GLM-5.2 vs Goose
GLM-5.2 (freemium, AI Score 8.7/10) vs Goose (free, AI Score 8.2/10). Side-by-side pricing, features, pros and cons, and which to pick.
The verdict
- →overall capability matters more than price (AI Score 8.7 vs 8.2)
- →you want our editor's pick for this category
Side-by-side specs
| Spec | GLM-5.2 | Goose |
|---|---|---|
| Category | Coding | Coding |
| Pricing model | freemium | free |
| Headline pricing | Free 20M tokens on signup + open weights; paid API & coding plans (check site) | Free (open-source, Apache 2.0) |
| Free tier | Free chat access plus 20M free tokens on API signup, and open weights available to download and self-host under MIT. | Completely free and open-source (Apache 2.0). You pay only for LLM API usage from your chosen provider. |
| AI Score | 8.7/10 | 8.2/10 |
| Best for | — | — |
| Editor's pick | ✓ Yes | — |
| Use cases | — | — |
| Date added | 2026-06-27 | 2026-06-07 |
Pros and cons
GLM-5.2
Coding · freemium
Pros
- ✓MIT-licensed open weights — full commercial use, self-hosting, and fine-tuning with no revocable API terms
- ✓1M-token context handles whole codebases and long agent histories in one pass
- ✓Benchmark results competitive with top closed frontier models, especially on coding and agentic tasks
- ✓Genuinely free to start: chat UI, 20M signup tokens, or download the weights
- ✓Strong fit for coding agents thanks to its long-horizon, tool-use orientation
Cons
- ×At 744B parameters, self-hosting demands serious GPU hardware — out of reach for most individual developers
- ×Vendor-published benchmarks need independent verification; real-world coding performance may vary from the claims
- ×Hosted API and coding-plan pricing isn't transparently listed, so budgeting requires checking the site
- ×As a model from Zhipu AI, some enterprises face data-residency or procurement constraints around China-based providers
Goose
Coding · free
Pros
- ✓Completely free and open-source with no vendor lock-in
- ✓Full local execution keeps your code private by default
- ✓MCP-based extension system is genuinely modular and community-driven
- ✓Model-agnostic — use any LLM provider or run local models via Ollama
Cons
- ×Requires your own API keys and managing LLM costs separately
- ×More setup friction than turnkey editors like Cursor or Windsurf
- ×No built-in IDE — it's an agent, not an editor, so you still need your own code editor
- ×Agent autonomy can be unpredictable without careful prompt guidance
FAQ
Is GLM-5.2 better than Goose? ▾
GLM-5.2 scores 8.7/10 in our evaluation versus Goose at 8.2/10. GLM-5.2 edges ahead overall, but "better" depends on your use case — see the verdict block above.
Does GLM-5.2 or Goose have a free tier? ▾
Both offer free access. GLM-5.2: Free chat access plus 20M free tokens on API signup, and open weights available to download and self-host under MIT.. Goose: Completely free and open-source (Apache 2.0). You pay only for LLM API usage from your chosen provider..
Should I choose GLM-5.2 or Goose in 2026? ▾
If overall capability matters more than price (AI Score 8.7 vs 8.2) pick GLM-5.2. If budget is the constraint pick Goose. Both are credible — neither is a wrong choice.
Related comparisons
Updated 2026-06-27. Spec data sourced from official product pages and tracked in our public directory at /tools.