v2.13.3 — Parallel Multi-LLM Execution with Intelligent Merge
🚀 Core Differentiator: Parallel Ensemble (P0)
Nobody does parallel multi-LLM execution with result merging.
A3M Router runs multiple providers simultaneously, scores each result, and returns the best answer.
📊 Independent Benchmark (llm-gateway-bench)
| Scenario | TTFT | Overhead |
|---|---|---|
| Direct to Groq | 138ms | — |
| Through A3M (forced) | 234ms | +96ms |
| Through A3M (auto) | 374ms | +236ms |
Full methodology: docs/BENCHMARK.md
What's New
- Parallel Ensemble (P0) —
executeEnsemble()runs N providers in parallel, scores results - Query-Type Presets (P1) — per-task provider/temperature configuration
- Persistent Memory (P3) —
EpisodicMemoryStorewith auto-save to disk - Third-party validation — routing tiers align with MMLU benchmark rankings
- New exports:
adaptive-memory-multi-model-router/ensemble,/presets,/memory