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Z.ai · mid

Is GLM 5.1 good?

GLM 5.1 has been tested across 6 task areas. It's strongest at investor & pitch and weakest at executive assistant. It's a mid-priced option ($5.275/1M tokens).

Top-3 finishes
6/22
Task areas tested
$5.275
Per 1M tokens
Slow
Typical speed

Our take

Z.ai: GLM 5.1 is a mid-tier model that we tested across 6 task areas. It performs best at Investor & Pitch, and is weakest at Chef / Home Cooking.

Strengths

Specificity Concision Risk handling Tone Practicality Risk detection

Weak spots

Structure Timing accuracy Source of truth quality Practical sequencing Tone control Action quality

How GLM 5.1 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
Investor & Pitch #18 of 50
Chef / Home Cooking #24 of 50
AI Strategy #33 of 50
Landing Pages #38 of 56
Content & Brand #40 of 50
Executive Assistant #41 of 50

Industry benchmarks

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

Artificial Analysis indices

40.2
Intelligence
55.8
Coding
29.9
Agentic

Design Arena — human preference (avg Elo 1298)

3d 1336 svg 1286 dataviz 1324 gamedev 1340 website 1290 asciiart 1179 uicomponent 1292 codecategories 1333

Headline vs. real-world

GLM 5.1 looks strong on paper but underperforms on our real-world tasks relative to its Intelligence Index.

Source: Artificial Analysis (artificialanalysis.ai) via OpenRouter (openrouter.ai/rankings). (2026-06-29) · Source: Design Arena (www.designarena.ai) via OpenRouter (openrouter.ai/rankings). (2026-06-29)

Like GLM 5.1, but…

Cheaper

Smarter

Frequently asked

Is GLM 5.1 any good?

GLM 5.1 places top-3 in 0 of 6 task areas we benchmarked. It performs best at Investor & Pitch.

What is GLM 5.1 best at?

Its strongest task areas are Investor & Pitch, Chef / Home Cooking, AI Strategy.

Is there a cheaper alternative to GLM 5.1?

DeepSeek V3.2 is 89% 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