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Official release GLM-5.3 Zhipu / Z.ai Flagship LLM
2026-08-14 · Model Watch · updated same day after official announcement

GLM-5.3 Officially Released: Post-Training Scaling, Emergent Cyber, Weights in 2 Weeks

Z.ai officially announced GLM-5.3 on August 14 — same base model as GLM-5.2, with every gain coming from scaled post-training. It's live for all GLM Coding Plan subscribers right now, ships with an API breaking change on thinking parameters, finds real vulnerabilities at a rate that surprised its own creators, and goes open-weights in ~two weeks. Full numbers, the migration warning, and overseas reaction below.

Direct answer

GLM-5.3 is officially out (Aug 14, 2026). The official announcement states: "Today we are releasing GLM-5.3. It uses the same base model as GLM-5.2 — every gain comes from post-training." Z.ai calls it "the most capable open-weights model for coding" (a 50% jump on its in-house Z.ai Code Bench) and state-of-the-art on CyberGym for vulnerability discovery. Rollout status: GLM Coding Plan — live for all subscribers (points-based quota; 50% off-peak discount); API — documented with a required migration (three effort levels low/high/max, and thinking.type: "disabled" is gone — old requests will fail); weights — public in ~2 weeks after safety hardening. API pricing is not yet published. For production stacks on relays: stay on glm-5.2 until 5.3 is generally available and healthy upstream.

Verified status at a glance

ItemStatus (per official sources, 2026-08-14)
AnnouncementOfficial blog post live: z.ai/blog/glm-5.3 ("Today we are releasing GLM-5.3")
GLM Coding PlanRolled out to all subscribers; points-based quota; off-peak 50% (peak = weekdays 14:00–18:00 UTC+8)
APIModel page + docs live; glm-5.3 with thinking effort low / high / max (default max); disabling thinking no longer supported
Open weights"in two weeks after launch, once safety evaluation and hardening are complete" (~end of August)
Context / output1M context · 128K max output · text in / text out (no native vision)
API pricingNot published yet — treat any pre-announcement price as speculation
Changelog entriesdocs.bigmodel.cn model page live; the release-notes/changelog pages hadn't caught up at the time of writing

Rollout order this time was blog + Coding Plan first, changelogs trailing — the mirror image of a docs-first rollout. If your signal is "is it in the changelog yet", you'll be late.

The numbers (vendor-reported, from the official table)

All scores below are Z.ai's own reported numbers from the announcement. Selected rows; the full table in the blog covers ~20 benchmarks.

BenchmarkGLM-5.3GLM-5.2Kimi K3Opus 4.8Fable 5 / GPT-5.6 Sol
Terminal Bench 2.188.281.088.385.088.0 / 88.8
Terminal Bench 3.028.34.617.421.133.7 / 34.6
DeepSWE v1.166.946.267.558.069.7 / 72.7
SWE-Marathon v1.142.519.448.148.833.1 / 42.5
Agents' Last Exam (CLI)28.523.827.625.723.8 / 28.6
HLE w/ Tools62.554.759.857.963.9 / 64.5
GDPval-AA v217691508168215881743 / 1730
CyberGym84.577.280.078.183.8 / 83.6
ExploitBench54.424.432.240.078.0 / 76.5
  • Honest read of the table: GLM-5.3 roughly matches or beats Kimi K3 and DeepSeek-V4-Pro-0813 (62.7 DeepSWE) across coding/agentic rows, sits at or near Opus 4.8, and still trails Claude Fable 5 and GPT-5.6 Sol on the hardest rows (Terminal Bench 3.0, DeepSWE, ExploitBench). Z.ai itself says the gap to the closed frontier is widest exactly where it improved most.
  • Token efficiency: on the in-house Z.ai Code Bench, at High effort 5.3 hits 31.4% with ~50K output tokens, surpassing Opus 4.8's 29.5% at 120K; Fable 5 still leads at 39.5% (Max effort).
  • Vendor claims, labeled as such: "most capable open-weights model for coding", open-source SOTA on Terminal Bench 3.0 and ALE, ~50% coding-experience improvement. Independent verification arrives with the weights in ~2 weeks.

The cyber story is real-world, not just benchmarks

The most unusual part of the release: Z.ai ran GLM-5.2/5.3 against real codebases with several security teams in China. After expert review and deduplication, the model identified 2,436 vulnerabilities across 269 projects, including 1,097 medium-to-high severity issues — spanning kernels, browser engines, open-source infrastructure, web apps, and network protocols. The oldest flaw dates to 1981; on average a vulnerability had lived 26.6 years before discovery.

  • Findings flow into a public Z.ai Security Disclosure Ledger — per unite.ai's coverage, 53 were public with CVEs at announcement and 2,383 remain under embargo (Linux kernel use-after-free, WebKit/Safari memory bugs, FreeBSD parameter validation among them).
  • On exploitation-depth benchmarks the pattern is consistent: big jumps from 5.2 (ExploitGym 29→105 tasks @2h), but Mythos 5 and GPT-5.6 Sol remain well ahead. This is a strong defensive/security-review capability, not an offense frontier.
  • Z.ai's own framing: capability "developed faster than we expected" as post-training scaled — hence the two-week safety hardening window before weights ship.

API builders: one breaking change to plan for

  • Migration required: GLM-5.3 supports thinking effort low / high / max (default max, recommended for coding) — and thinking.type: "disabled" is no longer supported. The official docs are blunt: change it to enabled and set reasoning_effort before switching the model ID, "otherwise, the request will fail."
  • Coding Plan economics: the plan is now points-based (input, cached input, and output counted separately); weekdays 14:00–18:00 UTC+8 are peak, everything else — including weekends — consumes 50% of standard points. ZCode adds a 98%+ cache hit rate and a 1.5x quota boost through Aug 31.
  • Through relays like ChinaModelAPI: production stays on glm-5.2 for now; we'll add the 5.3 model ID once the upstream API is generally available and healthy. When you migrate, budget for the mandatory thinking-parameter change above.
  • Same base, same envelope: 1M context / 128K output / same capability surface (thinking, streaming, function calling, context cache, structured output, MCP) — so migration is a model-ID + params swap plus regression runs on your agent loops.
  • Still text-only: vision was the top community ask in Zhipu's feedback round; it didn't make this release.

Overseas reaction

  • Reddit r/LocalLLaMA has a "GLM 5.3 Released" thread linking the official blog, with the headline detail that weights land "in two weeks".
  • Reddit r/ZaiGLM users on Lite plans reported GLM-5.2 "responding very differently" in the days before announcement — consistent with a staged rollout behind the 5.2 label rather than a big-bang switch.
  • unite.ai covered the launch under "a cyber capability that outgrew its training", highlighting the 2,436-vulnerability disclosure program and the end-of-August weights window for independent verification.
  • Laurie Voss (LinkedIn) — a widely read commentator on open-weight models — framed 5.2-as-go-to with "GLM 5.3 open weights in development", putting the GLM line ~6–9 months ahead of the open-weight pack in his telling.
  • X/Twitter tech commentators (e.g. Julian Goldie) had tracked the pre-release leaks; the official @zai_org announcement settles the "when" question.

Primary sources

FAQ

Is GLM-5.3 released?

Yes — officially announced Aug 14, 2026 on the Z.ai blog. Coding Plan users have it now; weights follow in ~2 weeks.

GLM-5.3 pricing?

API pricing not published yet. Coding Plan moved to points with 50% off-peak discounts (peak = weekdays 14:00–18:00 UTC+8).

Will my glm-5.2 calls break?

No — 5.2 stays GA, open-weight, and routed as usual. But when you do move to 5.3, thinking.type: "disabled" requests will fail; migrate params first.

Does 5.3 add vision?

No — text in / text out. Vision was the top community request but is not in this release.