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Z.ai · mid

Is GLM 5.2 good?

GLM 5.2 has been tested across 6 task areas. It's strongest at customer support and weakest at chef / home cooking. It's a mid-priced option ($3.93/1M tokens).

Top-3 finishes
6/22
Task areas tested
$3.93
Per 1M tokens
Slow
Typical speed

Strengths

Specificity Clarity Constraint adherence Concision Practicality

Weak spots

Food quality Practical sequencing Timing accuracy Explanation quality

How GLM 5.2 ranks, task by task

Rank is the position in each field; Rating is the absolute quality bar. A model can be rated "Excellent" yet sit mid-table when the whole field is strong — and vice-versa.

Task area Rank
Customer Support #12 of 104
Coding #17 of 106
AI Strategy #26 of 117
Content & Brand #26 of 115
Creative & Comedy #43 of 101
Chef / Home Cooking #52 of 117

Industry benchmarks

Standardized third-party scores, shown for context — these are independent of our real-task tests.

Headline vs. real-world

Source: Artificial Analysis (artificialanalysis.ai) via OpenRouter (openrouter.ai/rankings). (2026-07-02) · Source: Design Arena (www.designarena.ai) via OpenRouter (openrouter.ai/rankings). (2026-07-02)

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Frequently asked

Is GLM 5.2 any good?

GLM 5.2 places top-3 in 0 of 6 task areas we benchmarked. It performs best at Customer Support.

What is GLM 5.2 best at?

Its strongest task areas are Customer Support, Coding, AI Strategy.

Is there a cheaper alternative to GLM 5.2?

Gemini 3.1 Flash Lite Preview is 55% cheaper and stays competitive on quality across our benchmarks.

How we test & rank

Each model is scored on real tasks across 6 task areas by an LLM judge with deterministic checks. "Percentile" is this model's standing within each area's field; the cross-area figures are rank-based so quality and Elo scores are never mixed.

This page is Spring Prompt, running

We just did this for every model. Do it for your prompt.

The rankings above come from running real tasks through real models and scoring every output. Spring Prompt is that same engine — pointed at your prompt, your test cases, and your definition of good.

  • Generate test cases from your prompt — no eval set required to start.
  • Compare models side by side with quality, cost and latency in one matrix.
  • Optimise the winner until the scores say it's ready to ship.
Experiment · Cold outreach email

Prompt × model results

12 test cases · 3 evals
Claude Opus
GPT-5
Gemini
v1
7.1
6.8
7.4
v2
8.3
7.9
8.0
v3
9.2
8.6
8.4
Best combo: v3 × Claude Opus
9.2 quality · $0.004/run · 1.8s