GLM-5.3
FlagshipGLM-5.3 is Z.ai's August 2026 flagship, and the interesting part is how it was built: not a new pretrain, but extended post-training on the same base as GLM-5.2. The gains are concentrated where that kind of work pays off. Terminal-Bench 3.0 jumped from 4.6 to 28.3, DeepSWE v1.1 went from 46.2 to 66.9, and independent evaluation puts it at 95.4 on SWE-bench Verified. Z.ai also reports 62.5 on Humanity's Last Exam with tools and a notable cybersecurity capability that emerged rather than being targeted, with 54.4 on ExploitBench and 84.5 on CyberGym. Pricing is $1.40 per million input tokens and $4.40 output, with a 1M token context window and 128K max output. It launched API-first through the Z.ai API and Coding Plan, and the weights have since landed ungated on Hugging Face at zai-org/GLM-5.3, roughly 753 billion parameters. Read the license before you deploy. It is a custom GLM-5.3 License rather than the plain MIT that covered GLM-5.2: permissive for almost everyone, but any Model-as-a-Service operator whose group revenue tops $10 billion over 12 months must pass a Z.ai security review before commercial use. Treat every score here as vendor-reported except the independently run SWE-bench figure.
Input Price
$1.40
per 1M tokens
Output Price
$4.40
per 1M tokens
Context Window
1.0M
tokens
Released
2026-08
Open source
Capabilities
Key Strengths
- ✓Terminal-Bench 3.0 of 28.3, up from 4.6 on GLM-5.2
- ✓95.4 on SWE-bench Verified from an independent evaluator
- ✓1M token context with 128K max output
- ✓$1.40/$4.40 pricing, far below comparable frontier coding models
- ✓Emergent cybersecurity capability: 84.5 CyberGym, 54.4 ExploitBench
Best For
- ▸Agentic coding and long-horizon software tasks
- ▸Security research and exploit reasoning
- ▸Cost-sensitive frontier workloads
- ▸Self-hosted deployment for teams under the license revenue threshold
Benchmark Scores
| Benchmark | Score | Description |
|---|---|---|
| SWE-bench | 95.4 | Real-world software engineering tasks from GitHub issues (SWE-bench Verified) |
| MMLU-Pro | 86.8 | General knowledge and reasoning across 57 subjects |
| GPQA Diamond | 88.1 | Graduate-level science questions verified by domain experts |
| FrontierCode v1.1 | 40.1 | Agentic coding on frontier software engineering tasks (Main split) |
| Terminal-Bench 4.0 | 25.3 | Long-horizon agentic work in a terminal across software, science, ML, operations, hardware, security, and media (66 tasks, all-or-nothing verifiers) |
| Humanity's Last Exam (tools) | 62.5 | Multidisciplinary expert-level reasoning with tool access |
Scores sourced from public benchmark datasets. See full benchmark leaderboard for all models.
Pricing Details
Input tokens
$1.40
per 1M tokens
Output tokens
$4.40
per 1M tokens
Estimated cost per 1K requests
$3.60
~1K input + ~500 output tokens avg
Prices are subject to change. Check the official documentation for current pricing. See the cost calculator for detailed estimates.
Open Source Model
GLM-5.3 is free to download and self-host under the GLM-5.3 License. Hosted API pricing varies by provider (e.g., Together, Fireworks, Groq). See our open source LLM guide for deployment options.
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