Streaming vs Batch LLM Processing: Which to Choose?
Use streaming for user-facing interfaces where perceived responsiveness matters. Use batch for background processing, bulk analysis, and workflows where 24-hour turnaround is acceptable — batch APIs typically cost 50% less. Use both in the same application for different endpoints.
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FAQ
How much cheaper is the Batch API?+
Both OpenAI and Anthropic's Batch APIs offer exactly 50% off standard API pricing. For GPT-4o: $2.50/$10 per 1M tokens standard → $1.25/$5 per 1M batch. For Claude Sonnet 4: $3/$15 per 1M tokens standard → $1.50/$7.50 per 1M batch. At 10M output tokens/month, that's a savings of $50/month (Sonnet) to $25/month (GPT-4o) — significant at scale.
What is the Vercel AI SDK and should I use it?+
The Vercel AI SDK is a TypeScript library that abstracts streaming across OpenAI, Anthropic, Google, and other providers. It provides useChat/useCompletion hooks for React, built-in streaming UI components, and a unified API surface. It's the recommended choice for Next.js applications. It handles the complexity of SSE streaming, token counting, and provider differences behind a clean interface.
Can I stream JSON output?+
Yes, with some care. Both OpenAI and Anthropic support streaming with structured/JSON output modes. You receive partial JSON chunks as they're generated. Parse them progressively with a streaming JSON parser. A common pattern: accumulate the full string, then parse on completion. For UI rendering, extract complete key-value pairs from the accumulating string using regex or a partial JSON parser like 'partial-json'.
What is the token limit for batch requests?+
OpenAI Batch API allows up to 50K requests per batch file with a 90,000 token per minute limit per batch (the limit resets hourly). Anthropic Message Batches allows up to 100K requests per batch with a 250,000 tokens per minute aggregate limit. Both use the same per-token context limits as the standard API (e.g., 128K for GPT-4o, 200K for Claude Sonnet 4).