GLM-5.2 vs Grok 4.5

What I tested — same prompt, two models

I run the same fixed prompt set through every new model the day it drops — same string, one shot, single HTML file out — and I score the result 0–10 on whether it ran, how close it hit the brief, and how good it looked. Below is what came out when I gave the exact same prompts to GLM-5.2 and Grok 4.5, side by side, on 46 shared tasks inside the Agent Operating System.

Both models were given identical prompts inside the Agent Operating System — no help, no iteration, no "best of N" tricks. I run each prompt once, save the HTML file the model produces, and score it 0–10 on whether it ran, how close it hit the brief, and how good it looked. The scoring is mine. The verdicts below are pulled from my source comparison guides at agentos.guide where I publish every score and the reasoning behind it.

GLM-5.2 · Default model inside Agent OS for any task that touches a long context — codebase Q&A, multi-file refactors, agent memory replay.

Grok 4.5 · Benched one-shot on the same GoldieBench game prompts as the field, with the threejs-game-director patterns baked into each prompt; weak builds iterated by Grok 4.5 itself (the model authors every fix, never hand-patched). Wired into the Agent OS as the newest engine.

Where GLM-5.2 beat Grok 4.5

The tasks where I gave GLM-5.2 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.

Where Grok 4.5 beat GLM-5.2

The tasks where I gave Grok 4.5 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.

Strengths & weaknesses I logged

Pricing & context — the spec sheet

The verdict — which should you pick?

Across 46 scored shared tasks, the averages are essentially tied — GLM-5.2 7.76 vs Grok 4.5 7.61. This isn't the comparison where one wins; it's the comparison where you pick based on context, pricing, and what you're actually trying to ship.

If you only run one of these inside your stack, the head-to-head average above is the call. If you can run both, my honest play is to wire GLM-5.2 and Grok 4.5 both into the Agent Operating System and dispatch each from the kanban by task type — long-context agent loops — pasting a whole codebase into one prompt → GLM-5.2, one-shot end-to-end app + game builds from a single prompt → Grok 4.5. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.

FAQ — GLM-5.2 vs Grok 4.5

Which is better, GLM-5.2 or Grok 4.5?

On Goldie Bench, GLM-5.2 averages 7.76/10 across the shared tasks, with 5 gold, 4 silver, 1 bronze overall. Grok 4.5 averages 7.61/10, with 12 gold, 34 silver, 2 bronze. GLM-5.2 wins the head-to-head 26–18.

How much does GLM-5.2 cost vs Grok 4.5?

GLM-5.2: Open-weights release: weights downloadable from Hugging Face for self-hosting, or runnable for free on z.ai for individuals (commercial use has separate licensing). Grok 4.5: ~4.2x fewer output tokens than Opus 4.8 on SWE-Bench Pro (15,954 vs 67,020 avg) and served at ~80 TPS, so real cost/latency is well below the sticker. Free for a limited time in Grok Build + Cursor.

What's the context window for GLM-5.2 vs Grok 4.5?

GLM-5.2 has a 1,000,000 tokens context window. Grok 4.5 has a xAI's smartest model, built for coding + agentic tasks; trained alongside Cursor. Default model in Grok Build. Benched here via OpenRouter (x-ai/grok-4.5). context window.

When should I pick GLM-5.2 over Grok 4.5?

Pick GLM-5.2 for: Long-context agent loops — pasting a whole codebase into one prompt; Cinematic visual builds — landing pages, voxel scenes, synthwave runners; Anyone who needs to run a frontier coder locally for $0. The trade-off is the weaknesses we logged on the bench: Faceplanted on the {{SITE_NAME}} raycaster — the engine was great but it spawned the player inside a wall; First-shot reliability lags Opus by a hair on consistency.

When should I pick Grok 4.5 over GLM-5.2?

Pick Grok 4.5 for: One-shot end-to-end app + game builds from a single prompt; Cost/latency-sensitive agentic coding loops (token-efficient + fast); Office-work automation (Excel/PowerPoint/Word via Grok Build). The trade-off is the weaknesses we logged on the bench: Raycaster/FPS (doom) under-renders + walks out of bounds one-shot; needed multiple self-fix passes; Occasional TDZ/init bug blanks a build to black (racing) — recovered by the model itself in one pass; Not available in the EU until mid-July 2026.

How does Goldie Bench score GLM-5.2 vs Grok 4.5?

Every demo on this page was built by Julian Goldie inside the Agent Operating System — same fixed prompt for both models, one shot, single HTML file out. Each result gets a 0–10 score on whether it ran, how close it hit the brief, and how good it looked. The highest score on each task gets gold; second gets silver; third gets bronze. See methodology for full provenance.

Related comparisons

Other head-to-heads using the same scoring system:

Full model pages: GLM-5.2 · Grok 4.5 · back to the leaderboard