Head-to-Head Model Comparison

Claude Sonnet 4 vs o1-pro

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Claude Sonnet 4 vs o1-pro: Benchmarks, Pricing & Speed Comparison

Claude Sonnet 4 by Anthropic and o1-pro 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 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.

Comparación Directa (VS)

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Anthropic

Claude Sonnet 4

Agente equilibrado

de Anthropic medio-2025 equilibrado agentic modelo fundacional que ofrece elite ingeniería de software, rápido multiturno herramienta interaction, y costo-efficient producción operations.

Intelligence Index58 / 100
Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

72.7%

OpenAI

o1-pro

Razonador de cómputo máximo

un compute-heavy o1 nivel que spends far más pensamiento tiempo en difficult análisis y planning.

Intelligence Index57 / 100
Input Token:

$150.00 / 1M

Output Token:

$600.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

51.5%

Diferencias Clave de un Vistazo

  • Claude Sonnet 4 is 44.5x cheaper for API usage (input + output tokens combined).
  • Claude Sonnet 4 is faster at 85 tok/s vs 22 tok/s.
  • Claude Sonnet 4 leads on SWE-bench coding (72.7% vs 51.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaracterísticaClaude Sonnet 4o1-pro
Intelligence Index
Composite reasoning & knowledge score (0-100)
5857
Provider
AnthropicOpenAI
Input Price
Cost per million input tokens
$3.00 / 1M$150.00 / 1M
Output Price
Cost per million output tokens
$15.00 / 1M$600.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$2.31 / 1M$116.25 / 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
64K100K
Throughput Speed
Tokens generated per second
85 tok/s22 tok/s
SWE-bench Verified
Real-world software engineering
72.7%51.5%
GPQA Diamond
Graduate-level reasoning
71.2%79%
Cached Input Price
Prompt caching discount per 1M tokens
$0.30 / 1M$37.50 / 1M

¿Quién gana en cada área?

At-a-glance decision framework
Código
Claude Sonnet 4
+21.2% SWE-bench lead
Costo
Claude Sonnet 4
44.5x cheaper monthly runtime
Velocidad
Claude Sonnet 4
+286% faster generation
Contexto
Tied
200K tokens window

Puntuaciones de Benchmarks Verificadas

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

Claude Sonnet 4o1-pro
SWE-bench Verified (Autonomous Coding)

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

72.7%vs51.5%
GPQA Diamond (Doctorate-Level Science & Math)

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

71.2%vs79%
MMLU-Pro (Multi-task Language Understanding)

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

84.5%vs90.5%
LMSYS Chatbot Arena Elo

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

1362ptsvs1362pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs11.6%
Terminal-Bench (Agentic Coding & Terminal Use)

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

42.1%vs46.5%
SciCode (Scientific Computing)

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

N/Avs46%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs74%
AIME (Advanced Math Competition)

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

N/Avs88%
Long-Context Reasoning

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

N/Avs77.5%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

85 tok/s vs22 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 Sonnet 40.52s
o1-pro4.20s
Est. End-to-End Response (500 tokens)TTFT + generation time
Claude Sonnet 46.40s
o1-pro26.93s

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 Sonnet 4 Monthly API Bill
$18.45 / month
$3/1M in · $15/1M out
o1-pro Monthly API Bill
$821.25 / month
$150/1M in · $600/1M out
Claude Sonnet 4 saves approximately $802.80 / month (98%) under this workload.44.5x Savings

Claude Sonnet 4 · Strengths & Key Advantages

  • Outstanding SWE-bench Verified codificación score (72.7%) un estándar empresarial precios
  • Integrated hybrid razonamiento modo allowing scalable cadena de pensamiento exploration
  • 90% prompt caching discount ($0.30/M) optimizing multiturno agente bucles
Considerations & Trade-offs
  • ventana de contexto capped un 200K tokens, trailing competitor 1M+ windows
  • Slightly menor pico analytical profundidad en de frontera científico problems que Opus 4

o1-pro · Strengths & Key Advantages

  • más alto precisión del o1 family en hard analytical problems
  • muy confiable en largo, multipaso planning tareas
  • Handles investigación-grade analytical plans sin supervision
Considerations & Trade-offs
  • Extremely expensive un $150 / $600 por 1M tokens
  • Lento: las respuestas pueden tardar minutos
  • o3-pro y GPT-5 Pro now deliver mejor results para menos

Token Use & Task Economics

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

MetricClaude Sonnet 4o1-pro
Cost per Task
Estimated USD to finish one task
$3.29$94.20
Output Tokens / Task
Tokens generated per task
72K62K
Reasoning Tokens / Task
Thinking tokens burned per task
37K45K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

CaracterísticaClaude Sonnet 4o1-pro
Official API Model ID (SDK)claude-sonnet-4-20250501o1-pro
API ProtocolAnthropic Messages API + AWS Bedrock + Vertex AIOpenAI Responses API & Chat Completions v1
Release Date2025-052025-03
Knowledge CutoffMarch 2025October 2023
ArchitectureHybrid Multimodal Reasoning TransformerHigh-compute reasoning transformer
ParametersConfidentialConfidential
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 ($150/1M in) across full 200K window
Prompt Cache Policy & TTL$0.3/1M cached read (90% off); 5-min default & 1-hour extended TTLAutomatic prefix caching at $37.5/1M (no extra cache-write fee)
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 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) · 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 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, vision
Output Modalitiestexttext

Claude Sonnet 4 vs o1-pro: Respuestas Rápidas (FAQ)

Which is more intelligent, Claude Sonnet 4 or o1-pro?

Claude Sonnet 4 is more intelligent. It scores 58 compared with 57 on the composite Intelligence Index.

Which model is faster?

Claude Sonnet 4 is faster, generating 85 tokens per second compared with 22 tokens per second.

Which model is cheaper to run?

Claude Sonnet 4 is cheaper at $2.31 per 1M tokens blended, compared with $116.25 (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 4.20s.

Veredicto

Verdict & Model Selection Recommendation: Choose Claude Sonnet 4 if your priority is Full-stack software engineering agents, CI/CD pipeline automation, and enterprise production applications. Its performance in demanding tasks justifies its operational token cost. Choose o1-pro if your workflow prioritizes Rare, high-stakes analytical problems where cost is irrelevant. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.

Preguntas frecuentes

How does Claude Sonnet 4 compare to o1-pro in API token pricing and cost per token?+

Claude Sonnet 4 costs $3.00 per 1M input tokens and $15.00 per 1M output tokens, whereas o1-pro costs $150.00 input and $600.00 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 Sonnet 4 or o1-pro?+

Both Claude Sonnet 4 and o1-pro 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 Sonnet 4 or o1-pro?+

Claude Sonnet 4 scores 72.7% on SWE-bench Verified while o1-pro scores 51.5%. 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 Sonnet 4 and o1-pro?+

Claude Sonnet 4 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, o1-pro provides chain-of-thought reasoning depth for complex math and science.

How does inference speed (tokens per second) compare between Claude Sonnet 4 and o1-pro?+

Claude Sonnet 4 generates approximately 85 tokens per second, while o1-pro delivers 22 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 Sonnet 4 and o1-pro 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 o1-pro. 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