The Circuitry
THE CIRCUITRYYour one-stop source for all tech news
HOMETODAYNEWSFEEDEVENTS
BOOKMARKS
RSS
© 2026 The Circuitry
About UsSourcesContactCorrectionsPrivacy
  • Today
  • Feed
  • Events
  • Saved
Scroll for more
Verification
VERIFIEDConfidence: HIGH
Source identified
Claims cross-referenced
No discrepancies found
Fact-check summary

Z.ai's GLM-5.2 release, benchmarks, Huawei training, pricing, and 1M context are corroborated by VentureBeat, the company's official blog, Hugging Face, docs.z.ai, Wikipedia, and multiple tech outlets as of June 16-18 2026.

Sourcing
1source

via Decrypt

Decrypt · track record
36Stories
100%Verified
530d
All sources →
From The CircuitryWhy The Circuitry

Verified tech news, cross-checked.

Every story is checked against independent sources before it posts — no rumors dressed up as fact.

How we verify →
Home/Tech/Z.ai Launches GLM-5.2, a Huawei-Trained Rival to Top AI Models
VERIFIEDBy Xavier Rivera· ·2 min read

Z.ai Launches GLM-5.2, a Huawei-Trained Rival to Top AI Models

Z.ai released GLM-5.2 on June 16, which scores within 1 percent of Claude Opus 4.8 on FrontierSWE while beating GPT-5.5. The MIT-licensed model trained solely on Huawei Ascend chips without NVIDIA hardware and undercuts Western API pricing.

Source:Decrypt
Post
Z.ai Launches GLM-5.2, a Huawei-Trained Rival to Top AI Models
From The CircuitryWhy The Circuitry

Verified tech news, cross-checked.

Every story is checked against independent sources before it posts — no rumors dressed up as fact.

How we verify →
TL;DRAI · 60 sec read

Z.ai releases GLM-5.2, a 744B MoE model trained solely on Huawei Ascend chips. It scores 74.4 on FrontierSWE, within 1 percent of Claude Opus 4.8 and above GPT-5.5, while offering a 1M-token context. The open-source model undercuts Western API prices and faces no regional limits, though local runs need 256GB memory.

Z.ai has introduced GLM-5.2, which reportedly delivers performance within 1 percent of Claude Opus 4.8 on the FrontierSWE benchmark while surpassing GPT-5.5.

GLM-5.2 posts strong benchmark scores. The model achieved 74.4 on FrontierSWE against Claude Opus 4.8's 75.1 and GPT-5.5's 72.6. It reached 62.1 on SWE-bench Pro, exceeding both GPT-5.5 at 58.6 and its predecessor GLM-5.1 at 58.4.
Development occurred solely on Huawei Ascend chips without any NVIDIA components.
These results position it as the leading open-source entry on the Artificial Analysis Intelligence Index that combines nine separate evaluations. Benchmarks from OpenRouter align it with the now-banned Claude Fable 5.

The model was trained exclusively on Huawei silicon. Development occurred solely on Huawei Ascend chips without any NVIDIA components. Stability AI founder Emad Mostaque placed overall training expenses near $25 million, approximately 80 percent of which went toward post-training.
From The CircuitryThe Feed — live briefs across tech, all day.See what’s happening →
The Beijing laboratory, listed on the U.S. Entity List since January 2025, had already used Huawei Ascend Atlas servers for image models without American hardware. GLM-5.2 expands that foundation as a 744-billion-parameter mixture-of-experts system featuring a genuine 1-million-token context window, five times the 200K capacity of GLM-5.1.
GLM-5.2 expands that foundation as a 744-billion-parameter mixture-of-experts system featuring a genuine 1-million-token context window, five times the 200K capacity of GLM-5.1.
Pricing undercuts Western frontier models. Access through the API runs $1.40 per million input tokens and $4.40 per million output tokens. Those figures stand well below Claude Opus 4.8 rates of $5 input and $25 output. A monthly Coding Plan begins near $18 and works inside Claude Code, Cline, Kilo Code plus leading agentic platforms. The release carries an MIT license and carries no regional limits.

Local deployment requires substantial hardware. Unsloth AI supplied 2-bit GGUF quantizations that compress the original 1.51TB file size down to 238GB while preserving roughly 82 percent accuracy. Execution still calls for 256GB of unified memory or an equivalent RAM/VRAM setup, whether a fully equipped M4 Ultra Mac Studio or a mid-range GPU workstation paired with 256GB system RAM and mixture-of-experts offloading.
From The CircuitryWhy The Circuitry

Verified tech news, cross-checked.

Every story is checked against independent sources before it posts — no rumors dressed up as fact.

How we verify →
Z.ai released GLM-5.2 on June 16. Combined with the recent ban on Anthropic Fable, the debut has reportedly lifted the company's shares 90 percent to a record high.
Why this mattersAI · ~100 words

Tap a lens to see what this story means for you.

Morning Brief

Liked this? The Brief brings you the whole day in tech, verified, every morning.

Two minutes, free forever. What's in The Brief →

Reader-supported
DonateBuy me a coffee →Follow@thecircuitry_ →Follow@thecircuitry.to →
HELP US IMPROVE
From The Circuitry

See what’s happening right now

The Feed runs all day — short, verified briefs the moment they break.

Open the Feed →
From The Circuitry

Follow @thecircuitry_

Every story we publish, as it happens. No noise between.

Follow on X ↗On Bluesky ↗

Reader-supported

The Circuitry is a passion project I've always wanted to build, and I love the work behind it.

Running it costs real money. APIs, hosting, time. To keep improving the site and growing this into something useful for everyone, those costs have to be covered.

Any contribution is appreciated. If not, no pressure. Thanks for reading.

Buy me a coffee
AIOpen SourceChina
More fromDecrypt
  • OKX Secures Backing at $25 Billion Pre-Money Valuation

    Markets · 1d
  • OKXICE Files for 24/7 Tokenized Stock Trading Under SEC Exemption

    Markets · 4d
  • MetaMask Withdraws Validators from Lido Following Infrastructure Issue

    Markets · 8d
More inTech
  • GlobalFoundries signs $2B TSMC deal for US silicon interposers

    Tech · 8h
  • SpaceX agrees to buy 800 MHz spectrum for Starlink Mobile

    Tech · 11h
  • Microsoft discloses CVE-2026-83947 in Azure Event Grid

    Tech · 11h
SupportThe Work

The Circuitry is reader-supported. If you find the daily brief useful, you can buy me a coffee to keep it going.

Buy a coffee →
From The CircuitryWhy The Circuitry

Verified tech news, cross-checked.

Every story is checked against independent sources before it posts — no rumors dressed up as fact.

How we verify →

MORE IN THIS BEAT

All Tech →
  • Tech· 

    Anthropic Launches Cyber Mission to Secure Infrastructure and Open-Source Code

    Anthropic has launched the Anthropic Cyber Mission to support defenders of critical infrastructure and open-source software with models, engineers, and tools. The initiative starts with the Critical Infrastructure Defense Program and free OSS Scanner amid ongoing challenges in verifying and fixing vulnerabilities.

  • Tech· 

    Anthropic launches Claude Haiku 5.5, cutting prices up to 90% from Haiku 4.5

    Anthropic released Claude Haiku 5.5, its cheapest and fastest small model, at $0.10 per million input tokens and $0.50 per million output tokens for prompts up to 100,000 tokens. Anthropic says it costs around 75% less to run than Haiku 4.5 on average and scores far higher on its benchmarks.

  • Tech· 

    OpenAI publishes 722 math manuscripts from an unreleased internal model

    OpenAI released 722 mathematical manuscripts, grouped into 372 result families, produced by an unreleased internal model. The papers are on GitHub, with Lean formalizations for many but not all of them, and OpenAI warns some unformalized results could have issues.

  • Tech· 

    Meta and Microsoft Slash Employee Claude AI Spending

    Meta and Microsoft are cutting employee use of Anthropic’s Claude AI and directing staff toward their own coding tools, The Information reported. The changes reflect tighter internal AI budgets while customer access to Claude through Microsoft platforms continues to expand.

  • Tech· 

    Microsoft preparing local MAI-Code-1.1-Flash for high-end PCs

    Microsoft has introduced a local edition of MAI-Code-1.1-Flash that runs on Windows PCs without server access. The model requires substantial memory and is coming to GitHub Copilot in experimental preview by the end of October, starting with Nvidia RTX Spark PCs.