GPT-5.4 nano
Edge and on-device model featuring sub-80ms latency, 250k context, and $0.06/$0.24 per million token economics.
250k
~188k words input
$0.06 / $0.24
Prompt / Completion per 1M
76.8 % pass@1
MMLU-Pro
Cloud Managed
Zero local VRAM
Holistic Capability Distribution
Normalized 0-100 rating vectors balanced across intelligence, throughput, and economics.
Verified LLM Benchmarks
Empirical evaluations across academic reasoning, software engineering, agentic execution, and human preference.
Inference Latency & Generation Throughput
Empirical telemetry benchmarking generation throughput (Tokens/Second) and Time to First Token (TTFT).
Measured under concurrent production load
p95 latency: 190 ms
Across 7,000 monitored requests
Architectural Strengths vs. Operational Considerations
An objective technical balance sheet analyzing deployment advantages and production constraints.
Key Architectural Strengths
- 200 tokens/sec throughput with sub-80ms time to first token.
- Fractional pricing ($0.06 / $0.24 per 1M tokens).
- 250k token context window.
Operational Considerations
- Text only; best paired with larger teacher models for complex architecture.
Hardware & Execution Parameters
Genealogical Provenance
Nano-tier model in the GPT-5.4 release wave.
openai gpt 5 nano
GPT-5.4 nano
Architecture Engineering & Capability Deep-Dive
Topology & Attention Mechanics
Ultra-fast dense transformer architecture optimized for hardware edge inference.
Evaluation Profile & Reasoning Capabilities
Instantaneous classification, intent extraction, and light text summarization.
Inference Economics & Cost Optimization
$0.06 input per 1M tokens.
Primary Production Workloads & Suitability
Cloud Deployment Architecture & Hardware Sizing
Cloud Deployment Architecture
Distributed enterprise serving infrastructure, autoscaling semantics, and runtime execution profile.
Proprietary commercial model hosted on managed multi-region clusters with automatic autoscaling, high availability, and prompt prefix caching.
Multi-Tenant Cloud API
Continuous autoscaling with regional failover
0 GB Local VRAM
Inference executed on hyperscaler accelerator clusters
250k tokens
Supported with automated KV cache prefix compression
SDK Installation
Official Repositories & Papers
Compare Showdowns
GPT-5.4 nano vs GPT-5.4
Compare GPT-5.4 nano against GPT-5.4's verified benchmarks, context window, and pricing.
GPT-5.4 nano vs GPT-5.4 mini
Compare GPT-5.4 nano against GPT-5.4 mini's verified benchmarks, context window, and pricing.
GPT-5.4 nano vs OpenAI Decisions
Compare GPT-5.4 nano against OpenAI Decisions's verified benchmarks, context window, and pricing.
GPT-5.4 nano vs GPT-3.5 Turbo
Compare GPT-5.4 nano against GPT-3.5 Turbo's verified benchmarks, context window, and pricing.
Commercial Token Rates & Cost Estimator
$0.06 / 1M
Standard prompt context ingestion
$0.24 / 1M
Generated completion & thinking tokens
$0.01 / 1M
Re-used prompt prefix context
Monthly Production Cost Simulator
$13.20
Includes prompt caching
-$3.00
Saved via prefix context caching
Comparable Foundation Architectures
Alternative foundation models with comparable intelligence benchmarks, context windows, and deployment profiles.
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.
GPT-5.4 mini
March 2026 compact model delivering 400k context, 69.5% SWE-bench resolution, and fractional $0.20/$0.80 pricing.
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.
GPT-3.5 Turbo
OpenAI's foundational conversational model that launched the ChatGPT era, optimized for fast dialogue, summary generation, and lightweight JSON tasks.
SDK Installation & API Integration
import OpenAI from 'openai';
const client = new OpenAI();
const completion = await client.chat.completions.create({
model: 'gpt-5.4-nano',
messages: [{ role: 'user', content: 'Ping' }],
});
console.log(completion.choices[0].message.content);Frequently Asked Questions about GPT-5.4 nano
Engineering specifications, VRAM sizing, commercial licensing terms, token economics, and empirical benchmark evaluations.
GPT-5.4 nano reaches 200 tokens per second with an 80ms TTFT.