GLM-130B vs Terracotta

GLM-130B puts a 130-billion-parameter bilingual language model in the open research stack THUDM built around the General Language Model (GLM) pre-training recipe. The weights target English and Chinese text, and the GitHub repo ships inference code, evaluation tasks, and checkpoints accepted at ICLR 2023. You can run left-to-right generation or blank infilling with [MASK] and [gMASK] tokens on hardware that fits a single multi-GPU server rather than a proprietary API.

Where most 100B+ models stay behind closed doors, GLM-130B publishes model weights, training notes, and YAML configs for 30+ benchmarks. Its INT4 quantization path is tuned so four RTX 3090 (24GB) cards can host inference with almost no accuracy drop, a much lower bar than the eight A100 (40GB) setup used for full FP16 runs. The training objective mixes autoregressive blank infilling on 95% of tokens with multi-task instruction data from T0++ and DeepStruct, which is a different bet than standard causal GPT-style pre-training.

Researchers studying bilingual zero-shot transfer, large-model quantization, or reproducible LLM benchmarks will get the most from GLM-130B. The repo focuses on evaluation and inference tooling rather than a hosted chat product, though THUDM later spun dialogue work into ChatGLM. Expect to bring your own GPUs, storage for a 260GB checkpoint, and patience for the weight download form.

Terracotta is an Infrastructure as Code governance tool that audits every pull request before merge, checking Terraform and OpenTofu changes against live cloud resources, remote state, and your team's governance policies. It installs as a GitHub or GitLab app, posts findings in the PR thread, and builds a tamper-evident audit trail regulators can export. The product targets platform engineering teams that need security, drift, cost, and compliance checks without rewriting CI pipelines.

Static scanners like Checkov or tfsec lint HCL syntax and known misconfigurations, but they never compare a plan to what is actually running in AWS. Terracotta closes that gap by correlating code, Terraform state, and live resources so drift, cross-PR conflicts, and hidden blast radius show up before anyone clicks merge. Its guardrails are written in plain English rather than Rego or Sentinel, which lowers the bar for teams that lack a dedicated policy-as-code engineer.

DevOps leads and platform engineers at regulated shops use Terracotta to block public S3 buckets, open SSH rules, and unapproved cost spikes at review time instead of in production. Security and compliance teams get a fleet-wide dashboard with drift posture, policy compliance rates, and exportable records for SOC 2 or HIPAA audits. Developers keep working inside GitHub or GitLab because findings arrive as PR comments, not another portal to check.

Beacon, Terracotta's in-PR chat assistant, answers questions about specific findings using context from the repo, plan output, and drift reports. The Platform tier adds unlimited drift repos, IAM and blast-radius analysis, Slack notifications, and a command center dashboard for $49 per engineer per month. Enterprise customers can run Terracotta self-hosted with SSO, SAML, and custom integrations for HCP Terraform or CircleCI.