GLM / Z.ai (Zhipu AI) vs Augment Code Intent
Which one should you pick? Here's the full breakdown.
GLM / Z.ai (Zhipu AI)
Zhipu AI's open-weights family -- GLM-5.1 (launched 2026-04-07) is 744B MoE / 40B active, topped SWE-Bench Pro at 58.4 (beating GPT-5.4 and Claude Opus 4.6), MIT licensed, 200K context. Trained entirely on 100K Huawei Ascend 910B chips -- first frontier model with zero Nvidia in the training stack
Augment Code Intent
Spec-driven multi-agent orchestration for code -- coordinator + implementor agents in isolated git worktrees + verifier. Works with Augment's Auggie, Claude Code, Codex, and OpenCode. Public beta 2026-02-10
| Category | GLM / Z.ai (Zhipu AI) | Augment Code Intent |
|---|---|---|
| Ease of Use | 6.5 | 7.0 |
| Output Quality | 8.5 | 8.0 |
| Value | 9.0 | 8.0 |
| Features | 8.0 | 9.0 |
| Overall | 8.0 | 8.0 |
Pricing Comparison
| Feature | GLM / Z.ai (Zhipu AI) | Augment Code Intent |
|---|---|---|
| Free Tier | Yes | No |
| Starting Price | $0 | Included in Auggie subscription |
Benchmark Head-to-Head
GLM-5.1 (744B MoE / 40B active) benchmarks — Augment Code Intent has no published benchmarks
| Benchmark | Description | Score |
|---|---|---|
| SWE-Bench Pro | 58.4% | |
| MMLU-Pro | Harder multi-subject reasoning | 81.2% |
| GPQA Diamond | Graduate-level science questions | 74.5% |
| HumanEval | Python code generation | 89.1% |
| SWE-Bench Verified | 64.2% | |
| BFCL (function calling) | 88% |
Which Should You Pick?
Pick GLM / Z.ai (Zhipu AI) if...
- ✓Better value for money (9/10)
- ✓Has a free tier
Teams that need genuine MIT-licensed frontier open weights with no commercial strings. Especially strong for agentic workflows and vision (GLM-4.6V).
Visit GLM / Z.ai (Zhipu AI)Pick Augment Code Intent if...
- ✓More features (9 vs 8)
Engineering teams already using Augment Code's Auggie or running mixed Claude-Code + Codex workflows who want higher-level orchestration than writing LangGraph graphs from scratch. Also teams that want git-worktree-isolated parallel agent work with a verifier in the loop.
Visit Augment Code IntentOur Verdict
GLM / Z.ai (Zhipu AI) and Augment Code Intent are extremely close overall. Your choice comes down to specific needs -- GLM / Z.ai (Zhipu AI) is better for teams that need genuine mit-licensed frontier open weights with no commercial strings, while Augment Code Intent works best for engineering teams already using augment code's auggie or running mixed claude-code + codex workflows who want higher-level orchestration than writing langgraph graphs from scratch.