GLM-5.2 is an open-weight large language model released by Zhipu AI (Z.ai) on June 13, 2026. It is a Mixture-of-Experts model with roughly 744 billion total parameters (about 40 billion active per token), a usable 1-million-token context window, two selectable reasoning modes (High and Max), and an MIT open-source license. It is positioned primarily as a coding and agentic model and undercuts Claude and GPT-5 pricing by roughly 10x.

What are GLM-5.2 benchmark scores?

Zhipu did not publish official benchmark numbers at launch, which is unusual for a frontier model. The most reliable reference point is its predecessor GLM-5.1, which scored 77.8% on SWE-bench Verified. For comparison, Claude Opus 4.8 scores around 80.9% and GPT-5.5 around 80% on the same benchmark. Independent third-party evaluations of GLM-5.2 are expected within two to three weeks of release.

Is GLM-5.2 better than Claude Opus 4.8 or GPT-5?

On raw reasoning, the consensus from early testing is that GLM-5.2 trails frontier models like Claude Opus 4.8 by roughly six months on abstract, feedback-poor reasoning tasks. On practical coding with tight feedback loops, large context, and real-world completion rates, it is highly competitive and often matches mid-tier frontier models at a fraction of the cost. The honest answer is that it is the strongest open #2 option, not a clear #1.

What are GLM-5.2 thinking modes?

GLM-5.2 introduces two selectable reasoning effort levels. High mode is faster and meant for everyday tasks. Max mode spends more compute on reasoning before answering and is recommended for complex coding and multi-step agentic work, at the cost of roughly 30 to 80 percent higher latency.

GLM-5.2 Review (2026): Specs, Benchmarks, Pricing & How It Compares to Claude and GPT-5

Q: When was GLM-5.2 released?

GLM-5.2 was released on June 13, 2026 by Zhipu AI. It launched first through the GLM Coding Plan with day-one support for eight agentic IDEs including Claude Code, Cline, and Roo Code. Standalone API pricing and official open weights on Hugging Face were announced to follow within roughly a week of launch.

Q: How much does GLM-5.2 cost?

At launch GLM-5.2 is available through the GLM Coding Plan at roughly $10/month (Lite), $30/month (Pro), and $80/month (Max). That is about 10x cheaper than Anthropic’s $200/month Claude Max plan. Standalone per-token API pricing was not published at launch; for reference, GLM-5 was about $1.00 per million input tokens and $3.20 per million output tokens.

Q: Is GLM-5.2 multimodal?

Zhipu did not explicitly claim vision, audio, or video support for GLM-5.2 in its launch materials, which focused on text and coding. Earlier GLM-5 family models advertised multimodal capability, but until Zhipu publishes a formal GLM-5.2 model card you should treat GLM-5.2 as text-only for production planning.

Q: Can I self-host GLM-5.2?

Yes. GLM-5.2 ships under an MIT license, which permits self-hosting, fine-tuning, and commercial use. Official weights were announced for release on Hugging Face under zai-org/GLM-5.2 within about a week of launch. The full model is large (over 1.5 TB in Safetensors format), so practical self-hosting requires multi-GPU infrastructure or a quantized community build.

Short answer: GLM-5.2 is Zhipu AI's open-weight frontier model, released June 13, 2026. It pairs a usable 1-million-token context window with two selectable reasoning modes (High and Max), an MIT open-source license, and pricing roughly 10x cheaper than Claude or GPT-5. The catch: Zhipu shipped it with no published benchmarks, so performance claims rest on its predecessor GLM-5.1 (77.8% on SWE-bench Verified) and early hands-on testing. Verdict: the strongest open #2 model for coding and agentic work today — not a clear #1 for hard reasoning. This review covers every confirmed spec, what's still unknown, real pricing, and how it stacks up against Claude Opus 4.8 and GPT-5.5.

What Is GLM-5.2? (The 60-Second Version)

GLM-5.2 is the latest large language model from Zhipu AI (which operates under the Z.ai brand internationally). It launched on June 13, 2026, and it matters for three concrete reasons:

It's genuinely open. GLM-5.2 ships under an MIT license with no regional restrictions — you can self-host it, fine-tune it, and use it commercially.

The context window is huge and usable. Zhipu claims a 1,000,000-token input window that holds up in real use, not just on a spec sheet. That's enough to load an entire mid-sized codebase or a stack of legal documents into a single prompt.

It's cheap. The GLM Coding Plan starts at roughly $10/month — about a tenth of what comparable frontier access costs from Anthropic or OpenAI.

The timing was not an accident. GLM-5.2 dropped 48 hours after US export rules forced Anthropic to disable its top Fable 5 and Mythos 5 models for foreign nationals (June 12, 2026). Zhipu explicitly framed the release around the idea that "frontier intelligence belongs to everyone" — a deliberate geopolitical counter-move in the US–China AI race.

GLM-5.2 Specs: Everything We Know (and What We Don't)

Here is the confirmed technical profile, sourced from Zhipu's launch materials and independent reporting:

Specification	GLM-5.2
Vendor	Zhipu AI (Z.ai)
Release date	June 13, 2026
Architecture	Mixture-of-Experts (MoE)
Total parameters	~744 billion
Active parameters / token	~40 billion
Expert count	384 experts
Context window (input)	1,000,000 tokens (usable)
Max output tokens	131,072
Pretraining data	~28.5 trillion tokens
Reasoning modes	Two: High & Max
License	MIT (open-source)
Regional restrictions	None

The two thinking modes — explained

The headline new feature is selectable reasoning effort:

High mode — Fast. Use it for everyday code, summaries, and tasks where the answer is fairly direct.
Max mode — Slower and more deliberate. It spends extra compute reasoning before it answers, which makes it the right choice for complex multi-file coding and long agentic chains. Expect roughly 30–80% higher latency in exchange.

If you've used extended thinking in other 2026 models, this is the same idea exposed as a clean toggle.

What Zhipu has not confirmed (be skeptical here)

A responsible review names the gaps. As of mid-June 2026, these were not officially documented:

❌ Official benchmark scores — none published at launch (more on this below).
❌ Multimodal support — launch materials focus only on text and code. Treat GLM-5.2 as text-only until a formal model card says otherwise.
❌ Standalone per-token API pricing — announced to follow within ~a week.
❌ Throughput (tokens/sec) and exact High-vs-Max latency numbers.
❌ Fine-tuning API availability and safety/moderation testing details.

Test What You Just Learned

Take our free 12-question CCA practice test with instant feedback and detailed explanations for every answer.

Start Free Quiz →

GLM-5.2 Benchmarks: The Honest Picture

Here's the unusual part: Zhipu published zero benchmark numbers at launch. For a model positioning itself against Claude and GPT-5, that's a conspicuous silence — and every competing article noticed it.

So how do you evaluate a model with no official scores? You triangulate from its predecessor and from independent leaderboards.

What GLM-5.1 scored (the most reliable proxy)

Benchmark	GLM-5.1 score
SWE-bench Verified	77.8%
SWE-bench Multilingual	73.3%
Terminal-Bench 2.0 (Terminus-2)	56.2% / 60.7%

GLM-5.2 is an iteration on this baseline, so 77.8% on SWE-bench Verified is a reasonable floor to assume until independent tests land (expected within 2–3 weeks of launch).

How that compares to the 2026 frontier

Model	SWE-bench Verified	Notes
Claude Opus 4.8	~80.9%	Current reasoning leader
GPT-5.5	~80%	Multimodal, newer eval protocol
GLM-5.2	not published	GLM-5.1 baseline ≈ 77.8%
GLM-5.1	77.8%	Likely GLM-5.2's floor
Gemini 3 Pro	~65%	Multimodal

Important caveat: classic benchmarks like SWE-bench, MMLU, and HumanEval have saturated above 90% for frontier models on many splits and no longer cleanly separate the top tier. The industry has shifted to LiveCodeBench, tau-bench (agentic), and real-world completion rates. On those practical axes, early GLM-5.x feedback is genuinely strong.

What early testers actually say

From the launch-day community discussion (a 600+ comment Hacker News thread) and early hands-on reports:

✅ Excels at tasks with tight feedback loops — coding, verification, structured generation, UI/design work.
✅ Often beats mid-tier frontier models on real-world completion rates despite lower abstract-reasoning scores.
⚠️ Trails Claude Opus 4.8 by roughly six months on abstract, feedback-poor reasoning.
⚠️ Can stumble on deceptively simple tasks (e.g., certain counting problems) — it sometimes emulates reasoning rather than achieving it on the hardest problems.

GLM-5.2 Pricing: Where It Really Wins

Cost is GLM-5.2's sharpest edge. Here's the launch pricing via the GLM Coding Plan:

Tier	Monthly cost	Rough prompt budget	Best for
Lite	~$10	~400/week	Casual development
Pro	~$30	~2,000/week	Regular development
Max	~$80	~8,000/week	Power users
Team	Seat-based	Unlimited	Organizations

GLM-5.2 vs Claude vs GPT-5 on cost

Plan	Monthly cost
Anthropic Claude Code (Pro)	~$20
GLM Coding Plan (Lite → Max)	~$10 – $80
Anthropic Claude Max	~$200

For a developer doing heavy agentic coding, the GLM Max tier at ~$80/month against Claude Max at ~$200/month is a ~60% saving — before you even factor in the option to self-host the open weights for free (minus your own compute).

Standalone API note: Per-token API pricing wasn't published at launch. As a reference point, GLM-5 was ~$1.00 / 1M input tokens and ~$3.20 / 1M output tokens — still far below Claude Opus or GPT-5 rates. Expect GLM-5.2 standalone pricing to land in a similar range.

How to Access GLM-5.2

There are three paths, in order of availability:

1. GLM Coding Plan (live now)

The fastest route. Subscribe at Z.ai's coding portal and connect it to your IDE. GLM-5.2 shipped with day-one support for eight agentic IDEs via OpenAI-compatible endpoints:

Claude Code
Cline
Roo Code
OpenCode
Goose
Crush
OpenClaw
Kilo Code

Because the endpoint is OpenAI-compatible, wiring it into an existing agentic workflow is usually a matter of changing the base URL and model ID (glm-5.2).

2. Standalone Z.ai API (rolling out)

A direct REST API and a web chatbot were announced to follow within roughly a week of launch — useful if you want to call GLM-5.2 from your own backend rather than an IDE.

3. Open weights / self-hosting (rolling out)

Official MIT-licensed weights were announced for Hugging Face under zai-org/GLM-5.2. The full model is over 1.5 TB in Safetensors format, so realistic self-hosting means multi-GPU infrastructure or waiting for a quantized community build. (An unofficial community upload appeared on day one — prefer the official zai-org repo once it's live for provenance and safety.)

Ready to Pass the CCA Exam?

Get all 300+ practice questions, timed exam simulator, domain analytics, and review mode. Professionals with the CCA certification command $130K-$155K+ salaries.

Try Free Quiz First Get CCA Mastery Bundle — $19.99

Best Use Cases for GLM-5.2

GLM-5.2's particular strengths — huge context, strong coding, low cost, open license — point to a clear set of jobs it does well:

Repo-scale refactoring. The 1M context lets you load an entire codebase and make coordinated changes across dozens of files.

Multi-file debugging. Put the whole project in context and let it trace a bug end-to-end.

Long-horizon agentic tasks. Context + Max mode supports chains with 100+ tool calls.

Structured data generation at scale — JSON, SQL, configuration, test suites.

Large-document analysis — compliance, legal, and research workflows where you need to reason over a lot of text at once.

Privacy-sensitive or on-prem deployments — the open weights make GLM-5.2 a real option where sending code to a US API vendor isn't allowed.

Where it's not the first pick (today): the hardest abstract-reasoning problems, and any workflow that genuinely needs vision or audio.

GLM-5.2 vs Claude vs GPT-5: Which Should You Use?

If you need…	Best pick
Maximum reasoning on hard, novel problems	Claude Opus 4.8
Multimodal (vision + text) reasoning	GPT-5.5 or Gemini 3 Pro
Cheap, high-volume coding with huge context	GLM-5.2
Open weights / self-hosting / no vendor lock-in	GLM-5.2
A geopolitical hedge against single-vendor risk	GLM-5.2 as a secondary model

The pragmatic 2026 setup for many teams is not "pick one." It's a frontier model (Claude or GPT-5) for the hardest 10% of reasoning, with GLM-5.2 handling the high-volume, cost-sensitive 90% — coding, refactors, structured generation, and long-context analysis.

The Verdict: Is GLM-5.2 Worth It?

Yes — as your high-volume coding and agentic workhorse, and as an open-weight hedge. GLM-5.2 delivers a usable 1M-token context, strong practical coding performance, and an MIT license at roughly a tenth of frontier pricing. For repo-scale automation and cost-sensitive teams, that combination is hard to beat. But go in with eyes open. The missing launch benchmarks are a real gap, multimodal support is unconfirmed, and on the hardest reasoning tasks it still trails Claude Opus 4.8. If your work lives or dies on abstract reasoning, keep a frontier model in the loop. Our recommendation: add GLM-5.2 to your stack now for coding and long-context work, but wait 2–3 weeks for independent benchmarks and the official open weights before betting a mission-critical pipeline on it.

Frequently Asked Questions

What is GLM-5.2?

GLM-5.2 is an open-weight Mixture-of-Experts language model from Zhipu AI, released June 13, 2026, with ~744B total parameters (~40B active), a usable 1M-token context window, two reasoning modes, and an MIT license. It's positioned mainly as a coding and agentic model.

When was GLM-5.2 released?

June 13, 2026, first via the GLM Coding Plan with day-one support for eight agentic IDEs. Standalone API and official open weights were announced to follow within about a week.

What are GLM-5.2's benchmark scores?

Zhipu published no official benchmarks at launch. Its predecessor GLM-5.1 scored 77.8% on SWE-bench Verified — a reasonable floor. Claude Opus 4.8 sits near 80.9% and GPT-5.5 near 80%. Independent GLM-5.2 evaluations are expected within 2–3 weeks of release.

How much does GLM-5.2 cost?

The GLM Coding Plan runs ~$10 (Lite), ~$30 (Pro), and ~$80 (Max) per month — roughly 10x cheaper than Claude Max at ~$200/month. Standalone per-token pricing wasn't published at launch; GLM-5 was ~$1.00/1M input and ~$3.20/1M output for reference.

Is GLM-5.2 multimodal?

Not confirmed. Launch materials cover only text and coding. Treat it as text-only for production planning until Zhipu publishes a formal model card.

Can I self-host GLM-5.2?

Yes — it's MIT-licensed. Official weights were announced for Hugging Face (zai-org/GLM-5.2). The model is large (1.5 TB+), so plan for multi-GPU infrastructure or a quantized build.

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

For hard abstract reasoning, no — it trails Claude Opus 4.8 by roughly six months. For high-volume coding, huge context, and cost efficiency, it's highly competitive and far cheaper. It's the strongest open #2, not a clear #1.

Last updated: June 15, 2026. GLM-5.2 is two days old at the time of writing; specs and pricing are confirmed from Zhipu AI's launch materials and independent reporting (Pandaily, MarkTechPost, Coder Sera, LayerLens), but benchmark and multimodal details remain unconfirmed by Zhipu. We'll update this review as official benchmarks and open weights are published.