Compare long-context model APIs by window size, price, source, and when a big context is actually worth paying for.
Long context helps when you stuff contracts, exports, support history, or large files into the prompt. It also makes bills jump. Compare window size and input price together, and decide whether retrieval would be cheaper than stuffing the whole document every time.
Base della fonte: NextModel curated catalog and OpenRouter context metadata when available. · Aggiornato 2026-07-01
Context
Parti dalla shortlist, poi testa prompt reali e confronta il costo mensile prima del routing in produzione.
GPT-5.4 is OpenAI’s latest frontier model, unifying the Codex and GPT lines into a single system. It features a 1M+ token context window (922K input, 128K output) with support for...
GPT-5.4 Pro is OpenAI's most advanced model, building on GPT-5.4's unified architecture with enhanced reasoning capabilities for complex, high-stakes tasks. It features a 1M+ token context window (922K input, 128K...
GPT-5.5 is OpenAI’s frontier model designed for complex professional workloads, building on GPT-5.4 with stronger reasoning, higher reliability, and improved token efficiency on hard tasks. It features a 1M+ token...
GPT-5.6 Luna is a fast, cost-efficient model in OpenAI's GPT-5.6 series. It is suited for high-volume, latency-sensitive tasks such as chat, classification, and lightweight agentic workflows, providing capable reasoning for...
Tabella comparativa
Usa questa vista per restringere una shortlist di produzione, costruire una strategia di fallback o confrontare l'economia dei modelli.
| Model | Provider | Input | Output | Context | Capabilities | Best for | Latency | Status | Source |
|---|---|---|---|---|---|---|---|---|---|
| OpenAI: GPT-5.4openai/gpt-5.4 | OpenAI | $0.362 / 1M tokens | $2.17 / 1M tokens | 1.1M | StreamingTool callingJSON modeVision | image understanding, multimodal chat | 1000-3000ms | Catalog | Platform curated |
| OpenAI: GPT-5.4 Proopenai/gpt-5.4-pro | OpenAI | $4.34 / 1M tokens | $26.04 / 1M tokens | 1.1M | StreamingTool callingJSON modeVision | image understanding, multimodal chat | 1000-3000ms | Catalog | Platform curated |
| OpenAI: GPT-5.5openai/gpt-5.5 | OpenAI | $0.723 / 1M tokens | $4.34 / 1M tokens | 1.1M | StreamingTool callingJSON modeVision | image understanding, multimodal chat | 1000-3000ms | Catalog | Platform curated |
| OpenAI: GPT-5.6 Lunaopenai/gpt-5.6-luna | OpenAI | $0.029 / 1M tokens | $0.174 / 1M tokens | 1.1M | StreamingTool callingJSON modeVision | image understanding, multimodal chat | 1000-3000ms | Catalog | Platform curated |
| OpenAI: GPT-5.6 Solopenai/gpt-5.6-sol | OpenAI | $0.723 / 1M tokens | $4.34 / 1M tokens | 1.1M | StreamingTool callingJSON modeVision | image understanding, multimodal chat | 1000-3000ms | Catalog | Platform curated |
| OpenAI: GPT-5.6 Terraopenai/gpt-5.6-terra | OpenAI | $0.289 / 1M tokens | $1.74 / 1M tokens | 1.1M | StreamingTool callingJSON modeVision | image understanding, multimodal chat | 1000-3000ms | Catalog | Platform curated |
| Google: Gemini 2.5 Flashgoogle/gemini-2.5-flash | $0.043 / 1M tokens | $0.362 / 1M tokens | 1M | StreamingTool callingJSON modeVision | image understanding, multimodal chat | 1000-3000ms | Catalog | Platform curated | |
| Google: Gemini 3 Flash Previewgoogle/gemini-3-flash-preview | $0.072 / 1M tokens | $0.434 / 1M tokens | 1M | StreamingTool callingJSON modeVision | image understanding, multimodal chat | 1000-3000ms | Catalog | Platform curated |
FAQ
No. Bigger windows help with big inputs. Cost, latency, retrieval design, and answer quality still decide whether it is a good idea.
When most of the document is irrelevant to each question. Pull the useful chunks, send less context, and keep a smaller model if quality holds.
Multiply average input tokens (including stuffed documents) by input price, then add output. Long inputs dominate the bill more often than people expect.
Classifiche