All Models
OpenAIReasoningProprietary Commercial APIReleased: 2023-03-14

GPT-4

OpenAI's foundational March 2023 frontier release, establishing breakthrough human-level performance on academic examinations, professional certifications, and complex logic.

Foundation DNA74/100
MOE ArchProprietary (~1.8T MoE estimated) params
At a Glance Specifications
Context Window

8.192k

~6k words input

Token Pricing

$30 / $60

Prompt / Completion per 1M

Top Benchmark

86.4 % pass@1

MMLU

Hardware Tier

Cloud Managed

Zero local VRAM

6-Axis Foundation Model DNA

Holistic Capability Distribution

Normalized 0-100 rating vectors balanced across intelligence, throughput, and economics.

Overall Index:74/100
ReasoningCodingSpeedEconomicsContextFlexibility
Context: 48/100 (Window Horizon)
ReasoningGPQA / Logic / Math
82/100
CodingSWE-bench / LCB
75/100
SpeedTokens / Second
52/100
EconomicsCost Efficiency
40/100
ContextWindow Horizon
48/100
FlexibilityTool Use & Open
82/100
Performance Evaluations

Verified LLM Benchmarks

Empirical evaluations across academic reasoning, software engineering, agentic execution, and human preference.

MMLU Headline
86.4% pass@1
lm-eval-harness
Academic ReasoningOpenAI GPT-4 Technical Report
HumanEval Headline
67% pass@1
lm-eval-harness
CodingOpenAI Technical Documentation
Chatbot Arena Elo Headline
1160Elo
LMSYS Blind Pairwise Battles
Human Preferencehttps://chat.lmsys.org/
GPQA Diamond Headline
35.8% pass@1
Inspect
Academic ReasoningOpenAI Technical Report
Real-Time Provider Telemetry

Inference Latency & Generation Throughput

Empirical telemetry benchmarking generation throughput (Tokens/Second) and Time to First Token (TTFT).

Peak Generation Speed
35tokens/sec

Measured under concurrent production load

Lowest Time to First Token
750ms

p95 latency: 1950 ms

Telemetry Verification
99.8%uptime

Across 3,200 monitored requests

Production Trade-Offs

Architectural Strengths vs. Operational Considerations

An objective technical balance sheet analyzing deployment advantages and production constraints.

Operational Advantages

Key Architectural Strengths

  • Historical leap in professional and academic reasoning (90th percentile Uniform Bar Exam).
  • Exceptional precision on formal prompt constraints and complex system prompts.
Production Constraints

Operational Considerations

  • High cost ($30/$60 per 1M tokens) and slow throughput compared to newer generations.
  • Small 8k context window.
Technical Specifications

Hardware & Execution Parameters

Architecture Typemoe
Total ParametersProprietary (~1.8T MoE estimated)
Attention MechanismMHA
Context Window8,192 tokens
Max Output Tokens4,096 tokens
Supported Modalities
textimage
License Typeproprietary
Commercial Use Allowed
Model DistillationProhibited
Zero Data RetentionAvailable
Knowledge Cutoff2021-09
Model Heritage & Evolutionary Lineage

Genealogical Provenance

First frontier foundation model in the GPT-4 generation.

Base Precursor

openai gpt 3 5 turbo

Current Architecture

GPT-4

Engineering Deep-Dive

Architecture Engineering & Capability Deep-Dive

Topology & Attention Mechanics

Large-scale Mixture-of-Experts architecture optimized for factual accuracy and complex instruction adherence.

Evaluation Profile & Reasoning Capabilities

Exhibits human-grade performance across law, medicine, physics, and computer science examinations.

Inference Economics & Cost Optimization

Legacy pricing remains high due to compute footprint.

Primary Production Workloads & Suitability

Historical benchmark verification
High-scrutiny legal analysis
Compute & Deployment Architecture

Cloud Deployment Architecture & Hardware Sizing

Cloud Deployment Architecture

Distributed enterprise serving infrastructure, autoscaling semantics, and runtime execution profile.

Cloud APIZero Local VRAM Required

Proprietary commercial model hosted on managed multi-region clusters with automatic autoscaling, high availability, and prompt prefix caching.

SLA: 99.9% Cloud Availability
Rate Limit: Scaled via Provider Quota
Cache: Automatic Prefix Compression
Serving Model

Multi-Tenant Cloud API

Continuous autoscaling with regional failover

Hardware Overhead

0 GB Local VRAM

Inference executed on hyperscaler accelerator clusters

Context Capacity

8.192k tokens

Supported with automated KV cache prefix compression

SDK Installation

$npm install openai
$pip install openai
Inference Economics & Total Cost of Ownership

Commercial Token Rates & Cost Estimator

Base Input Tokens

$30.00 / 1M

Standard prompt context ingestion

Base Output Tokens

$60.00 / 1M

Generated completion & thinking tokens

Prompt Cache ReadUp to 80% Off

$15.00 / 1M

Re-used prompt prefix context

Monthly Production Cost Simulator

Daily Prompt Ingestion5M tokens/day (~150M/mo)
Daily Completion Generation1M tokens/day (~30M/mo)
Prompt Prefix Cache Hit Rate40%
Estimated Monthly Spend

$5,400.00

Includes prompt caching

Monthly Cache Savings

-$900.00

Saved via prefix context caching

Frontier Alternatives

Comparable Foundation Architectures

Alternative foundation models with comparable intelligence benchmarks, context windows, and deployment profiles.

OpenAIMultimodal

GPT-4 Turbo

OpenAI's November 2023 DevDay milestone, expanding context to 128,000 tokens with vision capabilities, JSON mode, reproducible outputs, and lower pricing.

Context:128k ctx
Parameters:Proprietary
Input Rate:$10/1M
Compare Architecture
OpenAIMultimodal

GPT-4o

OpenAI's flagship omni model natively processing text, audio, and vision with low-latency multimodal reasoning and a 128,000 token context window.

Context:128k ctx
Parameters:Proprietary
Input Rate:$2.5/1M
Compare Architecture
OpenAIDecision

OpenAI Decisions

OpenAI Decisions is OpenAI's dedicated high-throughput decision-making API powered by GPT-6 Luna, accessed via the POST /v1/decisions endpoint. Designed for agent routing, automated content moderation, and classification, it processes typed questions (predicates, categorical choices, and rubric scores) roughly 10x faster than standard generation, billed at $0.10 per million input tokens with zero output-token fees.

Context:128k ctx
Parameters:Proprietary (GPT-6 Luna Decision Engine)
Input Rate:$0.1/1M
Compare Architecture
OpenAIGeneral

GPT-3.5 Turbo

OpenAI's foundational conversational model that launched the ChatGPT era, optimized for fast dialogue, summary generation, and lightweight JSON tasks.

Context:16.385k ctx
Parameters:Proprietary
Input Rate:$0.5/1M
Compare Architecture
Developer Quickstart

SDK Installation & API Integration

$npm install openai
$pip install openai
import OpenAI from 'openai';

const client = new OpenAI();
const completion = await client.chat.completions.create({
  model: 'gpt-4',
  messages: [{ role: 'user', content: 'Explain the legal doctrine of promissory estoppel.' }],
});
console.log(completion.choices[0].message.content);
Knowledge Base

Frequently Asked Questions about GPT-4

Engineering specifications, VRAM sizing, commercial licensing terms, token economics, and empirical benchmark evaluations.

GPT-4o is 2x faster, 12x cheaper, and includes 16x larger context (128k vs 8k) with native omni-modal vision and audio.

Verified Engineering FAQ
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