Z.ai-reported result
Terminal-Bench 3.0
Z.ai reports 28.3 vs 4.6 for the previous flagship on Terminal-Bench 3.0 — the largest reported jump.
GLM 5.3 is the new Zhipu AI (Z.ai) flagship large language model: 1M-token context, 128K maximum output, and top open-source coding benchmarks.
GLM 5.3 is the new flagship large language model from Zhipu AI (Z.ai), announced in August 2026, built on the previous flagship base with large-scale long-horizon post-training.
Z.ai newest flagship base model: 1M-token context window, 128K maximum output, and text-in, text-out modality.
It uses the previous flagship base and adds tens of times more long-horizon post-training across real compute clusters, storage, docs, and codebases; Z.ai says coding feel improves by about 50%.
The GLM 5.3 model API is coming soon, so this page separates what Z.ai has confirmed (specs and benchmarks) from what is still pending (API ID, pricing, weights, and license).
Z.ai has confirmed GLM 5.3 specs and benchmarks. API access, pricing, and open weights are still pending announcements.
Confirmed by Z.ai
Official model page lists a 1M-token context window.
Official maximum output tokens per response.
Text base model; no vision or multimodal input is documented.
Z.ai Coding Plan subscription has fully rolled out the model.
Z.ai says the model API will go live shortly and has not published a firm date.
Pending official details
Previous flagship API is about $1.40 input / $4.40 output per 1M tokens.
The previous flagship ships under MIT on Hugging Face; the new weights and license are not published yet.
Z.ai has not published parameter totals.
Use `glm-5.3` as the public API model ID on glm5.app.
Status is checked against Z.ai public communications as of August 2026; details not marked as confirmed remain unverified until Z.ai announces them.
Benchmarks / 02
Z.ai reports large GLM 5.3 benchmark gains, but a score only applies to the published harness and date.
Z.ai-reported result
Z.ai reports 28.3 vs 4.6 for the previous flagship on Terminal-Bench 3.0 — the largest reported jump.
Z.ai-reported result
Z.ai reports 66.9 vs 46.2 for the previous flagship on DeepSWE v1.1, a long-horizon engineering benchmark.
Z.ai-reported result
Z.ai reports 28.5 vs 23.8 for the previous flagship on Agents' Last Exam, covering agentic knowledge and reasoning.
Z.ai-reported result
Z.ai reports 84.5 on CyberGym, slightly above GPT-5.6 Sol at 83.6 — a published result, not a guarantee for your security workflow.
Capabilities / 03
GLM 5.3 supports the standard developer stack for agentic and long-horizon work, with 1M-token context for project-scale tasks.
Multiple thinking modes balance reasoning depth against latency, matching the task at hand.
Strong tool-calling support for external integrations, with your application validating and executing every requested action.
Real-time streaming responses for interactive chat and agent loops.
Smart caching optimizes long conversations and repeated context, cutting cost on long-horizon sessions.
JSON and other structured output formats make system integration predictable.
The model can call external MCP tools and data sources, extending agent workflows beyond chat.
Release timeline / 04
The milestones that led to GLM 5.3, and what still needs to land, updated as Z.ai publishes official news.
GLM 5.2 launched for long-horizon tasks with a 1M-token context window and effort-level control.
Z.ai published the official model page and benchmark results, naming it the new flagship built on the GLM 5.2 base.
The Z.ai Coding Plan fully rolled out the model for coding tools like Claude Code, Cline, and OpenCode.
Z.ai says the API is coming soon. The official model ID, limits, and pricing will be updated here.
GLM 5.3 download and license details are expected to follow the MIT precedent of its predecessor, pending official confirmation.
Follow the Z.ai blog, the zai-org GitHub repository, and the bigmodel docs for the first API announcements.
Who it is for / 05
GLM 5.3 is aimed at teams doing long-horizon engineering, agentic workflows, and security review.
Developers building coding assistants and IDE workflows benefit from the reported 50% coding feel gain and the 1M-token context for whole-repository work.
Agent teams use thinking modes, function calling, streaming, and MCP to build long-running workflows with clear stop conditions.
It shows strength in white-box code review and vulnerability discovery (CyberGym 84.5), useful as an assistant layer experts still validate.
Teams working across tens of thousands of lines and dozens of files use it to plan refactors, fix bugs, and deliver projects with minimal hand-holding.
Platform teams track API pricing and limits to budget for context caching and structured output before the official API goes live.
Self-hosters watch for open weights to plan hardware, quantization, and license review, following the previous MIT precedent.
GLM 5.3 is available in glm5.app Chat today, with the official model API expected to follow.
Open Chat on glm5.app, describe the problem, constraints, and desired outcome, then refine the response with your code.
For coding-tool integrations today, the Z.ai Coding Plan already serves it in tools like Claude Code, Cline, and OpenCode.
For glm5.app API access, use model ID `glm-5.3` with the OpenAI-compatible base URL `https://glm5.app/api/v1`.
Integration specimen
The official GLM 5.3 model API is coming soon from Z.ai. glm5.app exposes an OpenAI-compatible Chat Completions endpoint today, and the official model ID will be added here when published.
Open API documentationcurl https://glm5.app/api/v1/chat/completions \
-H "Authorization: Bearer $GLM5_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "glm-5.3",
"messages": [{
"role": "user",
"content": "Plan this refactor and list the rollback steps."
}]
}'Clear GLM 5.3 answers about release date, pricing, benchmarks, Hugging Face, parameters, weights, the coding plan, and the upgrade from 5.2.
The new flagship large language model from Z.ai, announced in August 2026.
The official model page and benchmarks arrived in August 2026. The GLM Coding Plan already serves it, and the model API is expected to go live shortly.
API pricing has not been published. For reference, the previous flagship costs about $1.40 input and $4.40 output per million tokens.
Weights are not on Hugging Face yet. Z.ai open-sourced the previous model under the MIT license, so a release there is widely expected, but it has not been published as of August 2026.
Parameter counts are unpublished; the official page lists 1M-token context and 128K maximum output. Totals likely follow the GLM 5 family MoE architecture.
Weights are expected under the MIT license, following the previous release on Hugging Face. Z.ai has not confirmed the license yet, so treat open-weights details as unconfirmed.
The Z.ai Coding Plan — a subscription for AI coding tools like Claude Code, Cline, and OpenCode — has fully rolled out the new model.
Chat with it free in glm5.app Chat today; the GLM Coding Plan also serves it. The public model API is expected to go live soon, and this page will update with the official ID and limits when announced.
Yes — glm5.3, GLM-5.3, and GLM 5.3 are spelling variants of the same model.
Start here
Chat with GLM 5.3 free on glm5.app, and track the official API, pricing, and open-source news here.