Head-to-Head Model Comparison

GPT-5 mini vs Claude Haiku 4.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial

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GPT-5 miniProfile

Claude Haiku 4.5Profile

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OpenAI

GPT-5 mini

Model Ringan & Hemat Biaya

GPT-5 mini dari OpenAI adalah model AI yang dirancang untuk efisiensi biaya API maksimal per token dan throughput produksi yang ringan, menghadirkan jendela konteks 400K, kecepatan 185 token/detik, indeks kecerdasan 46/100, serta tarif $0.2

Intelligence Index46 / 100

Input Token:

$0.25 / 1M

Output Token:

$2.00 / 1M

Context Window:

400K tokens

SWE-bench Verified:

52%

Anthropic

Claude Haiku 4.5

Inferensi Super Cepat

Claude Haiku 4.5 dari Anthropic adalah model AI yang dirancang untuk interaksi real-time dengan latensi sangat rendah dan routing bervolume tinggi, menghadirkan jendela konteks 200K, kecepatan 140 token/detik, indeks kecerdasan 54/100, sert

Intelligence Index54 / 100

Input Token:

$1.00 / 1M

Output Token:

$5.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

58.2%

Perbedaan Utama Sekilas

GPT-5 mini is 2.8x cheaper for API usage (input + output tokens combined).
GPT-5 mini has a larger context window (400K vs 200K tokens).
GPT-5 mini is faster at 185 tok/s vs 140 tok/s.
Claude Haiku 4.5 leads on SWE-bench coding (58.2% vs 52.0%).

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

Feature	GPT-5 mini	Claude Haiku 4.5
Intelligence Index Composite reasoning & knowledge score (0-100)	46	54
Provider	OpenAI	Anthropic
Input Price Cost per million input tokens	$0.25 / 1M	$1.00 / 1M
Output Price Cost per million output tokens	$2.00 / 1M	$5.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.27 / 1M	$0.77 / 1M
Context Window Maximum input + output tokens	400K tokens~600 A4 pages of text	200K tokens~300 A4 pages of text
Max Output Tokens Per single request	128K	64K
Throughput Speed Tokens generated per second	185 tok/s	140 tok/s
SWE-bench Verified Real-world software engineering	52%	58.2%
GPQA Diamond Graduate-level reasoning	66%	62.1%
Cached Input Price Prompt caching discount per 1M tokens	$0.03 / 1M	$0.10 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework

Coding

Claude Haiku 4.5

+6.2% SWE-bench lead

Cost

GPT-5 mini

2.8x cheaper monthly runtime

Speed

GPT-5 mini

+32% faster generation

Context

GPT-5 mini

400K tokens window

Skor Benchmark Terverifikasi

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

GPT-5 miniClaude Haiku 4.5

SWE-bench Verified (Autonomous Coding)

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

52%vs58.2%

GPQA Diamond (Doctorate-Level Science & Math)

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

66%vs62.1%

MMLU-Pro (Multi-task Language Understanding)

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

78.5%vs79.5%

LMSYS Chatbot Arena Elo

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

1315ptsvs1324pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

9.2%vsN/A

Terminal-Bench (Agentic Coding & Terminal Use)

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

30.5%vsN/A

SciCode (Scientific Computing)

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

32%vsN/A

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

56.5%vsN/A

AIME (Advanced Math Competition)

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

84%vsN/A

Long-Context Reasoning

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

68.5%vsN/A

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

185 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

GPT-5 mini0.70s

Claude Haiku 4.50.28s

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

GPT-5 mini3.40s

Claude Haiku 4.53.85s

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)

GPT-5 mini Monthly API Bill

$2.21 / month

$0.25/1M in · $2/1M out

Claude Haiku 4.5 Monthly API Bill

$6.15 / month

$1/1M in · $5/1M out

GPT-5 mini saves approximately $3.94 / month (64%) under this workload.2.8x Savings

GPT-5 mini · Strengths & Key Advantages

Jendela konteks 400K dengan kapasitas output maksimum hingga 128K token (SWE-bench Verified 52% · GPQA Diamond 66%)
Kecepatan generasi tinggi 185 token/detik dengan latensi token pertama (TTFT) hanya 700 ms
Skema harga API kompetitif (tarif $0.25/$2 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

Claude Haiku 4.5 · Strengths & Key Advantages

Jendela konteks 200K dengan kapasitas output maksimum hingga 64K token (SWE-bench Verified 58.2% · GPQA Diamond 62.1%)
Kecepatan generasi tinggi 140 token/detik dengan latensi token pertama (TTFT) hanya 280 ms
Skema harga API kompetitif (tarif $1/$5 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	GPT-5 mini	Claude Haiku 4.5
Cost per Task Estimated USD to finish one task	$0.32	$0.70
Output Tokens / Task Tokens generated per task	50K	20K
Reasoning Tokens / Task Thinking tokens burned per task	24K	10K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

Feature	GPT-5 mini	Claude Haiku 4.5
Official API Model ID (SDK)	gpt-5-mini	claude-haiku-4-5-20251001
API Protocol	OpenAI Responses API & Chat Completions v1	Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date	2025-08	2025-10
Knowledge Cutoff	September 2024	July 2025
Architecture	Compact unified reasoning model	Lightweight High-Speed Multimodal Transformer
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM	4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)	Flat rate ($0.25/1M in) across full 400K window	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL	Automatic prefix caching at $0.025/1M (no extra cache-write fee)	$0.1/1M cached read (90% off); 5-min default & 1-hour extended 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 tool + Hosted Code Interpreter & File Search RAG	Native Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning Support	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)	Custom Model Tuning via Amazon Bedrock & Prompt 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)
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	Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated
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

GPT-5 mini vs Claude Haiku 4.5: Jawaban Cepat (FAQ)

Which is more intelligent, GPT-5 mini or Claude Haiku 4.5?

Claude Haiku 4.5 is more intelligent. It scores 54 compared with 46 on the composite Intelligence Index.

Which model is faster?

GPT-5 mini is faster, generating 185 tokens per second compared with 140 tokens per second.

Which model is cheaper to run?

GPT-5 mini is cheaper at $0.27 per 1M tokens blended, compared with $0.77 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude Haiku 4.5 has lower latency, with a time to first token of 0.28s compared with 0.70s.

Which model has a larger context window?

GPT-5 mini has a larger context window, supporting 400K tokens compared with 200K tokens.

Kesimpulan

Baik GPT-5 mini (Sangat cocok untuk efisiensi biaya API maksimal per token dan throughput produksi yang ringan, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Claude Haiku 4.5 (Sangat cocok untuk interaksi real-time dengan latensi sangat rendah dan routing bervolume tinggi, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Claude Haiku 4.5 unggul dalam penalaran dan pemrograman, GPT-5 mini memberikan kecepatan generasi token lebih tinggi, dan GPT-5 mini lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, GPT-5 mini atau Claude Haiku 4.5?+

Dalam indeks kecerdasan gabungan dan benchmark coding, Claude Haiku 4.5 memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API GPT-5 mini vs Claude Haiku 4.5?+

GPT-5 mini mengenakan biaya $0.25 / $2.00 per 1M token input/output, sedangkan Claude Haiku 4.5 sebesar $1.00 / $5.00. Secara keseluruhan, GPT-5 mini lebih hemat biaya.

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

GPT-5 mini mendukung konteks 400K token dibandingkan 200K token pada Claude Haiku 4.5, sementara GPT-5 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)

GPT-5 mini vs Claude Haiku 4.5

Ganti & Bandingkan Model Apa Saja

GPT-5 mini

Claude Haiku 4.5

Siapa Unggul di Mana?

Skor Benchmark Terverifikasi

Latensi & Waktu Respons

Simulator Biaya Token Interaktif

GPT-5 mini · Strengths & Key Advantages

Considerations & Trade-offs

Claude Haiku 4.5 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Spesifikasi Teknis

GPT-5 mini vs Claude Haiku 4.5: Jawaban Cepat (FAQ)

Kesimpulan

Pertanyaan Umum (FAQ)

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