Head-to-Head Model Comparison

GPT-Realtime-2.1 vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial
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Compare GPT-Realtime-2.1 by OpenAI against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

Comparación Directa (VS)

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OpenAI

GPT-Realtime-2.1

Agente de voz

un en tiempo real voz-un-voz modelo con configurable razonamiento, uso de herramientas y sólido voz-agente behaviour.

Intelligence Index65 / 100
Input Token:

$32.00 / 1M

Output Token:

$64.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

62%

Anthropic

Claude Opus 5.5

Titán de inteligencia de frontera

de Anthropic pinnacle modelo de frontera diseñado para de largo alcance agentic ingeniería de software, denso multimodal documento síntesis, y autónomo investigación flujos de trabajo.

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

Diferencias Clave de un Vistazo

  • Claude Opus 5.5 is 4.5x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 128K tokens).
  • GPT-Realtime-2.1 is faster at 90 tok/s vs 78 tok/s.
  • Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 62.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaracterísticaGPT-Realtime-2.1Claude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
6594
Provider
OpenAIAnthropic
Input Price
Cost per million input tokens
$32.00 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$64.00 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$15.04 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
33K128K
Throughput Speed
Tokens generated per second
90 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
62%84.6%
GPQA Diamond
Graduate-level reasoning
70%82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$3.20 / 1M$0.40 / 1M

¿Quién gana en cada área?

At-a-glance decision framework
Código
Claude Opus 5.5
+22.6% SWE-bench lead
Costo
Claude Opus 5.5
4.5x cheaper monthly runtime
Velocidad
GPT-Realtime-2.1
+15% faster generation
Contexto
Claude Opus 5.5
1M tokens window

Puntuaciones de Benchmarks Verificadas

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

GPT-Realtime-2.1Claude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

62%vs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

70%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

83%vs91.5%
LMSYS Chatbot Arena Elo

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

1350ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

10.8%vs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

38%vs66.4%
SciCode (Scientific Computing)

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

36.5%vs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

62%vs83.1%
AIME (Advanced Math Competition)

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

86.5%vs95.4%
Long-Context Reasoning

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

74%vs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

90 tok/s vs78 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
GPT-Realtime-2.10.32s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT-Realtime-2.15.88s
Claude Opus 5.57.81s

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)
GPT-Realtime-2.1 Monthly API Bill
$110.40 / month
$32/1M in · $64/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
Claude Opus 5.5 saves approximately $85.80 / month (78%) under this workload.4.5x Savings

GPT-Realtime-2.1 · Strengths & Key Advantages

  • bajo-latencia voz-un-voz conversación
  • Configurable razonamiento y en vivo herramienta calls medio-conversación
  • Natural interruption handling para voz agentes
  • Handles barge-en y interruptions naturally
Considerations & Trade-offs
  • limitado 128K ventana de contexto versus texto-primer modelos
  • audio token precios es alto para largo sessions

Claude Opus 5.5 · Strengths & Key Advantages

  • inigualable autónomo multipaso codificación agéntica y refactorización
  • Flawless multidocumento razonamiento sobre 1M token contexto con no largo-prompt surcharge
  • más alto Artificial análisis inteligencia Index ever measured (58/100), leading SWE-bench Pro un 89.9%
  • Precise herramienta ejecución con robust error-recovery bucles
Considerations & Trade-offs
  • Premium salida precios ($20.00/M) plus heavy razonamiento-token usage (~119K salida tokens por index tarea) keeps largo agentic se ejecuta expensive
  • largo pensamiento times un maximum effort puede push un único hard agentic tarea toward ~$13

Token Use & Task Economics

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

MetricGPT-Realtime-2.1Claude Opus 5.5
Cost per Task
Estimated USD to finish one task
$6.66$3.85
Output Tokens / Task
Tokens generated per task
26K68K
Reasoning Tokens / Task
Thinking tokens burned per task
14K42K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

CaracterísticaGPT-Realtime-2.1Claude Opus 5.5
Official API Model ID (SDK)gpt-realtime-2-1claude-opus-5-5-20260901
API ProtocolOpenAI Responses API & Chat Completions v1Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2026-072026-09
Knowledge CutoffFebruary 2026June 2026
ArchitectureReal-time speech-to-speech multimodal transformerExtended Autonomous Hybrid Reasoning Transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($32/1M in) across full 128K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLAutomatic prefix caching at $3.2/1M (no extra cache-write fee)$0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function callingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxNative Web Search tool + Hosted Code Interpreter & File Search RAGNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)Custom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token BillingText BPE (~4 chars/token) · Audio (~25–32 tokens/sec)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 ClassificationOpenAI Preparedness Framework Audited & System Card PublishedAnthropic 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 Modalitiesaudio, texttext, vision
Output Modalitiesaudio, texttext

GPT-Realtime-2.1 vs Claude Opus 5.5: Respuestas Rápidas (FAQ)

Which is more intelligent, GPT-Realtime-2.1 or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 65 on the composite Intelligence Index.

Which model is faster?

GPT-Realtime-2.1 is faster, generating 90 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

Claude Opus 5.5 is cheaper at $3.08 per 1M tokens blended, compared with $15.04 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-Realtime-2.1 has lower latency, with a time to first token of 0.32s compared with 1.40s.

Which model has a larger context window?

Claude Opus 5.5 has a larger context window, supporting 1M tokens compared with 128K tokens.

Veredicto

Choose GPT-Realtime-2.1 for en tiempo real voz agentes, call automatización y en vivo asistentes, or choose Claude Opus 5.5 for grande-escala software development agentes, empresarial codebases, y de misión crítica científico síntesis.

Preguntas frecuentes

Which is cheaper: GPT-Realtime-2.1 or Claude Opus 5.5?+

GPT-Realtime-2.1 costs $32/1M input and $64/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: GPT-Realtime-2.1 or Claude Opus 5.5?+

GPT-Realtime-2.1 supports 128K tokens whereas Claude Opus 5.5 supports 1M tokens.

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: OpenAI & Anthropic Official Documentation