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Model details

gpt-5.4-nano

GPT-5.4 nano extends the GPT-5.4 family into a lightweight, ultra-efficient tier aimed at low-latency, cost-effective tasks at massive scale. Positioned as the smallest and cheapest member of the lineup, it is intended for high-volume production workloads where response speed and operating cost matter more than top-end reasoning. Multiple third-party write-ups frame the nano variant alongside GPT-5.4 mini as a "dynamic duo" for agent-style applications, with both models running more than twice as fast as the prior GPT-5 mini generation. The model keeps the same multimodal grounding as its larger siblings, natively accepting text and image inputs while producing text outputs, and it supports the cataloged API limit context window that closes much of the gap with the flagship GPT-5.4 for long-document and multi-step workflows.

In practice, GPT-5.4 nano fits naturally into pipelines that need quick classification, routing, extraction, formatting, and tool-augmented calls without paying flagship rates. The DataCamp and ETIH coverage note that, while it does not match the mini variant on every benchmark, it still beats the older GPT-5 mini on many evaluations, making it a sensible drop-in upgrade for existing nano-style traffic. The catalog describes a feature set consistent with agentic use, including reasoning, tool calling, structured output, and attachment handling, and the Microsoft Foundry listing confirms availability as a Direct from Azure deployment. Independent pricing trackers corroborate the per-million-token input rate, reinforcing its positioning as the budget-friendly option for teams that want GPT-5.4-era behavior on routine, latency-sensitive requests.

302.AIgpt-5.4-nanogpt-nano

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Provider
302.AI
Model key
gpt-5.4-nano
Release date
Mar 19, 2026
Last updated
Mar 19, 2026
Knowledge cutoff
2025-08-31
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.20
Output token cost
$1.25

Limits

Input tokens
272,000 tokens
Output tokens
128,000 tokens
Context window
400,000 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about gpt-5.4-nano

302.AI

CoverageBenchmark

302.AI's own Benchmark Lab published a selection guide on March 24, 2026 evaluating OpenAI's newly released GPT-5.4 mini and GPT-5.4 nano models, both of which 302.AI distributes through its API gateway at api.302.ai. The post frames the pair as the "dynamic duo" of the Agent era, emphasizing that nano is the smallest Technically, the article highlights that both models support a 400K-token context window and native text and image inputs, narrowing the capability gap with the flagship GPT-5.4 while delivering inference speeds more than double those of GPT-5 mini. For developers integrating the gpt-5.4-nano endpoint, the practical gu

302.AI

CoverageBenchmark

GPT-5.4 Mini costs $0.75/1M input, Nano $0.20/1M. Full pricing, benchmarks, and cost comparison vs Claude Haiku and Gemini Flash-Lite.

Poe

CoverageRelease Notes

EdTech Innovation Hub reports OpenAI's release of GPT-5.4 mini and nano, sourced from an OpenAI for Business LinkedIn post, positioning the models for high-volume workloads where organizations need to balance performance, cost, and latency. The article notes the models extend GPT-5.4's capabilities into more efficient The piece quotes OpenAI directly stating that GPT-5.4 nano is the smallest, cheapest GPT-5.4 model, optimized for classification, data extraction, ranking, and coding subagents. It discusses how nano and mini fit into a multi-model architecture where larger models handle planning and decision-making while smaller model

302.AI

CoverageBenchmark

Roboflow Playground maintains a model profile page for GPT-5.4 Nano with concrete technical specifications. The model is listed as a high-throughput, efficiency-optimized entry in the GPT-5.4 family, developed by OpenAI and released on March 17, 2026. It features a 400,000-token context window enabling processing of la The profile describes GPT-5.4 nano as a text-first worker optimized for high-volume classification, data extraction, ranking, and lightweight sub-agent orchestration where speed and low per-token cost are primary requirements. While it supports text and image inputs, it is not positioned as a specialized visual reasoni

302.AI

CoverageBenchmark

OpenRouter's model page for GPT-5.4 Nano describes it as the most lightweight and cost-efficient variant of the GPT-5.4 family, optimized for speed-critical and high-volume tasks such as classification, data extraction, ranking, and sub-agent execution. It supports text and image input/output with a 400K context window The page shows routing across OpenAI, Azure, and OpenAI Flex providers, with throughput/latency figures (OpenAI at ~0.64s latency and 59 tps throughput, Azure at ~1.42s/24 tps). Weighted-average effective prices reflect real-world caching: $0.1183/M input and $1.259/M output. These specs give developers concrete parame

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