GLM-4.5 Chat: pricing, context window and benchmarks
GLM-4.5 Chat is a multimodal model from Zhipu AI. It offers a 65,536-token context window, costs $4.53 per million input tokens and $21.22 per million output tokens, and averages 78.3 across the index's benchmark suite.
Pricing
GLM-4.5 Chat costs $4.53 per million input tokens and $21.22 per million output tokens. A blended 3:1 input-to-output mix works out to about $8.70 per million tokens. Cached input is listed at $0.56 per million tokens.
| Item | Price | Notes |
|---|---|---|
| Input | $4.53 | per 1M tokens |
| Output | $21.22 | per 1M tokens |
| Cached input | $0.56 | per 1M tokens |
| Blended 3:1 | $8.70 | estimate per 1M tokens |
| 1M in + 1M out | $25.75 | 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 | 81.7 | 130 | 78th | |
| GPQA Diamond | 74.3 | 159 | 74th | |
| SWE-bench Verified | 69.6 | 121 | 80th | |
| HumanEval | 83.8 | 137 | 77th | |
| MATH-500 | 82.8 | 149 | 75th | |
| AIME 2025 | 70.7 | 243 | 60th | |
| LiveCodeBench | 68.9 | 209 | 65th | |
| IFEval | 84.5 | 201 | 67th | |
| TruthfulQA | 81.6 | 139 | 77th | |
| HellaSwag | 88.1 | 138 | 77th | |
| MMMU | 75.6 | 148 | 75th | |
| Arena Elo | 1418.6 | 155 | 74th |
What GLM-4.5 Chat is good for
GLM-4.5 Chat 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 $4.53 per million input tokens, it sits in the mid-range of the index, and the 65,536-token context window is enough for large files and multi-file diffs.
Strengths
- 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 Chat | Zhipu AI | 65536 | $4.53 | 78.3 |
| Hunyuan-Turbo Max | Tencent | 128000 | $12.40 | 78.3 |
| 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 |
FAQ
How much does GLM-4.5 Chat cost?
GLM-4.5 Chat is listed at $4.53 per million input tokens and $21.22 per million output tokens. Cached input is $0.56 per million tokens. A blended 3:1 input-to-output mix is about $8.70 per million tokens.
What is the context window of GLM-4.5 Chat?
GLM-4.5 Chat has a context window of 65,536 tokens and can emit up to 8,192 output tokens per request in this index.
Is GLM-4.5 Chat open weights?
Yes. GLM-4.5 Chat is listed as an open-weight model under a open weights licence.
How does GLM-4.5 Chat score on benchmarks?
GLM-4.5 Chat averages 78.3 across the scored benchmarks in this index, ranking #161 of 600 models. Its strongest relative result is Arena Elo at 1418.6.
What is GLM-4.5 Chat best for?
GLM-4.5 Chat 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 $4.53 per million input tokens, it sits in the mid-range of the index, and the 65,536-token context window is enough for large files and multi-file diffs.