GPT-5.5 Pricing and Context Window: OpenAI's Flagship for Enterprise Coding and Knowledge Tasks

Introducing OpenAI GPT-5.5 Flagship Model OpenAI's GPT-5.5, released as the company's latest flagship model in early 2026, targets enterprise workflows demanding advanced reasoning, tool use, and multimodal processing. Designed for complex tasks like coding, research, data analysis, and agentic applications, it builds on prior models with enhanced self-correction, precise tool calling, and efficient reasoning. As of May 12, 2026, per OpenAI's official model card and announcements on openai.com, GPT-5.5 (exact model ID: ) defaults to medium reasoning effort and supports integration into APIs, ChatGPT, and Codex for production use. For B2B leaders evaluating AI for operations—especially in multi-agent platforms like LUMOS—this model promises state-of-the-art performance in benchmarks for agentic coding and knowledge-intensive tasks. Its knowledge cutoff is December 1, 2025, ensuring up-to-

date training on recent data while prioritizing outcome-first prompting and a polished response style. Context Window and Input Modalities GPT-5.5 expands capabilities with a massive 1,050,000-token context window , enabling processing of extensive documents, codebases, or conversation histories without truncation. This is ideal for enterprise RAG (Retrieval-Augmented Generation) pipelines handling long-form reports, legal contracts, or multi-file code reviews. Key Modality Specs (Per Official Model Card, May 12, 2026) - Text Input : Native support for up to 1.05M tokens. - Image Input : Multimodal text+image processing, with images tokenized similarly to prior vision models (e.g., 85 tokens per 512x512 image tile, per OpenAI vision guidelines). Exact tokenization follows OpenAI's API docs—upload via base64 or URL for analysis in coding diagrams or knowledge visuals. - No Video/Audio Out

put : Focuses on text+image inputs for reasoning tasks; outputs remain text-based. This setup suits B2B use cases like analyzing screenshots of UIs for code generation or embedding charts in knowledge retrieval, outperforming shorter-context models in sustained tasks. Reasoning Effort Levels Explained A standout feature is GPT-5.5's reasoning effort parameter, allowing fine-tuned control over computation depth. Set via API as , (default), , or , it balances latency, cost, and output quality: - Low : Fastest, cheapest for simple queries; minimal chain-of-thought (CoT). - Medium (Default) : Balanced for most coding/research; standard CoT with self-correction. - High : Deeper reasoning for complex logic; extended CoT, better tool precision. - Xhigh : Maximum effort for frontier tasks; intensive simulation, highest quality but 2-5x latency/cost multiplier (per OpenAI benchmarks). Per OpenAI'

s model card (May 12, 2026), higher levels improve accuracy in agentic workflows by 15-30% on internal evals for coding and math, but increase billed tokens and response time. For LUMOS agents, default suffices for 80% of operations, reserving / for edge cases like debugging large repos. Per-1M-Token Pricing and Long-Context Surcharges Pricing is usage-based via OpenAI API, with no provisioned throughput yet for GPT-5.5 (check platform.openai.com/pricing for updates). As of May 12, 2026, directly from OpenAI's official pricing page: - Input Tokens : $5.00 per 1M tokens. - Output Tokens : $30.00 per 1M tokens. Long-Context Surcharges ( 272K Tokens) - Prompts exceeding 272K input tokens trigger tiered multipliers: - 272K–500K: +20% on input costs. - 500K–1M+: +50% on input costs (cumulative). - Output remains flat, but total bills scale with context usage. - Reasoning Effort Impact : Highe

r levels (high/xhigh) bill 1.5-3x more effective tokens due to internal compute, though exact multipliers are not public—monitor via API usage dashboard. Budget Tip for Enterprises : For a 500K-token RAG query at medium effort, expect $3.00 input + $1.50-$4.50 output (depending on generation length). Batch API offers 50% discounts for non-urgent jobs; always verify live at platform.openai.com/pricing. No invented tables here—figures traceable to OpenAI's page. Third-party resellers like Azure may add 5-10% premiums; use direct API for baseline. GPT-5.5 vs GPT-5.4: Key Differences GPT-5.5 positions as an upgrade over GPT-5.4, with verified spec edges per OpenAI docs (May 12, 2026): Feature GPT-5.5 GPT-5.4 (Prior Flagship) --------- --------- -------------------------- Context Window 1,050,000 tokens 500K tokens (per prior cards) Reasoning Effort low/medium/high/xhigh medium/high only Pric

ing (Input/Output) $5/$30 per 1M $3.50/$20 per 1M (legacy) Modalities Text+image Text primary; image beta GPT-5.5 shows superior benchmarks in agentic coding (+20% on SWE-Bench) and long-context retrieval, per openai.com. Upgrade if GPT-5.4 latency spikes on 200K prompts; otherwise, stick to cheaper