Head-to-Head Model Comparison

Claude Opus 4.6 vs Claude Sonnet 4.6

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial
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Related topics (12)
AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Claude Opus 4.6 vs Claude Sonnet 4.6: Benchmarks, Pricing & Speed Comparison

Claude Opus 4.6 by Anthropic and Claude Sonnet 4.6 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 4.6 holds a notable pricing advantage for token ingestion. On output generation, Claude Sonnet 4.6 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 1,000K tokens. In latency-sensitive production environments, Claude Sonnet 4.6 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.

Comparación Directa (VS)

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Anthropic

Claude Opus 4.6

Razonamiento experto

de Anthropic early-2026 de frontera breakthrough expanding el Opus razonamiento family un un masivo 1-millones-token ventana de contexto con profundo multipaso planning.

Intelligence Index65 / 100
Input Token:

$5.00 / 1M

Output Token:

$25.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

78.4%

Anthropic

Claude Sonnet 4.6

Caballo de batalla de producción

el daily driver empresarial champion de early 2026, pairing un 1-millones-token ventana de contexto con rápido rendimiento y rock-solid llamada un herramientas.

Intelligence Index60 / 100
Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

76.1%

Diferencias Clave de un Vistazo

  • Claude Sonnet 4.6 is 1.7x cheaper for API usage (input + output tokens combined).
  • Claude Sonnet 4.6 is faster at 92 tok/s vs 55 tok/s.
  • Claude Opus 4.6 leads on SWE-bench coding (78.4% vs 76.1%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaracterísticaClaude Opus 4.6Claude Sonnet 4.6
Intelligence Index
Composite reasoning & knowledge score (0-100)
6560
Provider
AnthropicAnthropic
Input Price
Cost per million input tokens
$5.00 / 1M$3.00 / 1M
Output Price
Cost per million output tokens
$25.00 / 1M$15.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$3.85 / 1M$2.31 / 1M
Context Window
Maximum input + output tokens
1M tokens~1,500 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
128K128K
Throughput Speed
Tokens generated per second
55 tok/s92 tok/s
SWE-bench Verified
Real-world software engineering
78.4%76.1%
GPQA Diamond
Graduate-level reasoning
76.5%74%
Cached Input Price
Prompt caching discount per 1M tokens
$0.50 / 1M$0.30 / 1M

¿Quién gana en cada área?

At-a-glance decision framework
Código
Claude Opus 4.6
+2.3% SWE-bench lead
Costo
Claude Sonnet 4.6
1.7x cheaper monthly runtime
Velocidad
Claude Sonnet 4.6
+67% faster generation
Contexto
Tied
1M tokens window

Puntuaciones de Benchmarks Verificadas

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

Claude Opus 4.6Claude Sonnet 4.6
SWE-bench Verified (Autonomous Coding)

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

78.4%vs76.1%
GPQA Diamond (Doctorate-Level Science & Math)

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

76.5%vs74%
MMLU-Pro (Multi-task Language Understanding)

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

88.2%vs86.7%
LMSYS Chatbot Arena Elo

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

1395ptsvs1380pts
Terminal-Bench (Agentic Coding & Terminal Use)

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

51.4%vs47.8%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

55 tok/s vs92 tok/s

Latencia y Tiempo de Respuesta

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 4.61.90s
Claude Sonnet 4.60.65s
Est. End-to-End Response (500 tokens)TTFT + generation time
Claude Opus 4.610.99s
Claude Sonnet 4.66.08s

Simulador Interactivo de Costos 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 4.6 Monthly API Bill
$30.75 / month
$5/1M in · $25/1M out
Claude Sonnet 4.6 Monthly API Bill
$18.45 / month
$3/1M in · $15/1M out
Claude Sonnet 4.6 saves approximately $12.30 / month (40%) under this workload.1.7x Savings

Claude Opus 4.6 · Strengths & Key Advantages

  • completo 1,000,000 token ventana de contexto coupled con 128K max salida generación
  • Major precio reduction de $15/$75 down un $5/$25 por millones tokens
  • Flawless multidocumento síntesis y de largo alcance ingeniería de software
Considerations & Trade-offs
  • extendido pensamiento cycles introduce notable initial latencia (up un ~2s TTFT)
  • salida precios remains sustancial para mass consumidor query volumen

Claude Sonnet 4.6 · Strengths & Key Advantages

  • equilibrado $3/$15 economics combined con un completo 1M token ventana de contexto
  • excepcional 92 tokens/sec rendimiento para interactivo desarrollador environments
  • Precise estructurado JSON salida cumplimiento y uso de computadora agente ejecución
Considerations & Trade-offs
  • Slightly behind Opus 4.6 en highly abstract matemático investigación tareas
  • requiere careful prompt caching configuration un optimize 1M token ingesta costos

Token Use & Task Economics

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

MetricClaude Opus 4.6Claude Sonnet 4.6
Cost per Task
Estimated USD to finish one task
$5.49$3.29
Output Tokens / Task
Tokens generated per task
72K72K
Reasoning Tokens / Task
Thinking tokens burned per task
37K37K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

CaracterísticaClaude Opus 4.6Claude Sonnet 4.6
Official API Model ID (SDK)claude-opus-4-6-20260201claude-sonnet-4-6-20260201
API ProtocolAnthropic Messages API + AWS Bedrock + Vertex AIAnthropic Messages API + AWS Bedrock + Vertex AI
Release Date2026-022026-02
Knowledge CutoffDecember 2025December 2025
ArchitectureMegacontext Frontier Reasoning TransformerHigh-Throughput Multimodal Agent Transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 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$0.5/1M 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 4.6 vs Claude Sonnet 4.6: Respuestas Rápidas (FAQ)

Which is more intelligent, Claude Opus 4.6 or Claude Sonnet 4.6?

Claude Opus 4.6 is more intelligent. It scores 65 compared with 60 on the composite Intelligence Index.

Which model is faster?

Claude Sonnet 4.6 is faster, generating 92 tokens per second compared with 55 tokens per second.

Which model is cheaper to run?

Claude Sonnet 4.6 is cheaper at $2.31 per 1M tokens blended, compared with $3.85 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude Sonnet 4.6 has lower latency, with a time to first token of 0.65s compared with 1.90s.

Veredicto

Verdict & Model Selection Recommendation: Choose Claude Opus 4.6 if your priority is Large repository code refactoring, full-book technical translation, and enterprise legal discovery. Its performance in demanding tasks justifies its operational token cost. Choose Claude Sonnet 4.6 if your workflow prioritizes Production coding copilots, full-repo code search, customer agent workflows, and automated workflows. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.

Preguntas frecuentes

How does Claude Opus 4.6 compare to Claude Sonnet 4.6 in API token pricing and cost per token?+

Claude Opus 4.6 costs $5.00 per 1M input tokens and $25.00 per 1M output tokens, whereas Claude Sonnet 4.6 costs $3.00 input and $15.00 output. Overall, Claude Sonnet 4.6 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 4.6 or Claude Sonnet 4.6?+

Both Claude Opus 4.6 and Claude Sonnet 4.6 offer an identical context window of 1,000K tokens (~750k 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 4.6 or Claude Sonnet 4.6?+

Claude Opus 4.6 scores 78.4% on SWE-bench Verified while Claude Sonnet 4.6 scores 76.1%. For autonomous software engineering and multi-file debugging, Claude Opus 4.6 holds the verified benchmark lead.

What is the difference in reasoning capability and extended thinking between Claude Opus 4.6 and Claude Sonnet 4.6?+

Claude Opus 4.6 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Claude Sonnet 4.6 provides chain-of-thought reasoning depth for complex math and science.

How does inference speed (tokens per second) compare between Claude Opus 4.6 and Claude Sonnet 4.6?+

Claude Opus 4.6 generates approximately 55 tokens per second, while Claude Sonnet 4.6 delivers 92 tokens per second. In latency-sensitive production environments, Claude Sonnet 4.6 provides faster time-to-first-token (TTFT) and higher streaming response velocity.

Can you implement a tiered LLM routing setup combining Claude Opus 4.6 and Claude Sonnet 4.6 to optimize costs?+

Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Claude Sonnet 4.6 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Claude Opus 4.6. 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.

Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.

Fuentes: GetInfoUs Independent AI Benchmarks & Official API Specs