Head-to-Head Model Comparison

GPT Realtime Whisper vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Reviewed by the GetInfoUs research teamLast reviewed: October 2026Editorial policy
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Compare GPT Realtime Whisper by OpenAI against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

Head-to-Head Comparison

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OpenAI

GPT Realtime Whisper

Streaming STT

A streaming speech-to-text model that emits low-latency transcript deltas from live audio.

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

Frontier Intelligence Titan

Anthropic's most intelligent model for complex reasoning, research, and strategic analysis.

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

Key Differences at a Glance

  • 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

Who Wins Where?

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

Empirical Head-to-Head Benchmark Scores

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

Latency & Response Time

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

Real-Time Interactive Token Cost Simulator

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

  • Streaming transcription with very low latency
  • Ideal for live captions and real-time agent input
  • Priced per minute of audio rather than per token
  • Emits transcript deltas with very low latency
Considerations & Trade-offs
  • Speech-to-text only — no generation or reasoning
  • Accuracy drops in very noisy environments

Claude Opus 5.5 · Strengths & Key Advantages

  • Unmatched autonomous multi-step agentic coding and refactoring
  • Flawless multi-document reasoning over 1M token context with no long-prompt surcharge
  • Highest composite Intelligence Index score measured (94/100), leading SWE-bench Verified at 84.6%
  • Precise tool execution with robust error-recovery loops
Considerations & Trade-offs
  • Premium output pricing ($20.00/M) plus heavy reasoning-token usage (~68K output tokens per complex task) keeps long agentic runs expensive
  • Long thinking times at maximum effort can push a single hard agentic task toward ~$3.85+

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

Technical Specifications

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: Quick Answers

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.

Verdict

Choose GPT Realtime Whisper for live captions and real-time voice-agent transcription, or choose Claude Opus 5.5 for large-scale software development agents, enterprise codebases, and mission-critical scientific synthesis.

Frequently asked questions

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.

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.

Sources: OpenAI & Anthropic Official Documentation