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OpenAI

OpenAI: GPT-5.4 Mini

GPT-5.4 Mini Overview

GPT-5.4 mini is a fast, cost-efficient model developed by OpenAI and released on March 17, 2026, optimized for high-throughput workloads and subagent orchestration. It supports text and image inputs within a 400,000-token context window, making it ideal for processing extensive visual datasets and large codebases in a single request. Designed for low-latency production environments, the model integrates with key API features including function calling, web search, and tool-based computer use, allowing it to assist in automated workflows that require navigating digital interfaces.

Compared to the previous GPT-5 mini, this version runs more than twice as fast while approaching the performance levels of the flagship GPT-5.4 on reasoning and coding benchmarks. While the larger GPT-5.4 introduces native, state-of-the-art computer-use capabilities, GPT-5.4 mini provides a scalable alternative for interpreting screenshots and reasoning over dense UI layouts. For vision tasks on Playground, it excels at extracting structured information from visual documents and assisting in agentic tasks that involve real-time interpretation of software interfaces alongside text.

GPT-5.4 Mini Interactive Demo

GPT-5.4 Mini Details & Performance

Details

Resources

Vision Tasks

Vision LanguageObject DetectionClassificationOCRVisual Question AnsweringCaptioning

Features

Foundation VisionLLMs with Vision CapabilitiesMultimodal Vision

Usage

Past 30 Days

Performance

Avg. Latency

Arena Rankings

GPT-5.4 Mini Vision Evals

Visual Understanding

74 models · 67 tasks
HighestLowest
This model#4 of 7477.61% pass rate · better than 89%
Score77.61%pass rate across 67 tasks
Speed5.80savg response per task
Cost$0.0015 / task$0.750 in · $4.50 out / 1M
Tokens1.9K / task1.4K in · 104 out
Score key:≥75%40–74%<40%
CategoryPassedScore
Object Understanding13 / 14
92.9%
Document Understanding8 / 9
88.9%
Spatial Understanding16 / 19
84.2%
Defect Detection11 / 15
73.3%
Object Counting4 / 10
40%
HighestLowest
This model#28 of 5577.29% pass rate · better than 49%
Score77.29%pass rate across 229 tasks
Speed3.24savg response per task
Cost$0.0006 / task$0.750 in · $4.50 out / 1M
Tokens304 / task105 in · 126 out
Score key:≥75%40–74%<40%
CategoryPassedScore
License Plate Recognition26 / 30
86.7%
VQA & Extraction50 / 60
83.3%
Focused Scene OCR75 / 99
75.8%
Text Recognition22 / 30
73.3%
Handwritten Math4 / 10
40%

Scores based on a single evaluation run · Methodology

View all Vision Evals →

GPT-5.4 Mini Pricing

GPT-5.4 Mini costs $0.750 per 1M input tokens and $4.50 per 1M output tokens.

Input$0.750 / 1M tokens
Output$4.50 / 1M tokens
Cached input$0.075 / 1M tokens

Pricing updated Jul 9, 2026

Price vs. performance

Estimated cost per task vs. Visual Understanding score, for this model and others ranked near it. Upper-left is the sweet spot (high quality, low cost).

8 of 8 models plotted

ModelScoreMedian tokensEst. cost / taskCompare
GoogleGemini 3.5 Flash79.1%1.4K$0.0043Compare
AnthropicClaude Fable 579.1%2.9K$0.041Compare
OpenAIGPT-5.4 Mini(this model)77.6%1.9K$0.0015
OpenAIGPT-5.477.6%1.7K$0.0052Compare
OpenAIGPT-5.577.6%1.7K$0.011Compare
QwenQwen3.5 122B A10B76.1%1.2K$0.0003Compare
GoogleGemini 3.1 Pro75.8%1.1K$0.0024Compare
GoogleGemini 3 Flash74.6%1.4K$0.0014Compare

Alternatives to GPT-5.4 Mini

Other models worth comparing for similar use cases.

Google
Gemini 2.5 Flash
Gemini 2.5 Flash, released on June 17, 2025, is Google DeepMind’s production-ready, efficiency-focused model in the Gemini 2.5 family. It is multimodal, accepting text, images, video, and audio as inputs, with text as the primary output format. The model supports 1 million input tokens and up to 65K output tokens, enabling it to process very large contexts such as books, long video transcripts, or extensive datasets. Its training knowledge extends to January 2025.Designed as a price-performance leader, Gemini 2.5 Flash balances speed and reasoning power, making it suitable for everyday enterprise and developer use cases without the higher latency and cost of Pro models. It supports advanced workflows like function calling, code execution, search grounding, URL context ingestion, and structured outputs. While efficient and scalable, output length is still limited compared to its input capacity, and multimodal outputs (e.g. image or audio generation) remain restricted to specialized or preview variants.
Anthropic
Claude Sonnet 5
Claude Sonnet 5 is a mid-tier large language model from Anthropic, released on June 30, 2026, as the latest model in the Sonnet series and a direct successor to Claude Sonnet 4.6. It is a hybrid reasoning model designed primarily for agentic workflows, software coding, and professional tasks. The model features a 1 million token context window, a 128k maximum output token limit, and runs adaptive thinking by default, giving API users fine-grained control over reasoning effort across five levels (low, medium, high, max, and extra-high). It uses an updated tokenizer shared with Opus 4.7 and later models, which produces approximately 30% more tokens for equivalent text compared to earlier Claude models. On benchmarks, Sonnet 5 scores 63.2% on agentic coding and 81.2% on OSWorld, narrowing the gap with Opus 4.8 while remaining at Sonnet-tier pricing.The model supports text and image input with text output, and accepts tools including browsers and terminals for autonomous multi-step task execution. Anthropic's safety evaluations report that Sonnet 5 shows a lower rate of undesirable behaviors than Sonnet 4.6 and is generally safer in agentic contexts, with improved resistance to prompt injection and reduced sycophancy. Cybersecurity safeguards equivalent to those on Opus 4.7 and 4.8 are active, though Anthropic notes the model was not deliberately trained on cybersecurity tasks. The model is proprietary and API-only, with no open weights.
Google
Gemini 3.5 Flash
Gemini 3.5 Flash is a multimodal language model developed by Google DeepMind and released at Google I/O 2026. It is built on the Gemini 3 Flash reasoning foundation and introduces configurable thinking levels (minimal, low, medium, and high) that allow developers to tune the depth of internal reasoning before a response is generated. The model accepts text, image, video, audio, and PDF inputs and produces text output, with a 1 million token context window and up to 65,000 output tokens per request. It is natively multimodal, processing visual inputs alongside text to support tasks such as image captioning, classification, optical character recognition, object detection, and visual grounding, where the model references specific regions within an image or video frame.Its vision capabilities extend to interpreting UI screenshots, diagrams, charts, and real-world scenes, as well as understanding video and live frame sequences for activity and scene recognition. The model supports combined tool use, including Google Search, URL context, code execution, and custom functions, within a single request, and it uses reasoning context from previous turns when thought signatures are present in the conversation history, enabling persistent multi-turn reasoning chains. Gemini 3.5 Flash carries a knowledge cutoff of January 2026 and is available via the Gemini API, Google AI Studio, Google Antigravity, and the Gemini Enterprise Agent Platform.
Qwen
Qwen3.6 35B A3B
Qwen3.6-35B-A3B is a sparse Mixture-of-Experts (MoE) multimodal language model developed by the Qwen team at Alibaba Group. It carries 35 billion total parameters but activates only approximately 3 billion per forward pass via a learned routing mechanism, giving it the representational capacity of a large dense model at a fraction of the inference compute. The model is natively multimodal, processing images, documents, and video alongside text as a core architectural capability rather than an add-on. It supports a native context window of 262,144 tokens, extensible up to 1,010,000 tokens via YaRN. A key design feature is the unified thinking/non-thinking mode framework: users can switch between deliberate chain-of-thought reasoning and fast direct responses within a single model, and a "thinking preservation" option retains reasoning context across multi-turn agentic workflows to reduce redundant computation.The model is specifically optimized for agentic coding tasks, including repository-level reasoning, frontend workflow generation, multi-step tool use, and MCP (Model Context Protocol) integration. On SWE-bench Verified it scores 73.4%, on Terminal-Bench 2.0 it scores 51.5%, and on MCPMark it scores 37.0%. For vision-language tasks it achieves 92.0 on RefCOCO, 89.9 on OmniDocBench 1.5, and 83.7 on VideoMMMU. The model also supports Multi-Token Prediction (MTP) for speculative decoding. All Qwen3.6 open-weight models are released under the Apache 2.0 license.
Anthropic
Claude Sonnet 4.5
Claude Sonnet 4.5, released by Anthropic in September 2025, is the company’s most advanced Sonnet-series model, built for high-performance reasoning, coding, and long-horizon agentic workflows. It is a multimodal system that accepts both text and images, with a 200,000-token context window designed for handling large documents and extended interactions. Anthropic highlights its improvements in reliability, reduced sycophancy, and alignment, making it suitable for sustained enterprise use.The model delivers strong results in coding and autonomous workflows, achieving 61.4% on the OSWorld benchmark and leading performance on SWE-bench Verified. It introduces infrastructure features such as a memory tool (beta), checkpointing for Claude Code, parallel tool use, and tighter integration with VS Code. Compared to Opus, which targets broader reasoning, Sonnet 4.5 is optimized for structured, long-duration tasks. Positioned against leading offerings from OpenAI and Google, it is aimed at enterprise automation, software engineering, and research-intensive applications.

Other OpenAI GPT Mini models

Other versions in the same family as GPT-5.4 Mini.

GPT-5.4 Mini License

Proprietary

License terms and commercial-use guidance for GPT-5.4 Mini.

License information is provided as a guide and is not legal advice.