Model Review

GLM-5 Review: GLM-5.2, 5.1 & 5 — Benchmarks, Pricing & Access

GLM-5 is the model that put Zhipu AI (Z.ai) on the frontier — and its newest version, GLM-5.2, is the top-ranked open-weights model on the independent Artificial Analysis Intelligence Index. It's MIT-licensed, has a 1M-token context window, and costs a fraction of the Western frontier. This review maps the fast-moving GLM-5 line (GLM-5 → 5.1 → 5.2), separates the independently-verified benchmarks from the vendor-reported ones, gives the real Z.ai pricing, models what it costs to run, and shows how to call it.

GLM-5 review — GLM-5.2, 5.1 and 5 versions, benchmarks, pricing, and access

What GLM-5 is

GLM-5 is Zhipu AI / Z.ai's frontier-class model family, built around the thesis of its technical paper — "GLM-5: from Vibe Coding to Agentic Engineering" (arXiv 2602.15763). All three current versions are open-weights, MIT-licensed, text-only Mixture-of-Experts LLMs (~744-753B total parameters, ~40B active per token), available on Hugging Face under zai-org and via the Z.ai API. The newest, GLM-5.2, is the top-ranked open-weights model on the independent Artificial Analysis Intelligence Index — a genuine frontier-adjacent model at open-weights prices.

How this is sourced. Versions, dates, and Z.ai's own API rates are from Z.ai's docs (release notes + pricing page) and Hugging Face model cards, verified June 2026; the third-party gateway rates quoted below were captured from our live catalog on July 29, 2026 and move more often than Z.ai's list. The Artificial Analysis Index score is independent (artificialanalysis.ai). Benchmarks labeled "vendor-reported" come from the HF model card and have not been independently reproduced. Workload costs are our own model, and our hands-on coding results follow our published testing methodology.

The version map (5 → 5.1 → 5.2)

VersionReleasedContextHeadline
GLM-5Feb 12, 2026200KLaunched the family; DeepSeek Sparse Attention, async RL
GLM-5.1early April 2026200KLong-horizon agentic; vendor-claimed up-to-8-hour autonomous run
GLM-5.2June 16, 20261MCurrent flagship; #1 open-weights on the Artificial Analysis Index

The cadence is fast — three releases in four months — and all stay open-weights (MIT) with FP8 variants. GLM-5.1 shipped proprietary-first, then open-sourced around April 8; GLM-5.2's subscriber rollout began ~June 13 before the June 16 standalone API.

Benchmarks (verified vs vendor)

It's worth separating what's independently verified from what the vendor reports:

The honest read: GLM-5.2 is a legitimately frontier-adjacent model — independently the best open-weights option — with vendor benchmarks that look frontier-competitive but should be treated as vendor framing until reproduced.

How GLM-5.2 did in our test

Beyond the leaderboards, we ran GLM-5.2 ourselves through our executed-code coding benchmark — nine tasks scored by running the generated code against hidden tests (see our methodology). It scored 9/9 — a clean sweep — competitive with the frontier on correctness. The cost story is more nuanced than the sticker price: GLM-5.2 reasons moderately, emitting ~560 reasoning tokens per task and averaging ~12 seconds per task. That put its measured cost at about $1.99 per 1,000 tasks — below Claude Opus 4.8's $4.05, but well above lean coders like DeepSeek V4-Flash ($0.13) and Qwen3 Coder Next ($0.10). All four figures come from one dated sweep: measured token counts priced at list rates on July 17, 2026. The token counts are fixed by the run; the dollar figures move when list prices move, and DeepSeek V4-Flash and Qwen3 Coder Next have both edged up since.

Cheap per token ≠ cheap per task. GLM-5.2's per-token price looks low, but real spend = price × tokens generated, and its reasoning adds to the per-task bill. The sticker rate is the start of the cost question, not the end — which is exactly why we run the tasks. Full field and method: our coding-cost benchmark.

Pricing

GLM's prices are a fraction of the Western frontier — GLM-5.2's combined per-token cost on Z.ai (~$5.80/1M) is roughly one-sixth of GPT-5.5's $35, and on third-party gateway rates (~$2.99/1M as of July 29, 2026) closer to one-twelfth:

Output price per 1M tokensGLM at Z.ai rates, June 2026 · others captured July 29, 2026GPT-5.5$30GLM-5.2$4.40GLM-5$3.20DeepSeek V3.2$0.40
Chart: DataLLM Lab — output price per 1M tokens. GLM bars are Z.ai's own API rates (June 2026); GPT-5.5 and DeepSeek V3.2 are catalog rates captured July 29, 2026. GLM-5.2 and GLM-5 (highlighted) are far below GPT-5.5; DeepSeek is cheaper still. Note that the GLM ordering shown here holds only on Z.ai — on gateways GLM-5.2 is now cheaper than GLM-5, per the note below.

Z.ai API rates (per 1M tokens, from Z.ai's own pricing page, checked June 2026): GLM-5.2 $1.40 in / $4.40 out ($0.26 cached); GLM-5.1 $1.40 / $4.40; GLM-5 $1.00 / $3.20 ($0.20 cached). On this sheet the older model is the cheaper one. And because the weights are MIT-licensed, self-hosting is an option if you have the GPUs.

Note: those are Z.ai's own rates, and the endpoint you actually call probably isn't Z.ai. Through OpenRouter and gateways the numbers are lower — and as of July 29, 2026 they no longer rank the same way: GLM-5.2 $0.72 in / $2.27 out, GLM-5.1 $0.97 / $3.04, GLM-5 $0.95 / $2.55. The newest flagship is now the cheapest of the three there, which is the reverse of Z.ai's ordering — so "drop back to GLM-5 to save money" is advice that no longer works on a gateway. Gateway rates move often; price it on the endpoint you'll actually call.

What GLM-5.2 costs to run

Modeled monthly cost across five workloads, with the GLM columns priced at Z.ai's own rates — GLM-5.2 sits well below the Western flagship, with GLM-5 cheaper on Z.ai's sheet and DeepSeek cheaper still. Read the GLM-5 column as a Z.ai-only saving: buy the same two models through a gateway and it disappears, because GLM-5.2 is the cheaper of the pair there.

Monthly workloadGLM-5.2
$1.40 / $4.40
GLM-5
$1.00 / $3.20
GPT-5.5
$5 / $30
DeepSeek V3.2
$0.27 / $0.40
Support chatbot$109$78.4$560$15.6
RAG / knowledge base$368$264$1,600$62.0
Coding agent$222$160$1,150$31.6
Batch extraction$245$176$990$43.7
Content generation$204$148$1,300$21.4
Methodology. Cost = input_price × input volume + output_price × output volume. Monthly volumes: Support chatbot 40M in / 12M out, RAG 200M / 20M, Coding agent 80M / 25M, Batch extraction 150M / 8M, Content generation 20M / 40M. Rates used: GLM-5.2 $1.40/$4.40 and GLM-5 $1.00/$3.20 from Z.ai's pricing page (checked June 2026); GPT-5.5 $5/$30 and DeepSeek V3.2 $0.27/$0.40 from our catalog, captured July 29, 2026. GLM-5.2's cached-input rate ($0.26) lowers reused-context workloads further. Priced through a gateway instead, the GLM-5.2 column falls by about half and drops below the GLM-5 column.

How to access it

Three ways: the Z.ai API, a gateway, or self-host. The API is OpenAI-SDK-compatible:

from openai import OpenAI
client = OpenAI(base_url="https://api.z.ai/api/paas/v4", api_key="$ZAI_API_KEY")
resp = client.chat.completions.create(
    model="glm-5.2",                      # or glm-5.1, glm-5
    messages=[{"role": "user", "content": "Plan and implement this feature..."}],
)
print(resp.choices[0].message.content)

Or reach GLM-5.2 through a gateway with one key alongside 300+ other models; or download the MIT weights from Hugging Face (zai-org/GLM-5.2) to self-host.

Who should use GLM-5.2

Open-weights + frontier

  • You want the top open-weights model and can't use a closed flagship — GLM-5.2 leads the open Index.

Agentic coding

  • Long-horizon coding/engineering at ~1/6 the frontier's per-token price on Z.ai, and roughly 1/12 on gateway rates; pair with the 1M context for big repos.

Self-host / data control

  • MIT weights on Hugging Face — run it in your own infrastructure.

Even cheaper?

  • If you don't need GLM-5.2's Index lead, DeepSeek/Qwen are cheaper per token — compare.

Call GLM-5.2 and 300+ models with one key

GLM-5.2, Claude Opus 4.7, GPT-5.4, DeepSeek V3.2 and more — one OpenAI-compatible endpoint, live price comparison, failover.

FAQ

What is GLM-5?

Zhipu/Z.ai's frontier-class open-weights MoE family (~744B/40B), MIT-licensed. GLM-5 launched Feb 12, 2026; GLM-5.1 in early April; GLM-5.2 (current flagship) June 16, 2026.

Is GLM-5.2 good?

Yes — 51 on the independent Artificial Analysis Index, #1 open-weights at release (#4 overall). Vendor-reported SWE-bench Pro 62.1, AIME 2026 99.2, GPQA-Diamond 91.2.

How much does GLM-5 cost?

Z.ai API per 1M (checked June 2026): GLM-5.2 $1.40/$4.40 ($0.26 cached); GLM-5.1 same; GLM-5 $1.00/$3.20 — ~1/6 of GPT-5.5's combined cost. Gateways are cheaper and rank the models the other way round: as of July 29, 2026 GLM-5.2 is $0.72/$2.27, GLM-5.1 $0.97/$3.04 and GLM-5 $0.95/$2.55, so the newest model is the cheapest there. MIT weights are free to self-host.

Is GLM-5 open source?

Yes — GLM-5/5.1/5.2 are open-weights under MIT on Hugging Face (zai-org), with FP8 variants. Self-host, fine-tune, ship commercially.

What is GLM-5.2's context window?

1M tokens (up from 200K on GLM-5/5.1), with output capped around 128-131K depending on mode.

How do I use the GLM-5 API?

OpenAI-SDK-compatible at https://api.z.ai/api/paas/v4 — set base URL + model id (e.g. glm-5.2). Or self-host, or use a gateway like DataLLM Lab.

Difference between GLM-5, 5.1, and 5.2?

GLM-5 launched the family (200K, sparse attention); GLM-5.1 pushed long-horizon agentic (8h claim); GLM-5.2 is the flagship — 1M context, top open-weights Index score, best coding numbers.

Is GLM-5.2 better than DeepSeek or GPT-5?

It leads open-weights on the independent Index and ranks #4 overall; GPT-5.5/Opus 4.8 are above it overall. Vs DeepSeek it scores higher but costs more per token. Test on your tasks.

Written by

Founder of DataLLM Lab, the unified LLM gateway. Kevin tests models the boring way — same prompts, real costs, unedited outputs — and writes up what the runs actually show. Articles are drafted with AI assistance and published under his name; every first-party number comes from an executed run.

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