Head-to-Head Model Comparison

Claude 3 Opus vs GPT-4

Benchmarks, API Token Pricing, Context Window & Speed Comparison

تمت المراجعة بواسطة فريق أبحاث GetInfoUsآخر مراجعة: October 2026السياسة التحريرية
مشاركة
Related topics (12)
AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Claude 3 Opus vs GPT-4: Benchmarks, Pricing & Speed Comparison

Claude 3 Opus by Anthropic and GPT-4 by OpenAI represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Claude 3 Opus holds a notable pricing advantage for token ingestion. On output generation, GPT-4 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Claude 3 Opus provides an expanded memory horizon with 200K tokens. In latency-sensitive production environments, GPT-4 leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.

مقارنة مباشرة (VS)

بدّل وقارن بين أي نموذجين

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Profile
Profile
Multi-Model Arena Stack:
5-Model Matrix Workbench
Popular Matchups:
Anthropic

Claude 3 Opus

نموذج رائد متقدم

نموذج Claude 3 Opus المقدم من Anthropic يوفر نافذة سياق تصل إلى 200K رمز، بتكلفة $15 لكل مليون رمز إدخال و$75 لكل مليون رمز إخراج، ومصمم للبرمجة والاستدلال وتطبيقات الأعمال.

Intelligence Index44 / 100
Input Token:

$15.00 / 1M

Output Token:

$75.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

32.2%

OpenAI

GPT-4

نموذج رائد متقدم

نموذج GPT-4 المقدم من OpenAI يوفر نافذة سياق تصل إلى 8K رمز، بتكلفة $30 لكل مليون رمز إدخال و$60 لكل مليون رمز إخراج، ومصمم للبرمجة والاستدلال وتطبيقات الأعمال.

Intelligence Index38 / 100
Input Token:

$30.00 / 1M

Output Token:

$60.00 / 1M

Context Window:

8.2K tokens

SWE-bench Verified:

21%

أهم الفروقات في لمحة

  • Claude 3 Opus is 1.2x cheaper for API usage (input + output tokens combined).
  • Claude 3 Opus has a larger context window (200K vs 8K tokens).
  • GPT-4 is faster at 35 tok/s vs 30 tok/s.
  • Claude 3 Opus leads on SWE-bench coding (32.2% vs 21.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureClaude 3 OpusGPT-4
Intelligence Index
Composite reasoning & knowledge score (0-100)
4438
Provider
AnthropicOpenAI
Input Price
Cost per million input tokens
$15.00 / 1M$30.00 / 1M
Output Price
Cost per million output tokens
$75.00 / 1M$60.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$11.55 / 1M$17.25 / 1M
Context Window
Maximum input + output tokens
200K tokens~300 A4 pages of text8.2K tokens~12 A4 pages of text
Max Output Tokens
Per single request
4K4K
Throughput Speed
Tokens generated per second
30 tok/s35 tok/s
SWE-bench Verified
Real-world software engineering
32.2%21%
GPQA Diamond
Graduate-level reasoning
50.4%35.8%
Cached Input Price
Prompt caching discount per 1M tokens
$1.50 / 1M$7.50 / 1M

من يتفوق في كل مجال؟

At-a-glance decision framework
Coding
Claude 3 Opus
+11.2% SWE-bench lead
Cost
Claude 3 Opus
1.2x cheaper monthly runtime
Speed
GPT-4
+17% faster generation
Context
Claude 3 Opus
200K tokens window

نتائج الاختبارات المعيارية الموثقة

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

Claude 3 OpusGPT-4
SWE-bench Verified (Autonomous Coding)

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

32.2%vs21%
GPQA Diamond (Doctorate-Level Science & Math)

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

50.4%vs35.8%
MMLU-Pro (Multi-task Language Understanding)

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

74%vs68.2%
LMSYS Chatbot Arena Elo

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

1262ptsvs1210pts
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

30 tok/s vs35 tok/s

زمن الاستجابة والسرعة

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 Opus1.20s
GPT-41.20s
Est. End-to-End Response (500 tokens)TTFT + generation time
Claude 3 Opus17.87s
GPT-415.49s

محاكي تكلفة الرموز التفاعلي

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Claude 3 Opus Monthly API Bill
$92.25 / month
$15/1M in · $75/1M out
GPT-4 Monthly API Bill
$110.25 / month
$30/1M in · $60/1M out
Claude 3 Opus saves approximately $18.00 / month (16%) under this workload.1.2x Savings

Claude 3 Opus · Strengths & Key Advantages

  • بنية Frontier Dense Multimodal Transformer متطورة من Anthropic مع سعة سياق تبلغ 200K رمز
  • كفاءة عالية في التكلفة ($15/1M إدخال و$75/1M إخراج) وسرعة استجابة ممتازة
  • أداء قوي في اختبارات البرمجة، الاستدلال المنطقي، ودعم اللغات المتعددة
Considerations & Trade-offs
  • يتطلب إدارة دقيقة لاستهلاك الرموز عند استخدام نافذة السياق الكاملة
  • قد يحتاج إلى ضبط دقيق للتعليمات (Prompt Engineering) في المهام التخصصية المعقدة

GPT-4 · Strengths & Key Advantages

  • بنية Mixture-of-Experts (MoE) متطورة من OpenAI مع سعة سياق تبلغ 8K رمز
  • كفاءة عالية في التكلفة ($30/1M إدخال و$60/1M إخراج) وسرعة استجابة ممتازة
  • أداء قوي في اختبارات البرمجة، الاستدلال المنطقي، ودعم اللغات المتعددة
Considerations & Trade-offs
  • يتطلب إدارة دقيقة لاستهلاك الرموز عند استخدام نافذة السياق الكاملة
  • قد يحتاج إلى ضبط دقيق للتعليمات (Prompt Engineering) في المهام التخصصية المعقدة

Token Use & Task Economics

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

MetricClaude 3 OpusGPT-4
Cost per Task
Estimated USD to finish one task
$0.20$0.20
Output Tokens / Task
Tokens generated per task
24K24K
Reasoning Tokens / Task
Thinking tokens burned per task
0K0K

المواصفات التقنية

Architecture, release timeline, capabilities, and modalities.

FeatureClaude 3 OpusGPT-4
Official API Model ID (SDK)claude-3-opus-20240301gpt-4
API ProtocolAnthropic Messages API + AWS Bedrock + Vertex AIOpenAI Responses API & Chat Completions v1
Release Date2024-032023-03
Knowledge CutoffAugust 2023September 2021
ArchitectureFrontier Dense Multimodal TransformerMixture-of-Experts (MoE)
ParametersConfidentialConfidential (est. 1.8T MoE)
Enterprise Rate Limits (RPM / TPM)4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM10,000 – 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 tokensFlat rate ($30/1M in) across full 8K window
Prompt Cache Policy & TTL$1.5/1M cached read (90% off); 5-min default & 1-hour extended TTLAutomatic prefix caching at $7.5/1M (no extra cache-write fee)
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxNative Web Search Citations + Code Execution Tool + MCP ConnectorsNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportCustom Model Tuning via Amazon Bedrock & Prompt DistillationSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)Text BPE (~4 chars/token)
Quantization & Min GPU VRAMCloud-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 ClassificationAnthropic RSP ASL-2 / ASL-3 Constitutional Safety EvaluatedOpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext
Output Modalitiestexttext

Claude 3 Opus vs GPT-4: إجابات سريعة (FAQ)

Which is more intelligent, Claude 3 Opus or GPT-4?

Claude 3 Opus is more intelligent. It scores 44 compared with 38 on the composite Intelligence Index.

Which model is faster?

GPT-4 is faster, generating 35 tokens per second compared with 30 tokens per second.

Which model is cheaper to run?

Claude 3 Opus is cheaper at $11.55 per 1M tokens blended, compared with $17.25 (7:2:1 cache:input:output ratio).

Which model has a larger context window?

Claude 3 Opus has a larger context window, supporting 200K tokens compared with 8.2K tokens.

الحكم النهائي

Verdict & Model Selection Recommendation: Choose Claude 3 Opus if your priority is Executive strategy briefs, high-end creative writing, philosophical research, and nuanced legal evaluation. Its performance in demanding tasks justifies its operational token cost. Choose GPT-4 if your workflow prioritizes Complex multi-step legal analysis, nuanced philosophical debate, and academic benchmark research. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.

الأسئلة الشائعة (FAQ)

How does Claude 3 Opus compare to GPT-4 in API token pricing and cost per token?+

Claude 3 Opus costs $15.00 per 1M input tokens and $75.00 per 1M output tokens, whereas GPT-4 costs $30.00 input and $60.00 output. Overall, Claude 3 Opus is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.

Which model has a larger context window: Claude 3 Opus or GPT-4?+

Claude 3 Opus supports a context window of 200K tokens (~150k words), while GPT-4 supports 8K tokens (~6k words). Therefore, Claude 3 Opus can process more textual data and document context in a single prompt.

Which AI model is better for software engineering and coding: Claude 3 Opus or GPT-4?+

Claude 3 Opus scores 32.2% on SWE-bench Verified while GPT-4 scores 21%. For autonomous software engineering and multi-file debugging, Claude 3 Opus holds the verified benchmark lead.

What is the difference in reasoning capability and extended thinking between Claude 3 Opus and GPT-4?+

Claude 3 Opus is optimized for low-latency direct generation. In contrast, GPT-4 focuses on standard fast inference.

How does inference speed (tokens per second) compare between Claude 3 Opus and GPT-4?+

Claude 3 Opus generates approximately 30 tokens per second, while GPT-4 delivers 35 tokens per second. In latency-sensitive production environments, GPT-4 provides faster time-to-first-token (TTFT) and higher streaming response velocity.

Can you implement a tiered LLM routing setup combining Claude 3 Opus and GPT-4 to optimize costs?+

Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Claude 3 Opus to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to GPT-4. This tiered routing pattern cuts overall API bills by up to 70%.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.

المصادر الرسمية: GetInfoUs Independent AI Benchmarks & Official API Specs