Head-to-Head Model Comparison

GPT-5 Chat vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Reviewed by the GetInfoUs research teamLast reviewed: October 2026Editorial policy
Share
Related topics (4)
OpenAIAnthropicflagshipflagship

Compare GPT-5 Chat by OpenAI against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

Head-to-Head Comparison

Switch & Compare Any Models

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-5 Chat

Conversational GPT-5

A chat-tuned GPT-5 optimised for conversation, writing and tool workflows in ChatGPT.

Intelligence Index56 / 100
Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

70%

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-5 Chat is 1.0x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 128K tokens).
  • GPT-5 Chat is faster at 140 tok/s vs 78 tok/s.
  • Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 70.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGPT-5 ChatClaude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
5694
Provider
OpenAIAnthropic
Input Price
Cost per million input tokens
$0.00 / 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
128K tokens~192 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
16K128K
Throughput Speed
Tokens generated per second
140 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
70%84.6%
GPQA Diamond
Graduate-level reasoning
79%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
+14.6% SWE-bench lead
Cost
GPT-5 Chat
1.0x cheaper monthly runtime
Speed
GPT-5 Chat
+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-5 ChatClaude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

70%vs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

79%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

85%vs91.5%
LMSYS Chatbot Arena Elo

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

1358ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

11.6%vs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

42.5%vs66.4%
SciCode (Scientific Computing)

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

40%vs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

68%vs83.1%
AIME (Advanced Math Competition)

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

88%vs95.4%
Long-Context Reasoning

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

76%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-5 Chat1.05s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT-5 Chat4.62s
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-5 Chat Monthly API Bill
$0.00 / month
$0/1M in · $0/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
GPT-5 Chat saves approximately $24.60 / month (100%) under this workload.1.0x Savings

GPT-5 Chat · Strengths & Key Advantages

  • Smooth, well-calibrated conversational tone
  • Optimised for the ChatGPT product experience
  • Well calibrated refusals and safety behaviour
Considerations & Trade-offs
  • Not offered as a standard API model — subscription access only
  • Smaller context and output limits than the API GPT-5 tier

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-5 ChatClaude Opus 5.5
Cost per Task
Estimated USD to finish one task
$1.50$3.85
Output Tokens / Task
Tokens generated per task
54K68K
Reasoning Tokens / Task
Thinking tokens burned per task
28K42K

Technical Specifications

Architecture, release timeline, capabilities, and modalities.

FeatureGPT-5 ChatClaude Opus 5.5
Official API Model ID (SDK)gpt-5-chatclaude-opus-5-5-20260901
API ProtocolOpenAI Responses API & Chat Completions v1Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2025-082026-09
Knowledge CutoffSeptember 2024June 2026
ArchitectureChat-tuned unified reasoning modelExtended 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)Free across full context window (only KV-cache VRAM scales)Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLAutomatic prefix KV-caching in vLLM / SGLang (0 cost)$0.4/1M 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 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) · 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 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 Modalitiestext, visiontext, vision
Output Modalitiestexttext

GPT-5 Chat vs Claude Opus 5.5: Quick Answers

Which is more intelligent, GPT-5 Chat or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 56 on the composite Intelligence Index.

Which model is faster?

GPT-5 Chat is faster, generating 140 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

GPT-5 Chat 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-5 Chat has lower latency, with a time to first token of 1.05s 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.

Verdict

Choose GPT-5 Chat for interactive chat and writing inside chatgpt, 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-5 Chat or Claude Opus 5.5?+

GPT-5 Chat costs $0/1M 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-5 Chat or Claude Opus 5.5?+

GPT-5 Chat 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.

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