GLM 5.3: Benchmarks, API Access, and Weights ETA (2026)

GLM 5.3 shipped on 2026-08-14, and a day later the standalone API remains marked "coming soon", so every first-party route today runs through the GLM Coding Plan. The model reuses the GLM 5.2 base, and performance gains come from post-training. Weights are promised in about two weeks.

Key Specifications:

• Released: 2026-08-14 (Z.ai release note)
• Base model: Same as GLM 5.2, all gains from post-training
• Context: 1M tokens, 128K maximum output (Z.ai model page)
• Open weights: Not yet, Z.ai says roughly two weeks
• Coding: Terminal Bench 3.0 4.6 to 28.3, open-source SOTA
• Breaking API: thinking.type "disabled" removed; reasoning_effort low/high/max
• Access today: GLM Coding Plan, ZCode, Claude Code / Cline / OpenCode
• Standalone API: "coming soon", no date given
• Not yet listed: OpenRouter, gateway catalogs, HuggingFace
• Snapshot: 2026-08-15

What Is GLM 5.3?

It is a post-training refresh of GLM 5.2, not a new model family. Z.ai states in its release note that the model "uses the same base model as GLM-5.2", and "every gain comes from post-training."

• Same base weights as z-ai/glm-5.2, a month of extra RL on top
• Trained on synthesized long-horizon environments, some representing days of work for an experienced engineer
• Aimed squarely at agentic coding: terminal tasks, repo-level work, multi-step tool use
• Also ships a large security research section

The r/LocalLLaMA release thread passed 800 upvotes at a 0.99 ratio within hours, with top replies focused on one detail: a 743B-class model trading blows with much larger ones. That parameter figure is community arithmetic, not a published spec, so it is not repeated as fact.

When Was GLM 5.3 Released?

2026-08-14, and it reached GLM Coding Plan subscribers the same day.

The rollout is uneven in a way worth knowing before searching:

The model page arrived a day after the announcement, which is the normal shape of a launch: the release note is the source of truth on day one and the docs catch up later. What has not caught up yet is the part that matters most for anyone billing per token.

Is GLM 5.3 Open Source?

Not yet. Z.ai commits to publishing the weights about two weeks after launch, "once safety evaluation and hardening are complete."

The HuggingFace repo zai-org/GLM-5.3 already exists, and the API returns 401 for it while zai-org/GLM-5.2 returns 200. A 401 rather than a 404 indicates the repository is created and gated, not missing. That matches a scheduled release more than a vague intention, but a promise with a two-week fuse is still a promise.

There is a precedent for how long that wait runs. Simon Willison, writing on 2026-06-17, described the previous cycle: "Chinese AI lab Z.ai released GLM-5.2 to their coding plan subscribers on June 13th, and then yesterday (June 16th) released the full open weights under an MIT license." Three days last time, a stated two weeks this time. The license is worth watching too, because 5.2 shipped MIT and Z.ai has not said what 5.3 will carry.

If weights are needed this week, GLM 5.2 remains the option. The GLM 5.2 local setup guide covers the GGUF quants and what each one needs, and the self-hosting hardware and cost breakdown has the vLLM numbers. Because 5.3 shares the 5.2 base, the memory footprint and serving shape should carry over almost unchanged, which is the one useful thing about a post-training-only release: capacity planning does not reset.

How Much Does GLM 5.3 Cost?

Z.ai has not published a per-token price for GLM 5.3 yet, and the standalone API it would apply to has not opened. The pricing table in its developer docs still stops at GLM 5.2 as of this snapshot.

What is documented today:

Three things follow from that table. There is no free tier on any route, so the cheapest entry is a Coding Plan subscription rather than a trial key. The off-peak rate covers everything outside a 20-hour weekly window, weekends included, so a batch job scheduled at night is billed at half rate by default rather than by negotiation. And until a 5.3 row appears, anyone quoting a per-token price for GLM 5.3 is extrapolating from 5.2.

What Is the GLM 5.3 Context Window?

1M tokens, with a documented maximum output of 128K. Z.ai's GLM-5.3 model page lists both, and Zhipu's Chinese documentation carries the same pair.

Z.ai's own evaluations did not all run at that ceiling, which is a useful signal about where the model was actually exercised:

The spread matters if planning to lean on the full million. A 1M window is what the model accepts; 400K is what Z.ai chose for its headline coding suite. Whatever endpoint eventually serves 5.3 may also publish a lower cap of its own, so the provider's number is the operative one.

How Much Better Is GLM 5.3 at Coding?

Large on the newest agentic benchmarks, modest on the saturated ones. All figures below are Z.ai's own. The Terminal Bench, SWE-Marathon and Agents' Last Exam runs used the Claude Code 2.1.207 harness at max reasoning effort; DeepSWE used mini-swe-agent.

The Terminal Bench 3.0 line does the heavy lifting: 4.6 to 28.3 on a suite where GLM 5.2 was effectively not competing. On Terminal Bench 2.1, where everyone sits between 85 and 89, the same upgrade is worth 7 points and changes no ranking. Newer benchmarks have room to show movement; old ones do not.

The number Z.ai leads with is not a score. At High effort GLM 5.3 hits 31.4% on its in-house Code Bench using about 50K output tokens per task, against Claude Opus 4.8 at 29.5% using 120K.

That is the claim worth testing independently, because token count is what gets paid for. Z.ai also reports 34.5% at roughly 75K tokens at Max effort, up from GLM 5.2's 23.4% at 96K. Claude Fable 5 still leads that private benchmark at 39.5%, and GPT-5.6 Sol still leads Terminal Bench 3.0, so "open-source SOTA" is the accurate framing rather than "SOTA".

One caution on the whole table: it is a private benchmark plus vendor-run public ones. Kimi K3 and Claude Opus 4.8 numbers here were produced by Z.ai, not by their vendors.

Do I Need to Change My Code for GLM 5.3?

Yes, if thinking was ever disabled. thinking.type: "disabled" is gone, and Z.ai says the request will simply fail.

The new contract:

• thinking.type accepts enabled only
• reasoning_effort accepts low, high, max, and defaults to max
• Z.ai recommends max for coding
• Migration order matters: set enabled plus reasoning_effort: "low" first, then swap the model ID

{
  "model": "glm-5.3",
  "thinking": { "type": "enabled" },
  "reasoning_effort": "max"
}

The cost of losing disabled is easy to underestimate, so it was measured on GLM 5.2 through an OpenAI-compatible endpoint on 2026-08-14. One trivial prompt, "Reply with the single word: ok", three runs per configuration:

Run-to-run variance between the thinking modes swamps the difference between low and max on a prompt this small, so do not read an ordering into those three rows. The row that matters is the last one. Thinking off answered in 2 output tokens every time; the cheapest thinking-on setting still spent between 69 and 122. On GLM 5.3 that last row no longer exists.

If running GLM for classification, routing, extraction or any other high-volume short-answer job, that is the migration to cost out before switching, and low is now the floor. The GLM 5.2 versus GPT-5.5 cost comparison has the workload math for that shape of traffic.

Which Capabilities Does GLM 5.3 Support?

Text in, text out, plus thinking modes, streaming, function calling, context caching, structured output and MCP. Z.ai's model page lists all six; Zhipu's Chinese page lists the same set minus MCP.

Nothing here is new relative to GLM 5.2, which is consistent with a post-training-only release. Vision, image and audio stay on the separate GLM-5V and GLM-Image lines.

How Do I Access GLM 5.3?

Through the GLM Coding Plan today, in ZCode or in any coding agent that lets you point at Z.ai. The per-token API has not opened.

Zhipu has published the endpoints the API will land on before the API itself: https://open.bigmodel.cn/api/paas/v4 for the OpenAI Chat Completions protocol, /api/v1 for the OpenAI Responses protocol, and /api/anthropic for the Anthropic Messages protocol. One caveat in that same note is easy to miss: accounts that have ever subscribed to a GLM Coding Plan, including expired ones, are restricted to the Chat Completions protocol for now.

Anything OpenAI-compatible is a two-line change once your provider lists the model:

from openai import OpenAI

client = OpenAI(api_key="YOUR_KEY", base_url="https://api.ofox.ai/v1")

r = client.chat.completions.create(
    model="z-ai/glm-5.3",
    messages=[{"role": "user", "content": "Refactor this module and run the tests."}],
    reasoning_effort="low",   # "disabled" is not an option on 5.3
)
print(r.usage)

Run that before the catalog updates and you get the failure you would expect, which is worth knowing so you do not go hunting for an auth bug:

{"error":{"message":"Model 'z-ai/glm-5.3' not found","type":"model_not_found","code":404}}

z-ai/glm-5.2 answers on the same endpoint today, so the endpoint, key and request shape are all already correct when 5.3 appears. The GLM 5.2 API access guide covers the key setup end to end.

How Do You Point a Coding Agent at a Model That Launched Yesterday?

By changing one string, if your agent lets you set the endpoint yourself. Launch week always looks the same. The subscription product has the model, the metered API does not, the docs page lands a day late, and every tool keeps a hardcoded model list. On 2026-08-15 that gap is real for GLM 5.3 in both directions: Coding Plan subscribers are running it, while OpenRouter and the gateway catalogs have nothing to sell and the HuggingFace repo is locked.

The part you can control is how much re-plumbing a new model costs you. Agents that let you set base_url and a model string treat a launch as a one-line edit. Agents that ship a fixed dropdown make you wait for their release cycle, which is why the r/opencodeCLI thread appeared within an hour of the announcement.

Because Claude Code, OpenCode and most other agents speak OpenAI-compatible HTTP, one key behind one base URL keeps every one of them on the same billing and the same failover. 15% off top-ups through 2026-08-31 at ofox covers a catalog of about 130 models on that single endpoint, GLM 5.2 among them. GLM 5.3 is not in it at this snapshot, and the code block above is exactly what changes when it is.

GLM 5.3 vs GLM 5.2: What Actually Changed?

The post-training, and three things you can act on: no thinking-off switch, no downloadable weights yet, and a Terminal Bench 3.0 score that moved from 4.6 to 28.3.

Pick GLM 5.2 if you need downloadable weights this month, a published price, per-token billing, or the ability to turn thinking off for cheap short calls. Pick GLM 5.3 if the work is long-horizon agentic coding on a Coding Plan subscription, which is the only place the gap is dramatic.

References

• Z.ai release note: GLM-5.3
• Z.ai developer docs: GLM-5.3 model page
• Z.ai developer docs: pricing
• Z.ai devpack docs: GLM Coding Plan overview
• Zhipu AI docs: GLM-5.3
• HuggingFace: zai-org
• OpenRouter model list
• r/LocalLLaMA: GLM 5.3 Released
• r/opencodeCLI: GLM 5.3 is there!
• Simon Willison: GLM-5.2 is probably the most powerful text-only open weights LLM
• ofox model page: GLM 5.2

Frequently Asked Questions

Is the standalone GLM 5.3 API available now?

Not yet. Z.ai's model page carries a banner reading 'The GLM-5.3 API is coming soon' and Zhipu's Chinese documentation says the same, with no launch date on either. GLM 5.3 is already live for every GLM Coding Plan subscriber, which is the only first-party route today.

What is the GLM 5.3 max output length?

128K tokens, alongside a 1M-token context window, per Z.ai's model page. Z.ai's own benchmark runs sit at or below that: 128K output on Terminal Bench 3.0 and PostTrainBench, 64K on Agents' Last Exam. Whatever endpoint eventually serves the model may publish a lower cap of its own.

Can I use GLM 5.3 with Claude Code?

Yes. Z.ai lists Claude Code, Cline and OpenCode as supported coding tools for the GLM Coding Plan, and its own benchmark runs used the Claude Code 2.1.207 harness. Set reasoning_effort rather than disabling thinking, because the model no longer accepts thinking turned off.

Is GLM 5.3 better than Kimi K3?

On Z.ai's own table it wins Terminal Bench 3.0 by 28.3 to 17.4 and AutomationBench by 48.2 to 46.7, while Kimi K3 leads Toolathlon 76.5 to 73.0 and SWE-Marathon 48.1 to 42.5. Every one of those numbers is vendor-reported by Z.ai, so read it as a claim to verify rather than an independent result.

Does GLM 5.3 use a new base model?

No. Z.ai states GLM 5.3 uses the same base model as GLM 5.2 and that every gain comes from post-training. The release note opens with the line 'Scaling post-training is all we did for GLM-5.3.'

Is GLM 5.3 free?

There is no free tier. Day-one access runs through the points-based GLM Coding Plan or ZCode. Calls made outside the peak window of 14:00 to 18:00 UTC+8 on weekdays consume half the standard points, which is the closest thing to a discount available right now.

Where can I download GLM 5.3 weights?

Nowhere yet. The HuggingFace repo zai-org/GLM-5.3 exists but is not public, and returns 401 through the HuggingFace API while GLM 5.2 returns 200. Z.ai says the weights ship about two weeks after launch, once safety evaluation and hardening finish.

Originally published on ofox.ai/blog.