GLM-5.2 vs Claude Sonnet 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 Claude Sonnet 5, side by side, on 42 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.

Claude Sonnet 5 · Reach for it in Agent OS when the job is iterative, tool-using software engineering. For one-shot visual builds, GLM 5.2 (free) beat it 4-1 here.

Where GLM-5.2 beat Claude Sonnet 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 Claude Sonnet 5 beat GLM-5.2

The tasks where I gave Claude Sonnet 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 42 scored shared tasks, GLM-5.2 averaged 7.77/10, beating Claude Sonnet 5's 7.18/10 by 0.59 points. Pick GLM-5.2 when the build has to ship on the first prompt and you can afford the trade-offs in the comparison below.

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 Claude Sonnet 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, agentic software engineering — write / run / test / fix loops on real repos → Claude Sonnet 5. That's the same setup I run for the 3,600+ founders inside the AI Profit Boardroom.

FAQ — GLM-5.2 vs Claude Sonnet 5

Which is better, GLM-5.2 or Claude Sonnet 5?

On Goldie Bench, GLM-5.2 averages 7.77/10 across the shared tasks, with 5 gold, 2 silver, 1 bronze overall. Claude Sonnet 5 averages 7.18/10, with 3 gold, 3 silver, 3 bronze. Claude Sonnet 5 wins the head-to-head 22–19.

How much does GLM-5.2 cost vs Claude Sonnet 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). Claude Sonnet 5: $3.00 input / $15.00 output per million tokens; introductory $2.00/$10.00 through 2026-08-31.

What's the context window for GLM-5.2 vs Claude Sonnet 5?

GLM-5.2 has a 1,000,000 tokens context window. Claude Sonnet 5 has a 1,000,000 tokens context window.

When should I pick GLM-5.2 over Claude Sonnet 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 Claude Sonnet 5 over GLM-5.2?

Pick Claude Sonnet 5 for: Agentic software engineering — write / run / test / fix loops on real repos; Repo-level reasoning across a 1M-token context (Dev Team multi-agent mode); Precise logic — raycasters, physics — where one-shot open models slip. The trade-off is the weaknesses we logged on the bench: One-shot creative-visual builds trail GLM 5.2 here (lost 4 of 5) — no iteration to catch its own bugs; A temporal-dead-zone bug blanked its N-body orbit sim on the first shot.

How does Goldie Bench score GLM-5.2 vs Claude Sonnet 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 · Claude Sonnet 5 · back to the leaderboard