Head-to-Head Model Comparison

OpenAI o1 vs Claude 3.7 Sonnet

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs araştırma ekibi tarafından incelendiSon inceleme: October 2026Yayın ilkeleri

Paylaş

İstediğiniz Modelleri Seçin ve Karşılaştırın

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OpenAI o1Profile

Claude 3.7 SonnetProfile

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OpenAI

OpenAI o1

Derin Akıl Yürütme Motoru

OpenAI tarafından geliştirilen OpenAI o1; derin mantıksal akıl yürütme, ileri matematik ve çok adımlı bilimsel analiz için tasarlanmış olup 200K bağlam penceresi, 60 token/sn hız, 55/100 zeka indeksi ve 1M token başına $15/$60 fiyatlandırma

Intelligence Index55 / 100

Input Token:

$15.00 / 1M

Output Token:

$60.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

48.9%

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%

Bir Bakışta Temel Farklar

Claude 3.7 Sonnet is 4.8x cheaper for API usage (input + output tokens combined).
Claude 3.7 Sonnet is faster at 72 tok/s vs 60 tok/s.
Claude 3.7 Sonnet leads on SWE-bench coding (70.3% vs 48.9%).

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

Feature	OpenAI o1	Claude 3.7 Sonnet
Intelligence Index Composite reasoning & knowledge score (0-100)	55	48
Provider	OpenAI	Anthropic
Input Price Cost per million input tokens	$15.00 / 1M	$3.00 / 1M
Output Price Cost per million output tokens	$60.00 / 1M	$15.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$14.25 / 1M	$2.31 / 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	64K
Throughput Speed Tokens generated per second	60 tok/s	72 tok/s
SWE-bench Verified Real-world software engineering	48.9%	70.3%
GPQA Diamond Graduate-level reasoning	77.3%	65%
Cached Input Price Prompt caching discount per 1M tokens	$7.50 / 1M	$0.30 / 1M

Hangi Alanda Kim Kazanıyor?

At-a-glance decision framework

Coding

Claude 3.7 Sonnet

+21.4% SWE-bench lead

Cost

Claude 3.7 Sonnet

4.8x cheaper monthly runtime

Speed

Claude 3.7 Sonnet

+20% faster generation

Context

Tied

200K tokens window

Doğrulanmış Benchmark Puanları

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

OpenAI o1Claude 3.7 Sonnet

SWE-bench Verified (Autonomous Coding)

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

48.9%vs70.3%

GPQA Diamond (Doctorate-Level Science & Math)

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

77.3%vs65%

MMLU-Pro (Multi-task Language Understanding)

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

89.6%vs78.2%

LMSYS Chatbot Arena Elo

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

1355ptsvs1335pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

10.8%vs8.9%

Terminal-Bench (Agentic Coding & Terminal Use)

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

43.5%vs35.2%

SciCode (Scientific Computing)

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

44.2%vs40.1%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

72.1%vs64.8%

AIME (Advanced Math Competition)

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

83.3%vs61.3%

Long-Context Reasoning

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

75%vs71.5%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

60 tok/s vs72 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

OpenAI o13.20s

Claude 3.7 Sonnet0.52s

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

OpenAI o111.53s

Claude 3.7 Sonnet7.46s

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)

OpenAI o1 Monthly API Bill

$87.75 / month

$15/1M in · $60/1M out

Claude 3.7 Sonnet Monthly API Bill

$18.45 / month

$3/1M in · $15/1M out

Claude 3.7 Sonnet saves approximately $69.30 / month (79%) under this workload.4.8x Savings

OpenAI o1 · Strengths & Key Advantages

200K bağlam penceresi ve yanıt başına maksimum 100K çıktı tokenı kapasitesi (SWE-bench Verified 48.9% · GPQA Diamond 77.3%)
Sadece 3200 ms ilk token gecikmesi (TTFT) ile saniyede 60 token yüksek üretim hızı
İstem önbellekleme (Prompt Caching), araç çağırma ve yapılandırılmış JSON çıktısını destekleyen rekabetçi API ekonomisi (1M token başına $15/$60 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

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

Token Use & Task Economics

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

Metric	OpenAI o1	Claude 3.7 Sonnet
Cost per Task Estimated USD to finish one task	$0.20	$1.42
Output Tokens / Task Tokens generated per task	24K	41K
Reasoning Tokens / Task Thinking tokens burned per task	15K	22K

Teknik Özellikler

Architecture, release timeline, capabilities, and modalities.

Feature	OpenAI o1	Claude 3.7 Sonnet
Official API Model ID (SDK)	o1	claude-3-7-sonnet-20250201
API Protocol	OpenAI Responses API & Chat Completions v1	Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date	2024-12	2025-02
Knowledge Cutoff	October 2023	November 2024
Architecture	Chain-of-Thought Reasoning Foundation	Hybrid Reasoning MoE
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 ($15/1M in) across full 200K window	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL	Automatic prefix caching at $7.5/1M (no extra cache-write fee)	$0.3/1M 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

OpenAI o1 vs Claude 3.7 Sonnet: Hızlı Yanıtlar (SSS)

Which is more intelligent, OpenAI o1 or Claude 3.7 Sonnet?

OpenAI o1 is more intelligent. It scores 55 compared with 48 on the composite Intelligence Index.

Which model is faster?

Claude 3.7 Sonnet is faster, generating 72 tokens per second compared with 60 tokens per second.

Which model is cheaper to run?

Claude 3.7 Sonnet is cheaper at $2.31 per 1M tokens blended, compared with $14.25 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude 3.7 Sonnet has lower latency, with a time to first token of 0.52s compared with 3.20s.

Sonuç

Hem OpenAI o1 (derin mantıksal akıl yürütme, ileri matematik ve çok adımlı bilimsel analiz, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) hem de 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.) güçlü üretim seçenekleridir: OpenAI o1 karmaşık akıl yürütme ve kodlama testlerinde öne çıkarken, Claude 3.7 Sonnet 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 OpenAI o1 mi yoksa Claude 3.7 Sonnet mi daha iyi?+

Bileşik zeka endeksi ve yazılım testlerinde OpenAI o1 önde yer alıyor. Detaylı karşılaştırma için yukarıdaki SWE-bench ve GPQA tablolarına göz atabilirsiniz.

OpenAI o1 ve Claude 3.7 Sonnet API fiyatları nasıl karşılaştırılır?+

OpenAI o1 1M giriş/çıkış tokeni başına $15.00 / $60.00 ücretlendirilirken, Claude 3.7 Sonnet $3.00 / $15.00 seviyesindedir. Karma maliyette Claude 3.7 Sonnet daha avantajlıdır.

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

OpenAI o1 200K token bağlam penceresi sunarken Claude 3.7 Sonnet 200K token kapasiteye sahiptir. Saniyedeki token üretim hızında ise Claude 3.7 Sonnet 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)

OpenAI o1 vs Claude 3.7 Sonnet

İstediğiniz Modelleri Seçin ve Karşılaştırın

OpenAI o1

Claude 3.7 Sonnet

Hangi Alanda Kim Kazanıyor?

Doğrulanmış Benchmark Puanları

Gecikme Süresi ve Yanıt Hızı

Gerçek Zamanlı Token Maliyet Simülatörü

OpenAI o1 · Strengths & Key Advantages

Considerations & Trade-offs

Claude 3.7 Sonnet · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Teknik Özellikler

OpenAI o1 vs Claude 3.7 Sonnet: Hızlı Yanıtlar (SSS)

Sonuç

Sıkça Sorulan Sorular (SSS)

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