Head-to-Head Model Comparison

Claude 3.5 Haiku vs GPT-4o mini

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial

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Claude 3.5 HaikuProfile

GPT-4o miniProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Anthropic

Claude 3.5 Haiku

Model Agen Otonom & Alat

Claude 3.5 Haiku dari Anthropic adalah model AI yang dirancang untuk alur kerja agen otonom, pemanggilan alat (tool calling), dan otomatisasi multi-langkah, menghadirkan jendela konteks 200K, kecepatan 130 token/detik, indeks kecerdasan 36/

Intelligence Index36 / 100

Input Token:

$0.80 / 1M

Output Token:

$4.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

40.6%

OpenAI

GPT-4o mini

Model Ringan & Hemat Biaya

GPT-4o mini dari OpenAI adalah model AI yang dirancang untuk efisiensi biaya API maksimal per token dan throughput produksi yang ringan, menghadirkan jendela konteks 128K, kecepatan 140 token/detik, indeks kecerdasan 30/100, serta tarif $0.

Intelligence Index30 / 100

Input Token:

$0.15 / 1M

Output Token:

$0.60 / 1M

Context Window:

128K tokens

SWE-bench Verified:

24.5%

Perbedaan Utama Sekilas

GPT-4o mini is 5.6x cheaper for API usage (input + output tokens combined).
Claude 3.5 Haiku has a larger context window (200K vs 128K tokens).
GPT-4o mini is faster at 140 tok/s vs 130 tok/s.
Claude 3.5 Haiku leads on SWE-bench coding (40.6% vs 24.5%).

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

Feature	Claude 3.5 Haiku	GPT-4o mini
Intelligence Index Composite reasoning & knowledge score (0-100)	36	30
Provider	Anthropic	OpenAI
Input Price Cost per million input tokens	$0.80 / 1M	$0.15 / 1M
Output Price Cost per million output tokens	$4.00 / 1M	$0.60 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.62 / 1M	$0.14 / 1M
Context Window Maximum input + output tokens	200K tokens~300 A4 pages of text	128K tokens~192 A4 pages of text
Max Output Tokens Per single request	8K	16K
Throughput Speed Tokens generated per second	130 tok/s	140 tok/s
SWE-bench Verified Real-world software engineering	40.6%	24.5%
GPQA Diamond Graduate-level reasoning	41.6%	40.2%
Cached Input Price Prompt caching discount per 1M tokens	$0.08 / 1M	$0.07 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework

Coding

Claude 3.5 Haiku

+16.1% SWE-bench lead

Cost

GPT-4o mini

5.6x cheaper monthly runtime

Speed

GPT-4o mini

+8% faster generation

Context

Claude 3.5 Haiku

200K tokens window

Skor Benchmark Terverifikasi

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

Claude 3.5 HaikuGPT-4o mini

SWE-bench Verified (Autonomous Coding)

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

40.6%vs24.5%

GPQA Diamond (Doctorate-Level Science & Math)

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

41.6%vs40.2%

MMLU-Pro (Multi-task Language Understanding)

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

69.2%vs58.5%

LMSYS Chatbot Arena Elo

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

1260ptsvs1228pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

6.7%vs6.4%

Terminal-Bench (Agentic Coding & Terminal Use)

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

26.8%vs16.2%

SciCode (Scientific Computing)

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

24.4%vs14.7%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

43.6%vs28.3%

AIME (Advanced Math Competition)

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

47.8%vs46.2%

Long-Context Reasoning

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

62.3%vs52.7%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

130 tok/s vs140 tok/s

Latensi & Waktu Respons

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

GPT-4o mini0.31s

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

Claude 3.5 Haiku4.23s

GPT-4o mini3.88s

Simulator Biaya Token Interaktif

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

GPT-4o mini Monthly API Bill

$0.88 / month

$0.15/1M in · $0.6/1M out

GPT-4o mini saves approximately $4.04 / month (82%) under this workload.5.6x Savings

Claude 3.5 Haiku · Strengths & Key Advantages

Jendela konteks 200K dengan kapasitas output maksimum hingga 8K token (SWE-bench Verified 40.6% · GPQA Diamond 41.6%)
Kecepatan generasi tinggi 130 token/detik dengan latensi token pertama (TTFT) hanya 380 ms
Skema harga API kompetitif (tarif $0.8/$4 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur

Considerations & Trade-offs

Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi

GPT-4o mini · Strengths & Key Advantages

Jendela konteks 128K dengan kapasitas output maksimum hingga 16K token (SWE-bench Verified 24.5% · GPQA Diamond 40.2%)
Kecepatan generasi tinggi 140 token/detik dengan latensi token pertama (TTFT) hanya 310 ms
Skema harga API kompetitif (tarif $0.15/$0.6 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur

Considerations & Trade-offs

Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi

Token Use & Task Economics

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

Metric	Claude 3.5 Haiku	GPT-4o mini
Cost per Task Estimated USD to finish one task	$0.90	$0.16
Output Tokens / Task Tokens generated per task	45K	45K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

Feature	Claude 3.5 Haiku	GPT-4o mini
Official API Model ID (SDK)	claude-3-5-haiku-20241101	gpt-4o-mini
API Protocol	Anthropic Messages API + AWS Bedrock + Vertex AI	OpenAI Responses API & Chat Completions v1
Release Date	2024-11	2024-07
Knowledge Cutoff	July 2024	October 2023
Architecture	Optimized Lightweight Transformer	Small Multimodal Dense
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) · 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 ($0.15/1M in) across full 128K window
Prompt Cache Policy & TTL	$0.08/1M cached read (90% off); 5-min default & 1-hour extended TTL	Automatic prefix caching at $0.075/1M (no extra cache-write fee)
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	Native Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning Support	Custom Model Tuning via Amazon Bedrock & Prompt Distillation	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) · Vision (~258–765 tokens per image tile)
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	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, vision
Output Modalities	text	text

Claude 3.5 Haiku vs GPT-4o mini: Jawaban Cepat (FAQ)

Which is more intelligent, Claude 3.5 Haiku or GPT-4o mini?

Claude 3.5 Haiku is more intelligent. It scores 36 compared with 30 on the composite Intelligence Index.

Which model is faster?

GPT-4o mini is faster, generating 140 tokens per second compared with 130 tokens per second.

Which model is cheaper to run?

GPT-4o mini is cheaper at $0.14 per 1M tokens blended, compared with $0.62 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-4o mini has lower latency, with a time to first token of 0.31s compared with 0.38s.

Which model has a larger context window?

Claude 3.5 Haiku has a larger context window, supporting 200K tokens compared with 128K tokens.

Kesimpulan

Baik Claude 3.5 Haiku (Sangat cocok untuk alur kerja agen otonom, pemanggilan alat (tool calling), dan otomatisasi multi-langkah, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun GPT-4o mini (Sangat cocok untuk efisiensi biaya API maksimal per token dan throughput produksi yang ringan, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Claude 3.5 Haiku unggul dalam penalaran dan pemrograman, GPT-4o mini memberikan kecepatan generasi token lebih tinggi, dan GPT-4o mini lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, Claude 3.5 Haiku atau GPT-4o mini?+

Dalam indeks kecerdasan gabungan dan benchmark coding, Claude 3.5 Haiku memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API Claude 3.5 Haiku vs GPT-4o mini?+

Claude 3.5 Haiku mengenakan biaya $0.80 / $4.00 per 1M token input/output, sedangkan GPT-4o mini sebesar $0.15 / $0.60. Secara keseluruhan, GPT-4o mini lebih hemat biaya.

Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+

Claude 3.5 Haiku mendukung konteks 200K token dibandingkan 128K token pada GPT-4o mini, sementara GPT-4o mini unggul dalam kecepatan output token per detik.

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 GPT-4o mini

Ganti & Bandingkan Model Apa Saja

Claude 3.5 Haiku

GPT-4o mini

Siapa Unggul di Mana?

Skor Benchmark Terverifikasi

Latensi & Waktu Respons

Simulator Biaya Token Interaktif

Claude 3.5 Haiku · Strengths & Key Advantages

Considerations & Trade-offs

GPT-4o mini · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Spesifikasi Teknis

Claude 3.5 Haiku vs GPT-4o mini: Jawaban Cepat (FAQ)

Kesimpulan

Pertanyaan Umum (FAQ)

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