Head-to-Head Model Comparison

GPT-5.4 Pro vs GPT-5.4

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Reviewed by the GetInfoUs research teamLast reviewed: October 2026Editorial policy
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
GPT-5.4 Pro vs GPT-5.4: Benchmarks, Pricing & Speed Comparison

GPT-5.4 Pro by OpenAI and GPT-5.4 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, GPT-5.4 holds a notable pricing advantage for token ingestion. On output generation, GPT-5.4 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 1,050K tokens. In latency-sensitive production environments, GPT-5.4 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.

Head-to-Head Comparison

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OpenAI

GPT-5.4 Pro

Pro Precision

A precision GPT-5.4 tier for demanding professional reasoning and agent work.

Intelligence Index81 / 100
Input Token:

$25.00 / 1M

Output Token:

$150.00 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

80.8%

OpenAI

GPT-5.4

1M Agent-Ready

An agent-ready GPT generation built for coding and computer-use workflows at lower cost.

Intelligence Index78 / 100
Input Token:

$2.50 / 1M

Output Token:

$15.00 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

79.2%

Key Differences at a Glance

  • GPT-5.4 is 10.0x cheaper for API usage (input + output tokens combined).
  • GPT-5.4 is faster at 126 tok/s vs 48 tok/s.
  • GPT-5.4 Pro leads on SWE-bench coding (80.8% vs 79.2%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGPT-5.4 ProGPT-5.4
Intelligence Index
Composite reasoning & knowledge score (0-100)
8178
Provider
OpenAIOpenAI
Input Price
Cost per million input tokens
$25.00 / 1M$2.50 / 1M
Output Price
Cost per million output tokens
$150.00 / 1M$15.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$21.75 / 1M$2.17 / 1M
Context Window
Maximum input + output tokens
1.05M tokens~1,575 A4 pages of text1.05M tokens~1,575 A4 pages of text
Max Output Tokens
Per single request
128K128K
Throughput Speed
Tokens generated per second
48 tok/s126 tok/s
SWE-bench Verified
Real-world software engineering
80.8%79.2%
GPQA Diamond
Graduate-level reasoning
79.4%78.6%
Cached Input Price
Prompt caching discount per 1M tokens
$2.50 / 1M$0.25 / 1M

Who Wins Where?

At-a-glance decision framework
Coding
GPT-5.4 Pro
+1.6% SWE-bench lead
Cost
GPT-5.4
10.0x cheaper monthly runtime
Speed
GPT-5.4
+163% faster generation
Context
Tied
1.05M tokens window

Empirical Head-to-Head Benchmark Scores

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

GPT-5.4 ProGPT-5.4
SWE-bench Verified (Autonomous Coding)

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

80.8%vs79.2%
GPQA Diamond (Doctorate-Level Science & Math)

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

79.4%vs78.6%
MMLU-Pro (Multi-task Language Understanding)

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

89.2%vs88.6%
LMSYS Chatbot Arena Elo

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

1450ptsvs1436pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

16%vs15.4%
Terminal-Bench (Agentic Coding & Terminal Use)

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

56.5%vs54.5%
SciCode (Scientific Computing)

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

51%vs49.5%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

78%vs77%
AIME (Advanced Math Competition)

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

94.2%vs93.8%
Long-Context Reasoning

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

85.6%vs84.5%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

48 tok/s vs126 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-5.4 Pro4.60s
GPT-5.41.08s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT-5.4 Pro15.02s
GPT-5.45.05s

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-5.4 Pro Monthly API Bill
$176.25 / month
$25/1M in · $150/1M out
GPT-5.4 Monthly API Bill
$17.63 / month
$2.5/1M in · $15/1M out
GPT-5.4 saves approximately $158.63 / month (90%) under this workload.10.0x Savings

GPT-5.4 Pro · Strengths & Key Advantages

  • Highest accuracy in the GPT-5.4 line
  • Handles very long context with strong recall
  • Excellent on regulated, audit-sensitive analysis
Considerations & Trade-offs
  • Among the most expensive OpenAI models per token
  • Slow — not viable for interactive use

GPT-5.4 · Strengths & Key Advantages

  • First GPT-5-class model with a 1M-token context window
  • Native computer-use and browser automation
  • Well balanced cost for long agent runs
  • Handles 1M-token inputs with good recall
Considerations & Trade-offs
  • Input price doubles beyond 272K tokens
  • Computer-use actions still need human review on critical paths

Token Use & Task Economics

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

MetricGPT-5.4 ProGPT-5.4
Cost per Task
Estimated USD to finish one task
$18.50$2.10
Output Tokens / Task
Tokens generated per task
72K62K
Reasoning Tokens / Task
Thinking tokens burned per task
48K34K

Technical Specifications

Architecture, release timeline, capabilities, and modalities.

FeatureGPT-5.4 ProGPT-5.4
Official API Model ID (SDK)gpt-5-4-progpt-5-4
API ProtocolOpenAI Responses API & Chat Completions v1OpenAI Responses API & Chat Completions v1
Release Date2026-032026-03
Knowledge CutoffAugust 2025August 2025
ArchitectureMaximum-compute agent-ready reasoning modelAgent-ready unified reasoning model
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($25/1M in) across full 1050K windowFlat rate ($2.5/1M in) across full 1050K window
Prompt Cache Policy & TTLAutomatic prefix caching at $2.5/1M (no extra cache-write fee)Automatic prefix caching at $0.25/1M (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 tool + Hosted Code Interpreter & File Search RAGNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)Supervised 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 ClassificationOpenAI Preparedness Framework Audited & System Card PublishedOpenAI 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

GPT-5.4 Pro vs GPT-5.4: Quick Answers

Which is more intelligent, GPT-5.4 Pro or GPT-5.4?

GPT-5.4 Pro is more intelligent. It scores 81 compared with 78 on the composite Intelligence Index.

Which model is faster?

GPT-5.4 is faster, generating 126 tokens per second compared with 48 tokens per second.

Which model is cheaper to run?

GPT-5.4 is cheaper at $2.17 per 1M tokens blended, compared with $21.75 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-5.4 has lower latency, with a time to first token of 1.08s compared with 4.60s.

Verdict

Verdict & Model Selection Recommendation: Choose GPT-5.4 Pro if your priority is Mission-critical analysis and regulated workflows. Its performance in demanding tasks justifies its operational token cost. Choose GPT-5.4 if your workflow prioritizes Long-horizon agentic and computer-use workflows. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.

Frequently asked questions

How does GPT-5.4 Pro compare to GPT-5.4 in API token pricing and cost per token?+

GPT-5.4 Pro costs $25.00 per 1M input tokens and $150.00 per 1M output tokens, whereas GPT-5.4 costs $2.50 input and $15.00 output. Overall, GPT-5.4 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: GPT-5.4 Pro or GPT-5.4?+

Both GPT-5.4 Pro and GPT-5.4 offer an identical context window of 1,050K tokens (~788k 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: GPT-5.4 Pro or GPT-5.4?+

GPT-5.4 Pro scores 80.8% on SWE-bench Verified while GPT-5.4 scores 79.2%. For autonomous software engineering and multi-file debugging, GPT-5.4 Pro holds the verified benchmark lead.

What is the difference in reasoning capability and extended thinking between GPT-5.4 Pro and GPT-5.4?+

GPT-5.4 Pro features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, GPT-5.4 provides chain-of-thought reasoning depth for complex math and science.

How does inference speed (tokens per second) compare between GPT-5.4 Pro and GPT-5.4?+

GPT-5.4 Pro generates approximately 48 tokens per second, while GPT-5.4 delivers 126 tokens per second. In latency-sensitive production environments, GPT-5.4 provides faster time-to-first-token (TTFT) and higher streaming response velocity.

Can you implement a tiered LLM routing setup combining GPT-5.4 Pro and GPT-5.4 to optimize costs?+

Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to GPT-5.4 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to GPT-5.4 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.

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: GetInfoUs Independent AI Benchmarks & Official API Specs