Z.ai: GLM 5.2
z-ai/glm-5.2
Model weightsGLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering, and complex multi-step automation.
Reasoning efforts high and xhigh are supported; xhigh maps to max reasoning. It is particularly strong at coding and tool use across long-running tasks, able to maintain engineering context and follow standards consistently through a full development workflow, from requirements to multi-platform deployment, in a single task.
Providers
Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick: Balanced (price + speed), Nitro (fastest), or Floor (cheapest).
| $0.6200 | $2.4200 | $0.1400 | 0.46s | 198 tok/s | ||
| $0.0070 | $6.8000 | $0.0060 | 0.47s | 115 tok/s | ||
| $1.4000 | $4.4000 | $0.2600 | 0.29s | 172 tok/s | ||
| $1.5400 | $4.8400 | $0.1540 | 0.79s | 183 tok/s | ||
87% off | $1.40$0.1890 | $4.40$0.5940 | $0.26$0.0351 | 1.12s | 60 tok/s | |
| $0.1900 | $8.0000 | $0.1800 | 0.47s | 117 tok/s | ||
| $0.5950 | $1.8310 | $0.2010 | 0.50s | 80 tok/s | ||
54% off | $1.40$0.6496 | $4.40$2.0420 | $0.26$0.1206 | 2.13s | 82 tok/s | |
| $0.0066 | $7.9833 | $0.0066 | 1.08s | 87 tok/s | ||
50% off | $1.302$0.6510 | $4.092$2.0460 | $0.26$0.1300 | 1.20s | 71 tok/s | |
| $1.4000 | $4.4000 | $0.1400 | 1.46s | 107 tok/s | ||
| $0.7000 | $2.2000 | $0.1050 | 0.58s | 91 tok/s | ||
| $1.4000 | $4.4000 | $0.2600 | 0.32s | 101 tok/s | ||
| $1.4000 | $4.4000 | $0.2600 | 0.45s | 149 tok/s | ||
| $0.1900 | $8.0000 | $0.1900 | 1.25s | 76 tok/s | ||
80% off | $1.40$0.2800 | $4.40$0.8800 | $0.26$0.0520 | 1.45s | 45 tok/s | |
| $0.75$0.5625 | $2.40$1.8000 | $0.14$0.1050 | 0.86s | 59 tok/s | ||
| $0.9660 | $3.0360 | $0.1932 | 1.20s | 63 tok/s | ||
| $1.4000 | $4.4000 | $0.1400 | 0.95s | 103 tok/s | ||
| $1.4000 | $4.4000 | $0.2600 | 1.06s | 81 tok/s | ||
| $2.1000 | $6.6000 | $0.2100 | 0.34s | 234 tok/s | ||
| $1.4000 | $4.4000 | $0.1400 | 2.09s | 45 tok/s | ||
| $1.4000 | $4.4000 | $0.2600 | 0.70s | 111 tok/s | ||
33% off | $1.40$0.9380 | $4.40$2.9480 | $0.26$0.1742 | 2.23s | 47 tok/s | |
| $1.1200 | $3.5200 | $0.2240 | 1.02s | 57 tok/s | ||
| $1.4000 | $4.4000 | $0.2600 | 1.31s | 55 tok/s | ||
| $1.4000 | $4.4000 | $0.1400 | 0.73s | 75 tok/s | ||
Fast | $2.1000 | $6.6000 | $0.2100 | 0.37s | 168 tok/s | |
| $1.4000 | $4.4000 | $0.2600 | 2.57s | 45 tok/s | ||
Fast | $2.2500 | $7.8800 | $0.5600 | 0.76s | 77 tok/s | |
Fast | $2.3100 | $7.2600 | $0.4620 | 1.31s | 105 tok/s | |
| $0.6000 | $2.0000 | $0.1500 | 1.69s | 12 tok/s | ||
Not used in Standard routing:Why these endpoints are not used | ||||||
| $0.60$0.4500 | $1.92$1.4400 | $0.112$0.0840 | 2.84s | 55 tok/s | ||
- Input $0.62 / Output $2.42198 tok/s99.88% uptime
- Input $0.007 / Output $6.80115 tok/s100.00% uptime
- Input $1.40 / Output $4.40172 tok/s99.88% uptime
Input $1.54 / Output $4.84183 tok/s99.57% uptime- Input $0.189 / Output $0.59487% off60 tok/s99.91% uptime
- Input $0.19 / Output $8.00117 tok/s100.00% uptime
- Input $0.595 / Output $1.83180 tok/s99.80% uptime
- Input $0.6496 / Output $2.04254% off82 tok/s99.97% uptime
- Input $0.0066 / Output $7.983387 tok/s99.91% uptime
- Input $0.651 / Output $2.04650% off71 tok/s99.97% uptime
- Input $1.40 / Output $4.40107 tok/s100.00% uptime
- Input $0.70 / Output $2.2091 tok/s99.63% uptime
- Input $1.40 / Output $4.40101 tok/s99.62% uptime
- Input $1.40 / Output $4.40149 tok/s100.00% uptime
- Input $0.19 / Output $8.0076 tok/s100.00% uptime
- Input $0.28 / Output $0.8880% off45 tok/s100.00% uptime
Input $0.5625 / Output $1.8025% off59 tok/s99.49% uptime- Input $0.966 / Output $3.03663 tok/s98.35% uptime
Input $1.40 / Output $4.40103 tok/s99.63% uptime- Input $1.40 / Output $4.4081 tok/s100.00% uptime
- Input $2.10 / Output $6.60234 tok/s99.89% uptimeFast
- Input $1.40 / Output $4.4045 tok/s100.00% uptime
- Input $1.40 / Output $4.40111 tok/s98.85% uptime
- Input $0.938 / Output $2.94833% off47 tok/s99.46% uptime
- Input $1.12 / Output $3.5257 tok/s100.00% uptime
- Input $1.40 / Output $4.4055 tok/s97.67% uptime
- Input $1.40 / Output $4.4075 tok/s87.79% uptime
- Input $2.10 / Output $6.60168 tok/s99.78% uptimeFast
- Input $1.40 / Output $4.4045 tok/s100.00% uptime
- Input $2.25 / Output $7.8877 tok/s100.00% uptimeFast
- Input $2.31 / Output $7.26105 tok/s100.00% uptimeFast
- Input $0.60 / Output $2.0012 tok/s79.37% uptime
- Not used in Standard routing:Why these endpoints are not used
Input $0.45 / Output $1.4455 tok/s100.00% uptimeFlex+11 more label
Pricing
The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.
Weighted average
GLM 5.2 — Price history
| $0.00614 | $6.800 | 85.6% | 18.5% | ||
| $0.00659 | $7.983 | 80.2% | 2.7% | ||
| $0.07692 | $0.879 | 89.1% | 7.0% | ||
| $0.08321 | $0.593 | 68.7% | 9.4% | ||
| $0.18100 | $8.000 | 89.9% | 6.4% | ||
| $0.18998 | $8.000 | 69.8% | 0.5% | ||
| $0.21127 | $2.048 | 84.4% | 1.4% | ||
| $0.21177 | $2.200 | 82.1% | 0.5% | ||
| $0.25268 | $2.419 | 76.5% | 22.8% | ||
| $0.25763 | $2.043 | 74.3% | 3.4% | ||
| $0.27791 | $4.400 | 89.1% | 0.4% | ||
| $0.30270 | $1.805 | 56.9% | 2.8% | ||
| $0.34833 | $1.944 | 67.4% | 0.6% | ||
| $0.36924 | $3.036 | 77.2% | 0.1% | ||
| $0.40197 | $4.840 | 82.1% | 1.5% | ||
| $0.42145 | $4.399 | 85.8% | 5.5% | ||
| $0.43770 | $4.400 | 76.4% | 1.5% | ||
| $0.46738 | $2.947 | 61.6% | 0.0% | ||
| $0.48295 | $4.398 | 80.4% | 1.9% | ||
Fast | $0.51853 | $7.260 | 96.9% | 4.0% | |
| $0.54447 | $4.400 | 75.0% | 2.1% | ||
| $0.60362 | $4.399 | 69.9% | 0.5% | ||
| $0.60589 | $3.519 | 57.4% | 0.1% | ||
Fast | $0.62135 | $6.599 | 78.2% | 0.3% | |
| $0.70216 | $4.400 | 61.2% | 0.4% | ||
| $0.73056 | $4.399 | 53.1% | 0.8% | ||
| $0.79507 | $6.600 | 69.0% | 0.7% | ||
| $0.84220 | $4.400 | 48.9% | 2.6% | ||
| $0.84338 | $4.399 | 48.8% | 0.0% | ||
| $0.88251 | $4.399 | 41.1% | 1.3% | ||
Fast | $1.50338 | $7.879 | 44.2% | 0.1% | |
| $0.52036 | $2.000 | 17.7% | 0.1% | ||
Not used in Standard routing:Why these endpoints are not used | |||||
| $0.25684 | $1.439 | 52.8% | 0.1% | ||
- Effective in $0.00614 / Effective out $6.800Token share18.5%
- Effective in $0.00659 / Effective out $7.983Token share2.7%
- Effective in $0.07692 / Effective out $0.879Token share7.0%
- Effective in $0.08321 / Effective out $0.593Token share9.4%
- Effective in $0.18100 / Effective out $8.000Token share6.4%
- Effective in $0.18998 / Effective out $8.000Token share0.5%
- Effective in $0.21127 / Effective out $2.048Token share1.4%
- Effective in $0.21177 / Effective out $2.200Token share0.5%
- Effective in $0.25268 / Effective out $2.419Token share22.8%
- Effective in $0.25763 / Effective out $2.043Token share3.4%
- Effective in $0.27791 / Effective out $4.400Token share0.4%
- Effective in $0.30270 / Effective out $1.805Token share2.8%
- Effective in $0.34833 / Effective out $1.944Token share0.6%
- Effective in $0.36924 / Effective out $3.036Token share0.1%
- Effective in $0.40197 / Effective out $4.840Token share1.5%
- Effective in $0.42145 / Effective out $4.399Token share5.5%
- Effective in $0.43770 / Effective out $4.400Token share1.5%
- Effective in $0.46738 / Effective out $2.947Token share0.0%
- Effective in $0.48295 / Effective out $4.398Token share1.9%
- Effective in $0.51853 / Effective out $7.260FastToken share4.0%
- Effective in $0.54447 / Effective out $4.400Token share2.1%
- Effective in $0.60362 / Effective out $4.399Token share0.5%
- Effective in $0.60589 / Effective out $3.519Token share0.1%
- Effective in $0.62135 / Effective out $6.599FastToken share0.3%
- Effective in $0.70216 / Effective out $4.400Token share0.4%
- Effective in $0.73056 / Effective out $4.399Token share0.8%
- Effective in $0.79507 / Effective out $6.600FastToken share0.7%
- Effective in $0.84220 / Effective out $4.400Token share2.6%
- Effective in $0.84338 / Effective out $4.399Token share0.0%
- Effective in $0.88251 / Effective out $4.399Token share1.3%
- Effective in $1.50338 / Effective out $7.879FastToken share0.1%
- Effective in $0.52036 / Effective out $2.000Token share0.1%
- Not used in Standard routing:Why these endpoints are not used
- Effective in $0.25684 / Effective out $1.439FlexToken share0.1%
Performance
Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).
P50, best across providers
P50, best provider
Uptime
Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.
Availability over the last 3 days
Last 72 hoursAvailability over the last 24 hours
When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.
Benchmarks
Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.
| Source | Benchmark | Score |
|---|---|---|
| Artificial Analysis | GLM-5.2 (Non-reasoning) Coding Index | 46.5 |
| Artificial Analysis | GLM-5.2 (Non-reasoning) GPQA Diamond | 68.6% |
| Artificial Analysis | GLM-5.2 (Non-reasoning) HLE | 9.8% |
| Artificial Analysis | GLM-5.2 (Non-reasoning) AA-LCR | 42.3% |
| Artificial Analysis | GLM-5.2 (Non-reasoning) τ-Bench Banking | 16.7% |
| Artificial Analysis | GLM-5.2 (Non-reasoning) GDPval-AA | 37.6% |
| Artificial Analysis | GLM-5.2 (Non-reasoning) CritPt | 3.1% |
| Artificial Analysis | GLM-5.2 (Non-reasoning) Terminal-Bench 2.1 | 51.7% |
| Artificial Analysis | GLM-5.2 (Max) Coding Index | 68.8 |
| Artificial Analysis | GLM-5.2 (Max) Agentic Index | 38.4 |
| Artificial Analysis | GLM-5.2 (Max) GPQA Diamond | 89.5% |
| Artificial Analysis | GLM-5.2 (Max) HLE | 41.1% |
| Artificial Analysis | GLM-5.2 (Max) IFBench | 73.3% |
| Artificial Analysis | GLM-5.2 (Max) τ²-Bench Telecom | 99.1% |
| Artificial Analysis | GLM-5.2 (Max) AA-LCR | 78.3% |
| Artificial Analysis | GLM-5.2 (Max) τ-Bench Banking | 34.6% |
| Artificial Analysis | GLM-5.2 (Max) GDPval-AA | 44.1% |
| Artificial Analysis | GLM-5.2 (Max) CritPt | 20.9% |
| Artificial Analysis | GLM-5.2 (Max) SciCode | 51.2% |
| Artificial Analysis | GLM-5.2 (Max) Terminal-Bench Hard | 50.8% |
| Artificial Analysis | GLM-5.2 (Max) Terminal-Bench 4.0 | 1.0% |
| Artificial Analysis | GLM-5.2 (Max) Terminal-Bench 2.1 | 77.9% |
| Artificial Analysis | GLM-5.2 (Max) AA-Omniscience Accuracy | 21.1% |
| Artificial Analysis | GLM-5.2 (Max) AA-Omniscience Non-Hallucination Rate | 74.1% |
| Design Arena | GLM 5.2 Agents Arena Agenticgamedev Elo | 1159 |
| Design Arena | GLM 5.2 Agents Arena Androidnative Elo | 1170 |
| Design Arena | GLM 5.2 Agents Arena Blender3d Elo | 983 |
| Design Arena | GLM 5.2 Agents Arena Full Stack Elo | 1215 |
| Design Arena | GLM 5.2 Agents Arena Godotgamedev Elo | 1142 |
| Design Arena | GLM 5.2 Agents Arena Htmlslides Elo | 1071 |
| Design Arena | GLM 5.2 Agents Arena Mobile Apps Elo | 1153 |
| Design Arena | GLM 5.2 Agents Arena Pdf Elo | 1246 |
| Design Arena | GLM 5.2 Agents Arena Python-Pptxslides Elo | 1160 |
| Design Arena | GLM 5.2 Agents Arena Spreadsheet Elo | 1011 |
| Design Arena | GLM 5.2 Agents Arena Webapps Elo | 1202 |
| Design Arena | GLM 5.2 Models Arena 3D Elo | 1266 |
| Design Arena | GLM 5.2 Models Arena Asciiart Elo | 1185 |
| Design Arena | GLM 5.2 Models Arena Code Categories Elo | 1277 |
| Design Arena | GLM 5.2 Models Arena Data Visualization Elo | 1282 |
| Design Arena | GLM 5.2 Models Arena Game Development Elo | 1256 |
| Design Arena | GLM 5.2 Models Arena SVG Elo | 1195 |
| Design Arena | GLM 5.2 Models Arena UI Component Elo | 1286 |
| Design Arena | GLM 5.2 Models Arena Website Elo | 1277 |
| Vals AI | GLM 5.2 Code Migration | 37.9% |
| Vals AI | GLM 5.2 CorpFin v2 | 66.1% |
| Vals AI | GLM 5.2 EMB | 61.5% |
| Vals AI | GLM 5.2 Finance Agent (v2) | 49.7% |
| Vals AI | GLM 5.2 GPQA Diamond | 85.6% |
| Vals AI | GLM 5.2 Harvey's Legal Agent Benchmark v1 | 7.1% |
| Vals AI | GLM 5.2 LiveCodeBench | 69.5% |
| Vals AI | GLM 5.2 LegalBench | 84.1% |
| Vals AI | GLM 5.2 Legal Research Bench | 31.3% |
| Vals AI | GLM 5.2 MedCode | 40.8% |
| Vals AI | GLM 5.2 MedScribe | 83.5% |
| Vals AI | GLM 5.2 MMLU Pro | 86.7% |
| Vals AI | GLM 5.2 ProgramBench | 0.5% |
| Vals AI | GLM 5.2 ProofBench v1 | 35.0% |
| Vals AI | GLM 5.2 SkillsBench | 45.1% |
| Vals AI | GLM 5.2 SRE Bench | 0.0% |
| Vals AI | GLM 5.2 SWE-bench | 82.8% |
| Vals AI | GLM 5.2 TaxEval v2 | 73.3% |
| Vals AI | GLM 5.2 Terminal-Bench 2.1 | 67.8% |
| Vals AI | GLM 5.2 Vals Index | 53.1% |
| Vals AI | GLM 5.2 Vibe Code Bench v1.1 | 64.0% |
Apps
Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.
Activity
Token volume and request traffic to this model over time.
API
Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.
Available through EU in-region routing
Z.ai: GLM 5.2 is available through EU in-region routing. Requests sent to eu.openrouter.ai are decrypted in the EU and routed only to shared provider endpoints in Europe (the EU/EEA, the UK, and Switzerland).
- Providers in Europe
- Inceptron, Mistral
- Prices in Europe
- Inceptron: $1.40/M tokens input, $4.40/M tokens output
- Mistral: $1.54/M tokens input, $4.84/M tokens output
- Base URL
https://eu.openrouter.ai/api/v1- Plan
- Requires Business or Enterprise. Self-serve on Business: no contract, no monthly minimum. OpenRouter Business for EU in-region routing
Fails closed: if no shared provider endpoint in Europe is available, the request errors instead of leaving the region. Requests served by your own BYOK key go to your deployment’s region, which you control. In-region routing docs
Frequently asked questions
GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering, and complex multi-step automation. Reasoning efforts high and xhigh are supported; xhigh maps to max reasoning.
GLM 5.2 costs $0.0066/M input tokens and $7.983/M output tokens, with separate rates for Cache Read at $0.0066/M tokens.
GLM 5.2 has a 1,048,576 token context window. It supports up to 131,072 completion tokens.
Yes. GLM 5.2 accepts tools for function calling. It also supports structured outputs via a JSON schema in response_format.
GLM 5.2 is served by 24 providers on OpenRouter: Relace, Wafer, Baidu Qianfan (fp8), Cloudflare, StreamLake, DeepInfra, Morph, Ambient and 16 more. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.
GLM 5.2 was released on June 16, 2026.