All Models
OpenAISmall / On-DeviceProprietary Commercial APIReleased: 2026-03-12

GPT-5.4 mini

March 2026 compact model delivering 400k context, 69.5% SWE-bench resolution, and fractional $0.20/$0.80 pricing.

Foundation DNA84/100
DENSE ArchProprietary params
At a Glance Specifications
Context Window

400k

~300k words input

Token Pricing

$0.2 / $0.8

Prompt / Completion per 1M

Top Benchmark

69.5 % resolved

SWE-bench Verified

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:84/100
ReasoningCodingSpeedEconomicsContextFlexibility
Context: 94/100 (Window Horizon)
ReasoningGPQA / Logic / Math
85/100
CodingSWE-bench / LCB
86/100
SpeedTokens / Second
97/100
EconomicsCost Efficiency
98/100
ContextWindow Horizon
94/100
FlexibilityTool Use & Open
90/100
Performance Evaluations

Verified LLM Benchmarks

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

SWE-bench Verified Headline
69.5% resolved
swebench.harness
CodingOpenAI Technical Documentation
GPQA Diamond Headline
77% pass@1
Inspect
Academic ReasoningOpenAI Technical Documentation
Chatbot Arena Elo Headline
1400Elo
LMSYS Blind Pairwise Battles
Human Preferencehttps://chat.lmsys.org/
Real-Time Provider Telemetry

Inference Latency & Generation Throughput

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

Peak Generation Speed
140tokens/sec

Measured under concurrent production load

Lowest Time to First Token
160ms

p95 latency: 420 ms

Telemetry Verification
99.96%uptime

Across 5,200 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

  • Reaches 69.5% on SWE-bench Verified at ultra-low $0.20/$0.80 rates.
  • 400,000-token context window.
  • Sub-160ms time to first token.
Production Constraints

Operational Considerations

  • Advanced formal verification still favors full GPT-5.4.
Technical Specifications

Hardware & Execution Parameters

Architecture Typedense
Total ParametersProprietary
Attention MechanismSliding-Window
Context Window400,000 tokens
Max Output Tokens32,000 tokens
Supported Modalities
textimage
License Typeproprietary
Commercial Use Allowed
Model DistillationProhibited
Zero Data RetentionAvailable
Knowledge Cutoff2026-01
Model Heritage & Evolutionary Lineage

Genealogical Provenance

Spring 2026 high-speed compact model.

Base Precursor

openai gpt 5 mini

Current Architecture

GPT-5.4 mini

openai gpt 5 4openai gpt 5 4 nano
Engineering Deep-Dive

Architecture Engineering & Capability Deep-Dive

Topology & Attention Mechanics

Distilled model retaining GPT-5.4 reasoning graphs.

Evaluation Profile & Reasoning Capabilities

Fast code fixing, script generation, and structured data transformation.

Inference Economics & Cost Optimization

$0.20 input per 1M tokens.

Primary Production Workloads & Suitability

Interactive code completion
Automated bug triage
Customer service automation
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

400k 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

$0.20 / 1M

Standard prompt context ingestion

Base Output Tokens

$0.80 / 1M

Generated completion & thinking tokens

Prompt Cache ReadUp to 80% Off

$0.03 / 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

$43.80

Includes prompt caching

Monthly Cache Savings

-$10.20

Saved via prefix context caching

Frontier Alternatives

Comparable Foundation Architectures

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

OpenAIReasoning

GPT-5.4

March 2026 foundation model standardizing 83.8% SWE-bench Verified coding precision, 500k context, and $3/$12 economics for enterprise agent automation.

Context:500k ctx
Parameters:Proprietary
Input Rate:$3/1M
Compare Architecture
OpenAISmall / On-Device

GPT-5.4 nano

Edge and on-device model featuring sub-80ms latency, 250k context, and $0.06/$0.24 per million token economics.

Context:250k ctx
Parameters:Proprietary
Input Rate:$0.06/1M
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
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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-5.4-mini',
  messages: [{ role: 'user', content: 'Ping' }],
});
console.log(completion.choices[0].message.content);
Knowledge Base

Frequently Asked Questions about GPT-5.4 mini

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

GPT-5.4 mini delivers a 160ms time-to-first-token and generates at 140 tokens per second.

Verified Engineering FAQ
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