docs/dream-cycle/2026-06-15-performance-sota.md
TL;DR: Arbor's tree-search cognition layer delivers +193% inference throughput-latency Pareto improvement (arXiv June 2026); Ruflo has no equivalent tier, and its Flash Attention claim (2.49x–7.47x) remains unverified against any 2026 benchmark.
This report covers 2026 SOTA for the Ruflo Dream Cycle nightly research session, benchmarking performance, security (scan), and hive-mind (scan) surfaces against LangGraph, AutoGen, CrewAI, and OpenAI Swarm.
| Finding | Source | Confidence |
|---|---|---|
| MiniMax Sparse Attention: 28.4× attention compute reduction, 14.2× prefill, 7.6× decode on H800 | arXiv 2026-06-11 | A |
| Arbor tree-search cognition layer: +193% throughput-latency Pareto over vendor-optimized baseline (+33% without harness) | arXiv 2026-06-10 | B (arXiv abstract; paper ID unconfirmed) |
| ITME CXL-hybrid memory: +35.7% throughput for TB-scale long-context agent workloads | arXiv 2026-06-10 | A |
| FlowBank query-adaptive workflow portfolio: +4.26% over strongest automated baselines, +14.92% relative over handcrafted | arXiv 2026-06-09 | A |
| Kimi K2.6: 300-agent swarm coordinating 4,000+ tool calls over 12h; raised Qwen 3.5-0.8B from 15→193 tok/s in Zig | Vendor/press 2026 | B (crosschecked in press coverage) |
| LangGraph 1.0 GA: node-level caching, DeltaChannel incremental state; fastest latency in independent benchmarks | LangChain changelog 2026 | B |
| Capability | Status | Notes |
|---|---|---|
| Flash Attention speedup | Unverified | 2.49x–7.47x claimed; no benchmark exists |
| HNSW search | Measured 1.9x–4.7x | vs brute force at N≥5k (NAPI backend) |
| Int8 quantization | Measured 3.84x | reconstruction cosine 0.99999 |
| 3-tier model routing | Implemented | Tier-1 codemod / Tier-2 Haiku / Tier-3 Sonnet/Opus |
| Tree-search inference optimization | Missing | No cognition layer for per-query hardware tuning |
| CXL/hybrid context offload | Missing | Max context bounded by GPU VRAM |
| Inference-time workflow portfolio | Partial | FlowBank approach not implemented |
| SONA adaptation | Measured 0.0043ms | Target <0.05ms met |
| Framework | Latency | Token Overhead | Complex Task Success | 2026 Notable Change |
|---|---|---|---|---|
| LangGraph 1.0 | Fastest (GA) | Low | 62% | Node caching, DeltaChannel, full GA stability |
| AutoGen | ~2.1s (slowest) | +24% | 58% | Shifting dev focus to MS Agent Framework |
| CrewAI 0.28+ | Medium | +18% | 54% | 30–60% faster vs 2025; 34% fewer tokens (C) |
| OpenAI Swarm | Lowest latency | Low | N/A (experimental) | Still no production-ready release |
| Ruflo 3.6.10 | Unmeasured | Unknown | Unknown | Flash Attention unverified; 3-tier routing active |
| Benchmark | Result | Grade | Source |
|---|---|---|---|
| MiniMax Sparse Attention prefill speedup | 14.2× on H800 | A | arXiv 2026-06-11 |
| MiniMax Sparse Attention decode speedup | 7.6× on H800 | A | arXiv 2026-06-11 |
| MiniMax per-token attention compute reduction | 28.4× at 1M context | A | arXiv 2026-06-11 |
| Arbor tree-search Pareto throughput improvement | +193% vs vendor baseline | B | arXiv 2026-06-10 (abstract) |
| ITME CXL throughput gain | +35.7% | A | arXiv 2026-06-10 |
| Ruflo Flash Attention | 2.49x–7.47x | no 2026 data | No benchmark run |
| LangGraph complex-task completion | 62% | C | Industry benchmark 2026 (single source) |
| Field | Value |
|---|---|
| Session commit | 28c81c03e3e84555a9238b3217b9f586fc0c7dbc |
| Report SHA-256 | dd6ad0aa21f20738319e36197f6aa22eb5890c0c2c80d5969dd7d5550d9eecda |
| Witness stamp | a3de6fc925a502c0737c67d90d3544c9f2304a451e6266c8c6ca17c3750d7bcd |
| Verifier | sha256(pre-stamp-gist) → concat("28c81c03e3e84555a9238b3217b9f586fc0c7dbc") → sha256 → must equal a3de6fc925a502c0737c67d90d3544c9f2304a451e6266c8c6ca17c3750d7bcd |
Finding: VIPER-MCP (arXiv 2026-05-20) discovered 106 zero-day vulnerabilities and 67 CVEs across 39,884 MCP repositories via taint-style analysis; Ruflo's 314 MCP tools represent one of the largest per-agent MCP attack surfaces in the ecosystem. Additionally, AbO-DDoS (arXiv 2026-05-11) demonstrated 51.0× call amplification via recursive Möbius injection into a single agent node—directly relevant to Ruflo's swarm topology where recursive tool chains are common.
Competitive signal: "Blind Spots in the Guard" (arXiv 2026-05-21) shows detection drops from 93.8% to 9.7% with domain-camouflaged payloads—Llama Guard 3 detects zero camouflaged payloads.
Finding: "Byzantine Cheap Talk" (arXiv 2026-06-05) shows non-Byzantine agents fail to adapt collectively after betrayal, and communication topology disclosure degrades cooperation even without an active adversary. Ruflo's raft consensus broadcasts topology openly—agents always know the full member list—which per this paper reduces cooperation quality in non-adversarial scenarios.
No 2026 arXiv papers found under "hive-mind collective intelligence queen-led consensus" — evidence that hive-mind coordination language is proprietary to Ruflo; academic community uses "Byzantine fault-tolerant" or "federated agent coordination" terminology.
ADR-158 (this session): Add Tier-4 tree-search cognition layer to the 3-tier model routing system. For Tier-3 tasks estimated >5s, invoke an Arbor-style tree-search pass that autonomously selects the optimal inference configuration (batch size, attention kernel, KV-cache policy) before dispatching to Sonnet/Opus. Target: narrow the 193% Pareto gap to <50% within two sprints.
Flash Attention audit (immediate): Extend scripts/benchmark-intelligence.mjs to include Flash Attention on available hardware. Either confirm the 2.49x–7.47x claim with a Grade A benchmark or remove the claim from CLAUDE.md and v3/CLAUDE.md. MiniMax's 14.2× prefill (Grade A) sets the credible upper bound; Ruflo's unverified claim sits at less than half that—it must be measured or retracted.
MCP taint audit (sprint priority): Run VIPER-MCP methodology against Ruflo's 314 MCP tools—prioritize tools with file-system or shell access first. Each tool should require at minimum: input sanitization via @claude-flow/security InputValidator, rate-limiting to prevent 51× call amplification, and explicit trust-level declaration in plugin manifest.