Head-to-Head Model Comparison

Claude Opus 4 vs Claude Sonnet 4

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Vérifié par l’équipe de recherche de GetInfoUsDernière révision : October 2026Politique éditoriale
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Claude Opus 4 vs Claude Sonnet 4: Benchmarks, Pricing & Speed Comparison

Claude Opus 4 by Anthropic and Claude Sonnet 4 by Anthropic 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 Sonnet 4 holds a notable pricing advantage for token ingestion. On output generation, Claude Sonnet 4 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, both models provide an identical memory horizon with 200K tokens. In latency-sensitive production environments, Claude Sonnet 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.

Comparaison Face-à-Face (VS)

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Anthropic

Claude Opus 4

Raisonneur profond

d'Anthropic de référence heavy raisonnement moteur de moyen-2025, spécialement conçu pour multi-hour recherche, dense codebase migrations, et autonome agent planning.

Intelligence Index61 / 100
Input Token:

$15.00 / 1M

Output Token:

$75.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

72.5%

Anthropic

Claude Sonnet 4

Agent équilibré

d'Anthropic moyen-2025 équilibré agentic modèle de fondation offrant elite ingénierie logicielle, rapide multitour outil interaction, et coût-efficient production operations.

Intelligence Index58 / 100
Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

72.7%

Différences Clés en un Coup d’Œil

  • Claude Sonnet 4 is 5.0x cheaper for API usage (input + output tokens combined).
  • Claude Sonnet 4 is faster at 85 tok/s vs 42 tok/s.
  • Claude Sonnet 4 leads on SWE-bench coding (72.7% vs 72.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaractéristiqueClaude Opus 4Claude Sonnet 4
Intelligence Index
Composite reasoning & knowledge score (0-100)
6158
Provider
AnthropicAnthropic
Input Price
Cost per million input tokens
$15.00 / 1M$3.00 / 1M
Output Price
Cost per million output tokens
$75.00 / 1M$15.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$11.55 / 1M$2.31 / 1M
Context Window
Maximum input + output tokens
200K tokens~300 A4 pages of text200K tokens~300 A4 pages of text
Max Output Tokens
Per single request
32K64K
Throughput Speed
Tokens generated per second
42 tok/s85 tok/s
SWE-bench Verified
Real-world software engineering
72.5%72.7%
GPQA Diamond
Graduate-level reasoning
73.8%71.2%
Cached Input Price
Prompt caching discount per 1M tokens
$1.50 / 1M$0.30 / 1M

Qui gagne où ?

At-a-glance decision framework
Code
Claude Sonnet 4
+0.2% SWE-bench lead
Coût
Claude Sonnet 4
5.0x cheaper monthly runtime
Vitesse
Claude Sonnet 4
+102% faster generation
Contexte
Tied
200K tokens window

Scores de Benchmarks Vérifiés

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

Claude Opus 4Claude Sonnet 4
SWE-bench Verified (Autonomous Coding)

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

72.5%vs72.7%
GPQA Diamond (Doctorate-Level Science & Math)

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

73.8%vs71.2%
MMLU-Pro (Multi-task Language Understanding)

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

86.1%vs84.5%
LMSYS Chatbot Arena Elo

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

1368ptsvs1362pts
Terminal-Bench (Agentic Coding & Terminal Use)

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

43.2%vs42.1%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

42 tok/s vs85 tok/s

Latence et Temps de Réponse

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 Opus 41.80s
Claude Sonnet 40.52s
Est. End-to-End Response (500 tokens)TTFT + generation time
Claude Opus 413.70s
Claude Sonnet 46.40s

Simulateur Interactif de Coût de Tokens

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 Opus 4 Monthly API Bill
$92.25 / month
$15/1M in · $75/1M out
Claude Sonnet 4 Monthly API Bill
$18.45 / month
$3/1M in · $15/1M out
Claude Sonnet 4 saves approximately $73.80 / month (80%) under this workload.5.0x Savings

Claude Opus 4 · Strengths & Key Advantages

  • Exquisite profond conceptual raisonnement et multi-étapes theorem proving
  • haut de gamme-palier autonome TerminalBench score (43.2) pour command-line agent tâches
  • Remarkable resistance à injection d'invite et hallucination dans élevé-stakes flux de travail
Considerations & Trade-offs
  • élevé premium tarification ($15 dans / $75 out par 1M tokens) restricts bulk déploiement
  • Substantially supérieur latence et inférieur génération vitesse que Sonnet 4

Claude Sonnet 4 · Strengths & Key Advantages

  • Outstanding SWE-bench Verified codage score (72.7%) à standard d'entreprise tarification
  • Integrated hybrid raisonnement mode allowing scalable chaîne de pensée exploration
  • 90% prompt caching discount ($0.30/M) optimizing multitour agent boucles
Considerations & Trade-offs
  • fenêtre de contexte capped à 200K tokens, trailing competitor 1M+ windows
  • Slightly inférieur sommet analytical profondeur sur de pointe scientifique problems que Opus 4

Token Use & Task Economics

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

MetricClaude Opus 4Claude Sonnet 4
Cost per Task
Estimated USD to finish one task
$16.46$3.29
Output Tokens / Task
Tokens generated per task
72K72K
Reasoning Tokens / Task
Thinking tokens burned per task
37K37K

Spécifications Techniques

Architecture, release timeline, capabilities, and modalities.

CaractéristiqueClaude Opus 4Claude Sonnet 4
Official API Model ID (SDK)claude-opus-4-20250501claude-sonnet-4-20250501
API ProtocolAnthropic Messages API + AWS Bedrock + Vertex AIAnthropic Messages API + AWS Bedrock + Vertex AI
Release Date2025-052025-05
Knowledge CutoffMarch 2025March 2025
ArchitectureDense Frontier Reasoning TransformerHybrid Multimodal Reasoning Transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Standard rate up to 200K tokens; 2x input/output tier above 200K tokensStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL$1.5/1M cached read (90% off); 5-min default & 1-hour extended TTL$0.3/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
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 Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportCustom Model Tuning via Amazon Bedrock & Prompt DistillationCustom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token BillingText 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 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 EvaluatedAnthropic 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 TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision
Output Modalitiestexttext

Claude Opus 4 vs Claude Sonnet 4: Réponses Rapides (FAQ)

Which is more intelligent, Claude Opus 4 or Claude Sonnet 4?

Claude Opus 4 is more intelligent. It scores 61 compared with 58 on the composite Intelligence Index.

Which model is faster?

Claude Sonnet 4 is faster, generating 85 tokens per second compared with 42 tokens per second.

Which model is cheaper to run?

Claude Sonnet 4 is cheaper at $2.31 per 1M tokens blended, compared with $11.55 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude Sonnet 4 has lower latency, with a time to first token of 0.52s compared with 1.80s.

Verdict

Verdict & Model Selection Recommendation: Choose Claude Opus 4 if your priority is Deep mathematical analysis, mission-critical autonomous planning, and enterprise code audits. Its performance in demanding tasks justifies its operational token cost. Choose Claude Sonnet 4 if your workflow prioritizes Full-stack software engineering agents, CI/CD pipeline automation, and enterprise production applications. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.

Questions fréquentes

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

Claude Opus 4 costs $15.00 per 1M input tokens and $75.00 per 1M output tokens, whereas Claude Sonnet 4 costs $3.00 input and $15.00 output. Overall, Claude Sonnet 4 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 Opus 4 or Claude Sonnet 4?+

Both Claude Opus 4 and Claude Sonnet 4 offer an identical context window of 200K tokens (~150k words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.

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

Claude Opus 4 scores 72.5% on SWE-bench Verified while Claude Sonnet 4 scores 72.7%. For autonomous software engineering and multi-file debugging, Claude Sonnet 4 holds the verified benchmark lead.

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

Claude Opus 4 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Claude Sonnet 4 provides chain-of-thought reasoning depth for complex math and science.

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

Claude Opus 4 generates approximately 42 tokens per second, while Claude Sonnet 4 delivers 85 tokens per second. In latency-sensitive production environments, Claude Sonnet 4 provides faster time-to-first-token (TTFT) and higher streaming response velocity.

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

Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Claude Sonnet 4 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Claude Opus 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.

Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.

Sources: GetInfoUs Independent AI Benchmarks & Official API Specs