gpt-4o

GPT-4o ("omni") is OpenAI's flagship multimodal model — a unified replacement for the separate GPT-4 Turbo text and GPT-4V vision pipelines. The "omni" designation reflects its native handling of text, images, and audio in a single model rather than routing inputs through separate specialist modules. It delivers GPT-4 Turbo-level intelligence at roughly half the price and with meaningfully lower latency — a combination that made it the default choice for the majority of production OpenAI deployments. It supports a 128K-token context window, function calling, structured outputs, and streaming, and is available across OpenAI's API and the ChatGPT interface.

GPT-4o is priced at $2.50 per million input tokens and $10.00 per million output tokens, with prompt caching reducing repeated input to $1.25/1M — a 50% discount that compounds significantly for applications with long shared system prompts or document Q&A patterns. At a typical usage pattern of 1,000 input tokens and 500 output tokens per call, GPT-4o costs approximately $0.0075 per 1,000 API calls. The 4:1 output-to-input price ratio is standard for OpenAI's frontier models and reflects the sequential compute cost of autoregressive generation.

GPT-4o's 128K-token context window handles documents up to roughly 96,000 words — a full novel or a large codebase — in a single API call. Median time-to-first-token (P50 latency) is approximately 320ms under typical load, making it fast enough for interactive chat and real-time applications. Throughput is around 110 tokens per second, sufficient for streaming responses at comfortable reading speed. Maximum output length is 16,384 tokens, which covers most generation tasks including detailed code files, long-form essays, and structured reports. For latency-critical applications, GPT-4o mini (a smaller, faster variant) offers sub-200ms TTFT at a fraction of the cost, though with reduced capability on complex reasoning tasks.

GPT-4o is best suited to applications requiring a balance of capability, cost, and multimodal input: customer-facing chat assistants, document analysis, code generation and review, vision-based workflows (screenshot understanding, diagram interpretation, OCR), and agentic pipelines that combine function calling with multi-step reasoning. Its function calling implementation is among the most mature in the industry, with reliable JSON schema adherence and support for parallel tool calls — making it a strong default for agent frameworks like LangChain, LlamaIndex, and AutoGen. Vision support processes images at a cost of approximately 85–170 tokens per image tile depending on resolution, billed at the standard input rate.

GPT-4o sits at the top of OpenAI's production model lineup, positioned between the cost-optimized GPT-4o mini (efficient tier) and the reasoning-specialized o-series (o3, o4-mini). For tasks requiring deep multi-step reasoning — complex math, competitive programming, scientific analysis — the o3 or o4-mini models use extended chain-of-thought processing and carry higher per-token costs. For high-volume, lower-complexity tasks, GPT-4o mini delivers 80–90% of GPT-4o's quality at roughly 6% of the cost. GPT-4o's sweet spot is the broad middle ground: tasks complex enough to need frontier capability but not so specialized that reasoning models' latency and cost premium are justified. Its intelligence score of approximately 85/100 reflects strong general-purpose capability.