Head-to-Head Model Comparison

Claude 3.7 Sonnet vs GPT-4o

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs araştırma ekibi tarafından incelendiSon inceleme: October 2026Yayın ilkeleri

Paylaş

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Claude 3.7 SonnetProfile

GPT-4oProfile

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Popular Matchups:Claude 3.7 vs GPT-4o

Anthropic

Claude 3.7 Sonnet

Kodlama ve Yazılım Lideri

Anthropic tarafından geliştirilen Claude 3.7 Sonnet; otonom yazılım mühendisliği, çoklu dosya kod düzenleme ve ileri düzey hata ayıklama için tasarlanmış olup 200K bağlam penceresi, 72 token/sn hız, 48/100 zeka indeksi ve 1M token başına $3

Intelligence Index48 / 100

Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

70.3%

OpenAI

GPT-4o

Yerel Ses ve Konuşma Modeli

OpenAI tarafından geliştirilen GPT-4o; doğal ses sentezi, gerçek zamanlı ses işleme ve konuşma metne dönüştürme için tasarlanmış olup 128K bağlam penceresi, 105 token/sn hız, 41/100 zeka indeksi ve 1M token başına $2.5/$10 fiyatlandırma sun

Intelligence Index41 / 100

Input Token:

$2.50 / 1M

Output Token:

$10.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

38.8%

Bir Bakışta Temel Farklar

GPT-4o is 1.3x cheaper for API usage (input + output tokens combined).
Claude 3.7 Sonnet has a larger context window (200K vs 128K tokens).
GPT-4o is faster at 105 tok/s vs 72 tok/s.
Claude 3.7 Sonnet leads on SWE-bench coding (70.3% vs 38.8%).

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

Feature	Claude 3.7 Sonnet	GPT-4o
Intelligence Index Composite reasoning & knowledge score (0-100)	48	41
Provider	Anthropic	OpenAI
Input Price Cost per million input tokens	$3.00 / 1M	$2.50 / 1M
Output Price Cost per million output tokens	$15.00 / 1M	$10.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$2.31 / 1M	$2.38 / 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	64K	16K
Throughput Speed Tokens generated per second	72 tok/s	105 tok/s
SWE-bench Verified Real-world software engineering	70.3%	38.8%
GPQA Diamond Graduate-level reasoning	65%	53.6%
Cached Input Price Prompt caching discount per 1M tokens	$0.30 / 1M	$1.25 / 1M

Hangi Alanda Kim Kazanıyor?

At-a-glance decision framework

Coding

Claude 3.7 Sonnet

+31.5% SWE-bench lead

Cost

GPT-4o

1.3x cheaper monthly runtime

Speed

GPT-4o

+46% faster generation

Context

Claude 3.7 Sonnet

200K tokens window

Doğrulanmış Benchmark Puanları

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

Claude 3.7 SonnetGPT-4o

SWE-bench Verified (Autonomous Coding)

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

70.3%vs38.8%

GPQA Diamond (Doctorate-Level Science & Math)

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

65%vs53.6%

MMLU-Pro (Multi-task Language Understanding)

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

78.2%vs72.6%

LMSYS Chatbot Arena Elo

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

1335ptsvs1286pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

8.9%vs4.1%

Terminal-Bench (Agentic Coding & Terminal Use)

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

35.2%vs18.5%

SciCode (Scientific Computing)

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

40.1%vs27.3%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

64.8%vs43.9%

AIME (Advanced Math Competition)

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

61.3%vs29.7%

Long-Context Reasoning

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

71.5%vs58.2%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

72 tok/s vs105 tok/s

Gecikme Süresi ve Yanıt Hızı

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 3.7 Sonnet0.52s

GPT-4o0.41s

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

Claude 3.7 Sonnet7.46s

GPT-4o5.17s

Gerçek Zamanlı Token Maliyet Simülatörü

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 3.7 Sonnet Monthly API Bill

$18.45 / month

$3/1M in · $15/1M out

GPT-4o Monthly API Bill

$14.63 / month

$2.5/1M in · $10/1M out

GPT-4o saves approximately $3.82 / month (21%) under this workload.1.3x Savings

Claude 3.7 Sonnet · Strengths & Key Advantages

200K bağlam penceresi ve yanıt başına maksimum 64K çıktı tokenı kapasitesi (SWE-bench Verified 70.3% · GPQA Diamond 65%)
Sadece 520 ms ilk token gecikmesi (TTFT) ile saniyede 72 token yüksek üretim hızı
İstem önbellekleme (Prompt Caching), araç çağırma ve yapılandırılmış JSON çıktısını destekleyen rekabetçi API ekonomisi (1M token başına $3/$15 fiyatlandırma)

Considerations & Trade-offs

Kapalı ağırlıklı bulut modelidir; çevrimdışı yerel sunuculara indirilerek çalıştırılamaz
Yüksek hacimli üretim trafiğinde maliyetleri optimize etmek için Prompt Caching ve Batch API kullanımı önerilir

GPT-4o · Strengths & Key Advantages

128K bağlam penceresi ve yanıt başına maksimum 16K çıktı tokenı kapasitesi (SWE-bench Verified 38.8% · GPQA Diamond 53.6%)
Sadece 410 ms ilk token gecikmesi (TTFT) ile saniyede 105 token yüksek üretim hızı
İstem önbellekleme (Prompt Caching), araç çağırma ve yapılandırılmış JSON çıktısını destekleyen rekabetçi API ekonomisi (1M token başına $2.5/$10 fiyatlandırma)

Considerations & Trade-offs

Kapalı ağırlıklı bulut modelidir; çevrimdışı yerel sunuculara indirilerek çalıştırılamaz
Yüksek hacimli üretim trafiğinde maliyetleri optimize etmek için Prompt Caching ve Batch API kullanımı önerilir

Token Use & Task Economics

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

Metric	Claude 3.7 Sonnet	GPT-4o
Cost per Task Estimated USD to finish one task	$1.42	$0.68
Output Tokens / Task Tokens generated per task	41K	24K
Reasoning Tokens / Task Thinking tokens burned per task	22K	0K

Teknik Özellikler

Architecture, release timeline, capabilities, and modalities.

Feature	Claude 3.7 Sonnet	GPT-4o
Official API Model ID (SDK)	claude-3-7-sonnet-20250201	gpt-4o
API Protocol	Anthropic Messages API + AWS Bedrock + Vertex AI	OpenAI Responses API & Chat Completions v1
Release Date	2025-02	2024-05
Knowledge Cutoff	November 2024	October 2023
Architecture	Hybrid Reasoning MoE	Omni-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 ($2.5/1M in) across full 128K window
Prompt Cache Policy & TTL	$0.3/1M cached read (90% off); 5-min default & 1-hour extended TTL	Automatic prefix caching at $1.25/1M (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) · Audio (~25–32 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	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, audio
Output Modalities	text	text, audio

Claude 3.7 Sonnet vs GPT-4o: Hızlı Yanıtlar (SSS)

Which is more intelligent, Claude 3.7 Sonnet or GPT-4o?

Claude 3.7 Sonnet is more intelligent. It scores 48 compared with 41 on the composite Intelligence Index.

Which model is faster?

GPT-4o is faster, generating 105 tokens per second compared with 72 tokens per second.

Which model is cheaper to run?

Claude 3.7 Sonnet is cheaper at $2.31 per 1M tokens blended, compared with $2.38 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-4o has lower latency, with a time to first token of 0.41s compared with 0.52s.

Which model has a larger context window?

Claude 3.7 Sonnet has a larger context window, supporting 200K tokens compared with 128K tokens.

Sonuç

Hem Claude 3.7 Sonnet (otonom yazılım mühendisliği, çoklu dosya kod düzenleme ve ileri düzey hata ayıklama, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) hem de GPT-4o (doğal ses sentezi, gerçek zamanlı ses işleme ve konuşma metne dönüştürme, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) güçlü üretim seçenekleridir: Claude 3.7 Sonnet karmaşık akıl yürütme ve kodlama testlerinde öne çıkarken, GPT-4o daha yüksek üretim hızı sağlar; Claude 3.7 Sonnet ise yüksek hacimli API kullanımlarında daha ekonomiktir.

Sıkça Sorulan Sorular (SSS)

Kodlama ve akıl yürütme için Claude 3.7 Sonnet mi yoksa GPT-4o mi daha iyi?+

Bileşik zeka endeksi ve yazılım testlerinde Claude 3.7 Sonnet önde yer alıyor. Detaylı karşılaştırma için yukarıdaki SWE-bench ve GPQA tablolarına göz atabilirsiniz.

Claude 3.7 Sonnet ve GPT-4o API fiyatları nasıl karşılaştırılır?+

Claude 3.7 Sonnet 1M giriş/çıkış tokeni başına $3.00 / $15.00 ücretlendirilirken, GPT-4o $2.50 / $10.00 seviyesindedir. Karma maliyette Claude 3.7 Sonnet daha avantajlıdır.

Hangi modelin bağlam penceresi daha geniş ve hızı daha yüksek?+

Claude 3.7 Sonnet 200K token bağlam penceresi sunarken GPT-4o 128K token kapasiteye sahiptir. Saniyedeki token üretim hızında ise GPT-4o öndedir.

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 3.7 Sonnet vs GPT-4o

İstediğiniz Modelleri Seçin ve Karşılaştırın

Claude 3.7 Sonnet

GPT-4o

Hangi Alanda Kim Kazanıyor?

Doğrulanmış Benchmark Puanları

Gecikme Süresi ve Yanıt Hızı

Gerçek Zamanlı Token Maliyet Simülatörü

Claude 3.7 Sonnet · Strengths & Key Advantages

Considerations & Trade-offs

GPT-4o · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Teknik Özellikler

Claude 3.7 Sonnet vs GPT-4o: Hızlı Yanıtlar (SSS)

Sonuç

Sıkça Sorulan Sorular (SSS)

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