GLM-4.5: pricing, context window and benchmarks
GLM-4.5 is a multimodal model from Zhipu AI. It offers a 200,000-token context window, costs $4.55 per million input tokens and $20.60 per million output tokens, and averages 78.2 across the index's benchmark suite.
Pricing
GLM-4.5 costs $4.55 per million input tokens and $20.60 per million output tokens. A blended 3:1 input-to-output mix works out to about $8.56 per million tokens. Cached input is listed at $0.68 per million tokens.
| Item | Price | Notes |
|---|---|---|
| Input | $4.55 | per 1M tokens |
| Output | $20.60 | per 1M tokens |
| Cached input | $0.68 | per 1M tokens |
| Blended 3:1 | $8.56 | estimate per 1M tokens |
| 1M in + 1M out | $25.15 | estimate |
Benchmarks
Scores below are modelled estimates on a 0–100 scale. Use them to compare relative position, not as official vendor results.
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 78.8 | 215 | 64th | |
| GPQA Diamond | 74.9 | 147 | 76th | |
| SWE-bench Verified | 66.4 | 181 | 70th | |
| HumanEval | 81.6 | 193 | 68th | |
| MATH-500 | 81.7 | 170 | 72th | |
| AIME 2025 | 76.0 | 141 | 77th | |
| LiveCodeBench | 73.0 | 127 | 79th | |
| IFEval | 85.8 | 164 | 73th | |
| TruthfulQA | 79.7 | 193 | 68th | |
| HellaSwag | 88.8 | 117 | 81th | |
| MMMU | 73.9 | 194 | 68th | |
| Arena Elo | 1414.6 | 169 | 72th |
What GLM-4.5 is good for
GLM-4.5 is tuned toward coding work. It is a reasonable candidate for code generation, review, debugging and repository-scale tasks, especially when paired with a retrieval layer. At $4.55 per million input tokens, it sits in the mid-range of the index, and the 200,000-token context window is enough for large files and multi-file diffs.
Strengths
- Large 200,000-token context window for long documents and agent traces.
- Open weights make self-hosting, fine-tuning and data-residency review possible.
- Accepts more than text, including image input where the provider supports it.
- Coding benchmarks are a relative strength within its tier.
Trade-offs
- No standout weakness in the indexed specifications, but real-world behaviour still needs testing.
How it compares
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| GLM-4.5 | Zhipu AI | 200000 | $4.55 | 78.2 |
| Hunyuan-Large | Tencent | 65536 | $4.33 | 78.2 |
| Hunyuan-Large Instruct | Tencent | 65536 | $4.39 | 78.2 |
| Llama 3.3 | Meta AI | 128000 | $4.56 | 78.2 |
| Mistral Large 3 Base | Mistral AI | 65536 | $4.47 | 78.2 |
| QwQ Chat | Alibaba Cloud | 65536 | $4.28 | 78.2 |
FAQ
How much does GLM-4.5 cost?
GLM-4.5 is listed at $4.55 per million input tokens and $20.60 per million output tokens. Cached input is $0.68 per million tokens. A blended 3:1 input-to-output mix is about $8.56 per million tokens.
What is the context window of GLM-4.5?
GLM-4.5 has a context window of 200,000 tokens and can emit up to 32,768 output tokens per request in this index.
Is GLM-4.5 open weights?
Yes. GLM-4.5 is listed as an open-weight model under a open weights licence.
How does GLM-4.5 score on benchmarks?
GLM-4.5 averages 78.2 across the scored benchmarks in this index, ranking #163 of 600 models. Its strongest relative result is Arena Elo at 1414.6.
What is GLM-4.5 best for?
GLM-4.5 is tuned toward coding work. It is a reasonable candidate for code generation, review, debugging and repository-scale tasks, especially when paired with a retrieval layer. At $4.55 per million input tokens, it sits in the mid-range of the index, and the 200,000-token context window is enough for large files and multi-file diffs.