GLM-5.2
01
Snapshot
Overall
73
rank #10 of 22
Coding
66
rank #15 of 22
Multimodal
79
rank #12 of 22
Input / Output
$1.4 / $4.4
USD per 1M tokens
Context
128K
usable recall 88
Speed
~50 tok/s
TTFT 0.6s
Aggregated from public sources and independently weighted; methodology on the Terms page. Scores within 3 points are treated as statistically tied.
02
Specs & pricing
Every tracked field. List API prices in USD per 1M tokens; verify current vendor pricing before purchase.
| Vendor | Zhipu AI (CN) |
| Released / current | 2026.06 |
| Licensing | Open weights |
| Context window | 128K |
| Max output | 64K |
| Effective-context score | 88 |
| Input / output price | $1.4 / $4.4 per 1M tokens |
| Cache discount | No published cache discount |
| Free tier | ChatGLM free; free quota on the open platform |
| Speed / TTFT | ~50 tok/s / 0.6s |
| Function calling | 80 |
| Refusal rate | ~8% |
| English / Chinese | 70 / 90 |
| Modalities | text, image |
| Fine-tuning | Yes |
| Private deployment | Yes (enterprise) |
| SOC2 / no-train | no / yes |
03
Strengths & watch-outs
Strengths
- Strong open-source ecosystem
- Good Chinese
- Mature enterprise services
Watch-outs
- Mid overall performance
- Average multimodal
04
Where it ranks among 22 models
Overall 73/100 (#10), coding 66 (#15), multimodal 79 (#12). See the full boards and side-by-side compare on the leaderboard.
05
Pricing in practice
Illustrative monthly bill for 100M input + 30M output tokens: $272 at list. Your mix and cache-hit ratio change this.
Illustrative model using public list rates before any enterprise agreement; cache discount: No published cache discount.
06
Frequently asked questions
How much does GLM-5.2 cost?
List API pricing is $1.4 input and $4.4 output per 1M tokens. No published cache discount. ChatGLM free; free quota on the open platform
What is GLM-5.2's context window, and is it usable end to end?
It advertises a 128K window with 64K max output; its effective-context score is 88/100, which is the better predictor of whether long-document details are actually retained.
Is GLM-5.2 good for coding?
Its coding aggregate is 66/100, rank #15 of 22. It is adequate for scripts and assisted completion rather than the most demanding SWE-style work.
Can I self-host GLM-5.2?
Yes — it ships open weights and supports private deployment, so you can run it on your own infrastructure for data control; budget for GPU and operations.
How strong is it in Chinese and on multimodal inputs?
Chinese score is 90 versus English 70; multimodal aggregate is 79/100 (rank #12), accepting text, image.