OpenAI Platform Review

The OpenAI Platform (platform.openai.com, with docs at developers.openai.com) is where developers create API keys, buy credits and call OpenAI's models. The current lineup is led by GPT-6 Astra, which OpenAI calls its most capable model, GPT-6.1 Sol for near-Astra work at lower cost, GPT-6.1 Terra for visual reasoning and computer use, and GPT-6 Luna for cheap, high-volume tasks. All four take text and image input, return text, and list a 1,050,000-token context window with up to 128,000 output tokens. Beside them sit the GPT-Image models, GPT-Realtime and GPT-Live voice models, transcription and text-to-speech, embeddings, a free moderation model and the open-weight gpt-oss models.

The main interface is the Responses API, with Chat Completions still supported, plus Batch, Realtime and an Agents API. Hosted tools include web search, file search and containers for code execution, each billed per call or per session on top of tokens. You sign in, add a payment method, buy prepaid credits and your organization moves up usage tiers (and rate limits) as total purchases grow. Two things are winding down: the Assistants API (removal date August 26, 2026, per OpenAI's deprecations page) and self-serve fine-tuning, which no longer accepts new organizations.

There is no subscription: you pay per token (or per minute, call or session) from prepaid credits. Your usage tier and monthly usage limit rise with total credit purchases.

Standard prices per 1M tokens for prompts up to 272K input tokens:

Above 272K input tokens the GPT-6 models cost 2x input and 1.5x output for the whole request (GPT-6 Astra: $20 / $75). Batch and Flex are 50% of standard; Fast mode (formerly Priority) is 2x. Writing to the prompt cache costs 1.25x the input rate. Regional data-residency endpoints add 10% for models released on or after March 5, 2026, and FedRAMP endpoints add 10% from November 1, 2026.

Other meters: GPT-Image-2 is $8 input / $30 output per 1M image tokens; GPT-Live 1 voice sessions are $0.05 per minute; GPT-Transcribe is about $0.0045 per minute and Whisper $0.006 per minute; web search is $10 per 1,000 calls plus content tokens; file search is $2.50 per 1,000 calls plus $0.10 per GB per day of storage after 1 GB free.

Worked example: 1M input plus 1M output tokens costs $0.10 + $0.50 = $0.60 on GPT-6 Luna, $2 + $10 = $12 on GPT-6.1 Sol and $10 + $50 = $60 on GPT-6 Astra; the same jobs through Batch cost $0.30, $6 and $30. ChatGPT Pro and Business owners can claim $20 to $500 a month of API credits as a subscription benefit; unused credits expire each billing cycle.

Prices checked on the vendor's pricing page on November 2, 2026. See OpenAI API pricing.

What OpenAI documents on its developer platform:

It suits developers and companies who want OpenAI's own models first-hand: apps that need GPT-6-class reasoning, long-context document work, image generation, or low-latency voice agents, all under one key and one bill. GPT-6 Luna at $0.10 / $0.50 per million tokens makes it a reasonable default for high-volume classification and extraction too.

Look elsewhere if you want models from several labs behind one key: OpenRouter routes to many providers. For Claude models, use Anthropic's API; for Gemini, Google's Gemini API. If you mainly need cheap, fast open models, Groq is cheaper per token for what it hosts. Teams that already buy cloud through AWS or Azure can get OpenAI models billed through Amazon Bedrock or Microsoft Azure instead.

Independent coverage of the GPT-6 API is mostly pricing explainers rather than hands-on reviews. Two guides that repeat the $10 / $50 per million token list price for Astra, eesel AI's GPT-6 Astra pricing guide and Yotta Labs' cost breakdown, both come from companies selling their own AI products (a helpdesk agent and an AI gateway), so read them as vendor content. Both flag the surcharge above 272K input tokens, which bills the whole request at $20 / $75. Their shared advice: send routine traffic to cheaper models such as Luna, keep requests under 272K tokens, and use Batch or Flex for anything that can wait. We did not find an independent benchmark or reliability review of the GPT-6 API that we could cite, so treat performance claims as OpenAI's own until you test on your workload.