%vs44.9%

AIME (Advanced Math Competition)

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

47.8%vs63.7%

Long-Context Reasoning

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

62.3%vs63.9%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

130 tok/s vs240 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

Claude 3.5 Haiku0.38s

Gemini 2.0 Flash0.28s

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

Claude 3.5 Haiku4.23s

Gemini 2.0 Flash2.36s

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)

Claude 3.5 Haiku Monthly API Bill

$4.92 / month

$0.8/1M in · $4/1M out

Gemini 2.0 Flash Monthly API Bill

$0.55 / month

$0.1/1M in · $0.4/1M out

Gemini 2.0 Flash saves approximately $4.37 / month (89%) under this workload.9.0x Savings

Claude 3.5 Haiku · Strengths & Key Advantages

Janela de contexto de 200K com limite máximo de saída de 8K tokens (SWE-bench Verified 40.6% · GPQA Diamond 41.6%)
Taxa de transferência rápida de 130 tokens/segundo com latência inicial (TTFT) de 380 ms
Economia de API competitiva ($0.8/$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

Gemini 2.0 Flash · Strengths & Key Advantages

Janela de contexto de 1.0M com limite máximo de saída de 8K tokens (SWE-bench Verified 42% · GPQA Diamond 55.4%)
Taxa de transferência rápida de 240 tokens/segundo com latência inicial (TTFT) de 280 ms
Economia de API competitiva ($0.1/$0.4 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	Claude 3.5 Haiku	Gemini 2.0 Flash
Cost per Task Estimated USD to finish one task	$0.90	$0.13
Output Tokens / Task Tokens generated per task	45K	60K
Reasoning Tokens / Task Thinking tokens burned per task	0K	33K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

Feature	Claude 3.5 Haiku	Gemini 2.0 Flash
Official API Model ID (SDK)	claude-3-5-haiku-20241101	models/gemini-2-flash
API Protocol	Anthropic Messages API + AWS Bedrock + Vertex AI	Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date	2024-11	2024-12
Knowledge Cutoff	July 2024	August 2024
Architecture	Optimized Lightweight Transformer	Multimodal Flash MoE
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM	10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL	$0.08/1M cached read (90% off); 5-min default & 1-hour extended TTL	Implicit + Explicit Context Caching at $0.025/1M with configurable TTL
Computer Use / GUI Agent	Supported (Screen coordinate grounding, browser & desktop GUI action loops)	Supported (Screen coordinate grounding, browser & desktop GUI action loops)
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 Citations + Code Execution Tool + MCP Connectors	Built-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning Support	Custom Model Tuning via Amazon Bedrock & Prompt Distillation	Vertex AI Supervised Adapter Tuning & Context Distillation
Multimodal Token Billing	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)	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 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	Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated	Google DeepMind Frontier Safety Framework 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, vision, audio, video
Output Modalities	text	text

Claude 3.5 Haiku vs Gemini 2.0 Flash: Respostas Rápidas (FAQ)

Which is more intelligent, Claude 3.5 Haiku or Gemini 2.0 Flash?

Gemini 2.0 Flash is more intelligent. It scores 40 compared with 36 on the composite Intelligence Index.

Which model is faster?

Gemini 2.0 Flash is faster, generating 240 tokens per second compared with 130 tokens per second.

Which model is cheaper to run?

Gemini 2.0 Flash is cheaper at $0.08 per 1M tokens blended, compared with $0.62 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 2.0 Flash has lower latency, with a time to first token of 0.28s compared with 0.38s.

Which model has a larger context window?

Gemini 2.0 Flash has a larger context window, supporting 1.05M tokens compared with 200K tokens.

Veredito

Tanto Claude 3.5 Haiku (Indicado para fluxos de trabalho agênticos autônomos, chamada de ferramentas e automação, arquiteturas RAG corporativas e integração escalável via API.) quanto Gemini 2.0 Flash (Indicado para respostas em tempo real com latência ultrabaixa e roteamento de alto volume, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: Gemini 2.0 Flash lidera em inteligência geral e programação, Gemini 2.0 Flash oferece geração mais rápida e Gemini 2.0 Flash apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, Claude 3.5 Haiku ou Gemini 2.0 Flash?+

Nas avaliações de inteligência e código, Gemini 2.0 Flash leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, Claude 3.5 Haiku ou Gemini 2.0 Flash?+

O Claude 3.5 Haiku custa $0.80 / $4.00 por 1M de tokens (entrada/saída) e o Gemini 2.0 Flash custa $0.10 / $0.40. No custo combinado, Gemini 2.0 Flash é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O Claude 3.5 Haiku suporta 200K tokens de contexto contra 1.05M tokens do Gemini 2.0 Flash, enquanto Gemini 2.0 Flash 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)

Claude 3.5 Haiku vs Gemini 2.0 Flash

Troque e Compare Qualquer Modelo

Claude 3.5 Haiku

Gemini 2.0 Flash

Quem vence em cada categoria?

Pontuações de Benchmarks Verificadas

Latência e Tempo de Resposta

Simulador Interativo de Custo de Tokens

Claude 3.5 Haiku · Strengths & Key Advantages

Considerations & Trade-offs

Gemini 2.0 Flash · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificações Técnicas

Claude 3.5 Haiku vs Gemini 2.0 Flash: Respostas Rápidas (FAQ)

Veredito

Perguntas Frequentes (FAQ)

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