GetInfoUs
Head-to-Head Model Comparison

GPT Realtime Whisper vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

由 GetInfoUs 研究团队审核最后审核日期：October 2026编辑政策
分享
Related topics (4)
OpenAIAnthropiclightweightflagship

Compare GPT Realtime Whisper by OpenAI against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

模型直接对比 (VS)

切换并对比任意模型

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

Live comparison: no in-depth editorial review has been published for this pair yet.

Popular Matchups:
OpenAI

GPT Realtime Whisper

高性能 AI 模型

OpenAI 推出的 GPT Realtime Whisper 人工智能模型，具备 448 上下文窗口，输入价格为 $0.006/百万 Token，输出价格为 $0/百万 Token，专为高质量生产环境、推理与自动化工作流打造。

Intelligence Index44 / 100
Input Token:

$0.01 / 1M

Output Token:

$0.00 / 1M

Context Window:

448 tokens

SWE-bench Verified:

36%

Anthropic

Claude Opus 5.5

深度推理模型

Anthropic 推出的 Claude Opus 5.5 人工智能模型，具备 1M 上下文窗口，输入价格为 $4.0/百万 Token，输出价格为 $20.0/百万 Token，专为高质量生产环境、推理与自动化工作流打造。

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

核心差异一览

  • GPT Realtime Whisper is 2733.3x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 0K tokens).
  • GPT Realtime Whisper is faster at 140 tok/s vs 78 tok/s.
  • Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 36.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGPT Realtime WhisperClaude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
4494
Provider
OpenAIAnthropic
Input Price
Cost per million input tokens
$0.01 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$0.00 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.00 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
448 tokens~1 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
0K128K
Throughput Speed
Tokens generated per second
140 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
36%84.6%
GPQA Diamond
Graduate-level reasoning
46%82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.00 / 1M$0.40 / 1M

各项指标谁更胜一筹？

At-a-glance decision framework
Coding
Claude Opus 5.5
+48.6% SWE-bench lead
Cost
GPT Realtime Whisper
2733.3x cheaper monthly runtime
Speed
GPT Realtime Whisper
+79% faster generation
Context
Claude Opus 5.5
1M tokens window

权威基准测试得分对比

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

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

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

36%vs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

46%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

66%vs91.5%
LMSYS Chatbot Arena Elo

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

1255ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

5.5%vs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

23%vs66.4%
SciCode (Scientific Computing)

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

24.5%vs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

39%vs83.1%
AIME (Advanced Math Competition)

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

46%vs95.4%
Long-Context Reasoning

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

61%vs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

140 tok/s vs78 tok/s

延迟与响应速度

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 Whisper0.15s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT Realtime Whisper3.72s
Claude Opus 5.57.81s

实时 Token 成本模拟器

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 Whisper Monthly API Bill
$0.01 / month
$0.006/1M in · $0/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
GPT Realtime Whisper saves approximately $24.59 / month (100%) under this workload.2733.3x Savings

GPT Realtime Whisper · Strengths & Key Advantages

  • 由 OpenAI 研发的高精度 Streaming speech-to-text transformer 架构，支持 448 上下文窗口
  • 极具竞争力的 API 定价（输入 $0.006/1M，输出 $0/1M），支持高速推理与工具调用
  • 在代码生成、逻辑推理与多语言处理基准测试中表现出色
Considerations & Trade-offs
  • 超长上下文请求需要规划 Token 成本与并发配额
  • 针对特定垂直领域任务建议结合系统提示词与检索增强（RAG）以获得最佳效果

Claude Opus 5.5 · Strengths & Key Advantages

  • 由 Anthropic 研发的高精度 Extended Autonomous Hybrid Reasoning Transformer 架构，支持 1M 上下文窗口
  • 极具竞争力的 API 定价（输入 $4.0/1M，输出 $20.0/1M），支持高速推理与工具调用
  • 在代码生成、逻辑推理与多语言处理基准测试中表现出色
Considerations & Trade-offs
  • 超长上下文请求需要规划 Token 成本与并发配额
  • 针对特定垂直领域任务建议结合系统提示词与检索增强（RAG）以获得最佳效果

Token Use & Task Economics

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

MetricGPT Realtime WhisperClaude Opus 5.5
Cost per Task
Estimated USD to finish one task
$0.04$3.85
Output Tokens / Task
Tokens generated per task
3K68K
Reasoning Tokens / Task
Thinking tokens burned per task
0K42K

技术规格参数

Architecture, release timeline, capabilities, and modalities.

FeatureGPT Realtime WhisperClaude Opus 5.5
Official API Model ID (SDK)gpt-realtime-whisperclaude-opus-5-5-20260901
API ProtocolOpenAI Responses API & Chat Completions v1Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2026-052026-09
Knowledge CutoffFebruary 2026June 2026
ArchitectureStreaming speech-to-text 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 ($0.006/1M in) across full 0K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLAutomatic prefix caching at $0/1M (no extra cache-write fee)$0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI AgentText-only completion (No GUI action loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingPrompt-based JSON extraction onlyNative 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 Modalitiesaudiotext, vision
Output Modalitiestexttext

GPT Realtime Whisper vs Claude Opus 5.5: 常见问题解答 (FAQ)

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

Claude Opus 5.5 is more intelligent. It scores 94 compared with 44 on the composite Intelligence Index.

Which model is faster?

GPT Realtime Whisper is faster, generating 140 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

GPT Realtime Whisper is cheaper at $0.00 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT Realtime Whisper has lower latency, with a time to first token of 0.15s 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 448 tokens.

综合结论

Choose GPT Realtime Whisper for 企业级 ai 自动化、代码研发、智能体（agent）工作流以及 openai 生态深度集成, or choose Claude Opus 5.5 for 企业级 ai 自动化、代码研发、智能体（agent）工作流以及 anthropic 生态深度集成.

常见问题 (FAQ)

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

GPT Realtime Whisper costs $0.006/1M input and $0/1M 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 Whisper or Claude Opus 5.5?+

GPT Realtime Whisper supports 0K 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.

Tokens & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

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.

数据来源: OpenAI & Anthropic Official Documentation