GLM-5.2 Benchmark: The New Open-Weight Leader (2026)
GLM-5.2 benchmark analysis: Z.ai's 753B MoE under MIT license, coding and agentic results vs GPT-5.5 and MiniMax M3, cost-per-token, and where it fits.
LLM JSON Mode: A Structured-Output Benchmark (2026)
A 2026 benchmark of LLM JSON mode and constrained decoding: throughput, latency, and accuracy across grammar-based methods, with reproducible methodology.
FP8 vs INT8 vs INT4 LLM Quantization Benchmark (2026)
A 2026 LLM quantization benchmark comparing FP8, INT8, and INT4: accuracy retention, throughput, memory, and when each precision is the right call.
On-Device SLM Inference: A 2026 Edge GPU Benchmark
A 2026 benchmark methodology for small language models on edge GPUs — latency, tokens/sec, memory, and cost for Phi, Gemma, and Qwen on Jetson-class hardware.
SGLang vs vLLM vs TensorRT-LLM: 2026 Inference Benchmark
Reproducible 2026 benchmark of SGLang, vLLM, and TensorRT-LLM — throughput, p50/p99, KV cache utilization, and when each wins.
Agent Framework Benchmark: LangGraph, OpenAI SDK, Google ADK (2026)
Benchmark of four agent frameworks — LangGraph, OpenAI Agents SDK, Google ADK, CrewAI — across latency, durability, and tool-orchestration patterns.
Q2 2026 Open-Source Embedding Models Benchmark: BGE, GTE, E5, Stella, Nomic
Q2 2026 open-source embedding models benchmarked — BGE-M3, GTE-Qwen2, E5-Mistral, Stella, Nomic on MTEB plus latency, memory, and industrial retrieval tasks.