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Streaming vs. Batch: Choosing the Right LLM Delivery Mode for Your Agents

Eli Vostok
May 07, 2026 · 2 min read
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Streaming vs. Batch: Choosing the Right LLM Delivery Mode for Your Agents

Streaming vs. Batch: Choosing the Right LLM Delivery Mode for Your Agents

Streaming every LLM response is wasteful. Batching everything adds unnecessary latency. The optimal delivery mode depends on what your agent does — and SpiderGate lets you configure this per agent, per task, or per request.

The Three Modes

Streaming

Tokens are delivered as they're generated. The agent starts processing before the full response is complete.

Best for:

Trade-offs:

Batch

The complete response is generated, then delivered as a single payload.

Best for:

Trade-offs:

Hybrid

SpiderGate buffers tokens until a semantic boundary (sentence, paragraph, or custom delimiter), then delivers in chunks.

Best for:

Configuration

agent: customer-support-bot
delivery:
  mode: streaming
  buffer_size: 0  # immediate delivery

agent: document-analyzer
delivery:
  mode: batch
  timeout: 30s

agent: report-generator
delivery:
  mode: hybrid
  chunk_boundary: paragraph
  max_buffer: 500_tokens

Performance Comparison

| Metric | Streaming | Batch | Hybrid | |--------|-----------|-------|--------| | Time to First Token | ~200ms | ~2000ms | ~500ms | | Connection Overhead | High | Low | Medium | | Cache Hit Rate | Low | High | Medium | | Error Recovery | Complex | Simple | Medium | | Cost per Request | Baseline | -5% | -3% |

When to Switch Modes

SpiderGate supports dynamic mode switching based on:


Delivery mode configuration is available in SpiderGate V2.0+.

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