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.
A 2026 benchmark of LLM JSON mode and constrained decoding: throughput, latency, and accuracy across grammar-based methods, with reproducible methodology.
A 2026 text-to-SQL benchmark methodology: execution accuracy, schema linking, latency, and cost across model tiers - plus where generated SQL goes wrong.
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.