LLMs

Compare Voyage, OpenAI and open-weight embeddings on BEIR, code and finance benchmarks with per-million bills, proving domain models win by 8 points in tests.

Route open-weight inference across DeepInfra and Together AI with live price checks and cache math, cutting monthly model bills 41% in staging tests.

Test GPT OSS 20b at $0.02 per million against DeepSeek V3 on coding and MMLU Pro. Open-weight routing cuts task cost by 92%. Full benchmark inside.

Cisco reports 85% of enterprises pilot AI agents but only 5% reach production. Benchmark the trust gap across reliability, observability, and governance.

Route test-time compute by difficulty: match best-of-16 accuracy within 0.01 points at 58.9% fewer tokens with calibrated early stopping and halved latency.

Settle the stuff-vs-retrieve debate with measurements: 8K effective windows lose to graded RAG, and a Self-Route hybrid holds quality at 34% of cost.

Compare BFCL v4 scores per dollar — Opus 77.5% vs Haiku 68.7% vs GLM-4.6 value — and deploy a cheap-first router that keeps 98.6% accuracy at 16% cost.

Settle Claude Code versus Gemini 3.8 Flash with Terminal-Bench version truth, DeepSWE near-tie math and a task-shape routing rule for production.

Compare FP8, BF16 and INT4 on 100K-token local agent replays with KV-cache tests that explain tool-call breaks and halve GPU memory in production.

Discover how reasoning models waste tokens on tool calls and how hybrid routing to instruct models cuts agent bills by 5x with zero accuracy loss.

The Multi-Agent LLM Financial Trading Framework that scored 75 points on Hacker News uses four specialized LangGraph agents: market analysis, risk scoring, trade execution, and audit. This article provides full benchmark analysis across 6 months of backtesting, comparing the multi-agent approach against traditional quant strategies, single-agent bots, and buy-and-hold baselines.

The 47-point HN story 'The VMs Powering Mobile Agents' revealed that Firecracker microVMs are the critical infrastructure behind reliable mobile coding agents. This article provides the full architectural analysis: sub-second cold starts (125ms boot, 475ms total), hardware-level isolation preventing state leakage, and the warm-pool pattern that enables 150ms task-to-task switching.