- - 🆕 Compact GPT-5.4-class model for high-throughput, latency-sensitive workloads.
- - 📏 400,000-token context window with up to 128K output tokens.
- - 👁️ Accepts text and image inputs.
- - 🔧 Supports function calling, tool use, file search, and computer use.
- - 🌐 Built-in web search for grounded responses.
- - ⚡ Optimized for speed in coding assistants and parallel subagents.
- - 🎯 Recommended for classification, extraction, ranking, and coding subtasks.
OpenAI is an American artificial intelligence research organization headquartered in San Francisco, structured as both a for-profit public benefit corporation and a nonprofit foundation. The lab developed the GPT family of large language models, the DALL-E image generation…
Explore 16 more models by OpenAI →GPT-5.4 Mini, released in 2026 by OpenAI, is a smaller, faster sibling within the GPT-5.4 generation, bringing many of the strengths of [[sibling:openai-gpt-54|GPT-5.4]] to a model designed for high-volume, cost-sensitive deployments. It supports text and image inputs, tool use, function calling, web search, file search, computer use, and skills, alongside a 400,000-token context window. OpenAI positions it for workloads where latency directly shapes the product experience, such as responsive coding assistants and computer-using systems that interpret screenshots.
Within the catalog's mini lineage, it follows [[sibling:openai-gpt-4o-mini-2024-07-18|GPT-4o Mini]]. According to OpenAI, GPT-5.4 Mini and its companion nano are the company's most capable small models yet, and OpenAI now recommends starting with GPT-5.4 mini for most new low-latency, high-volume workloads in place of the earlier GPT-5 mini.
In practice, OpenAI describes a delegation pattern in Codex where a larger model like GPT-5.4 handles planning, coordination, and final judgment, while GPT-5.4 Mini subagents tackle narrower subtasks in parallel—searching a codebase, reviewing a large file, or processing supporting documents.
It sits alongside other GPT-5.4 tier models, including [[sibling:openai-gpt-54-pro|GPT-5.4 Pro]], and the later [[sibling:openai-gpt-55|GPT-5.5]] and [[sibling:openai-gpt-55-pro|GPT-5.5 Pro]] releases. OpenAI recommends it as a default starting point for new low-latency, high-volume agent and chat workloads.
This About section is AI-generated from public sources via VeniceStats + Venice inference, with no human editing. It may contain inaccuracies.
| Seller | Reputation↓ | Input $/M | Cached $/M | Output $/M | Categories | API |
|---|---|---|---|---|---|---|
| Venice.ai Proxy 0x1f22…18c9 | 88 | $0.4688 | $0.0469 | $2.8125 | chat,reasoning,vision,multimodal,web-search | openai-chat-completions |
| surplusintelligence.ai 0x0e49…8927 | 79 | $0.9375 | $0.0938 | $5.625 | chat,multimodal,reasoning,vision,web-search,research | openai-chat-completions |
| antseed-tidal-ibis-a9b7 0xb1e1…a9b7 | 65 | $400.00 | $200.00 | $1,800.00 | chat,fast,cheap | openai-chat-completions |
| Open Bird 0xc0f1…8183 | 57 | $0.2625 | $0.2625 | $1.575 | chat,coding | openai-chat-completions |
| ▲ Apex Ant 0x73b4…e736 | 40 | $0.0068 | $0.0014 | $0.041 | chat,fast,reasoning,cheap,coding,study | openai-chat-completions |
| Fire Ant 🔥🐜 0xbe05…bc5d | 38 | $0.2525 | $0.0369 | $1.565 | chat,cheap,coding,fast,gpt,json,math,multimodal,reasoning,study,tools,vision,web-search | — |
| Leftermute 0x388b…5389 | 26 | $0.0076 | $0.0076 | $0.0455 | chat,coding,json,tools | openai-chat-completions |
| stupmonke 0x789c…5f1b | 10 | $0.0067 | $0.0007 | $0.0267 | chat,coding,fast | openai-chat-completions |
| Meridian AI 0x8c8c…06f5 | 2 | $0.0911 | $0.0911 | $0.5468 | chat,coding | openai-chat-completions |
| Token God 0x0c56…fb35 | 0 | $0.025 | $0.01 | $0.068 | chat,math,coding | openai-chat-completions |
| antseed-to-da-moon 0xadb7…e98a | 0 | $0.02 | $0.01 | $0.06 | chat,math,coding | openai-chat-completions |
| antseed-fan 0x3620…19e7 | 0 | $0.017 | $0.01 | $0.055 | chat,math,coding | openai-chat-completions |
"Best price" and the seller table are live AntSeed catalog data (advertised $/1M tokens, not settled amounts). Reputation = on-chain trust (0-100). Model knowledge (TLDR, provider, About) via the VeniceStats enrichment layer. Advertised catalog, not the model used in any specific purchase.