Z.ai (Zhipu), open weights

# GLM-4.5V

> GLM-4.5V by Z.ai (Zhipu), released August 2025. Ranked #158 of 354 with a Noometry Index of 39.8. API: $0.60 in / $1.80 out per M tokens. 64K context. Scores, sources and comparisons.
- Canonical page: https://noometry.com/models/glm-4-5v
- Last updated: 2026-10-10
- Title: GLM-4.5V Benchmarks, Price & Rank (October 2026) | Noometry

GLM-4.5V by Z.ai (Zhipu) ranks 158th of 354 ranked models on the Noometry Index as of October 2026, with a score of 39.8. Its strongest category is multimodal, where it ranks 92nd. API pricing starts at $0.60 per million input tokens and $1.80 per million output tokens, with a 64K-token context window.

Last verified October 10, 2026

## Specifications

- **Noometry rank:** #158 of 354
- **Index score:** 39.8
- **Evidence:** Confirmed 15 results
- **Provider:** [Z.ai (Zhipu)](https://noometry.com/providers/zai)
- **Released:** August 11, 2025
- **Weights:** Open weights
- **Reasoning:** Yes
- **Context window:** 64K
- **Max output:** 16K
- **Input price:** $0.60 / M
- **Output price:** $1.80 / M
- **Blended price:** $0.90 / M
- **Output speed:** 34 tokens/s [Kagi](https://help.kagi.com/kagi/ai/llm-benchmark.html)
- **Value:** #107 of 219
- **Knowledge cutoff:** April 2025
- **Input:** text, image, video
- **Hugging Face:** [zai-org/GLM-4.5V](https://huggingface.co/zai-org/GLM-4.5V)

## Category scores

Each category score combines every public result we have in that category.

GLM-4.5V category scores

1.  Coding 39.5
2.  Reasoning 27.4
3.  Math 37.4
4.  Knowledge 37.5
5.  Multimodal 34.3
6.  Multilingual 44.6
7.  Instruction Following 69.2
8.  Long Context 39.6
9.  Writing & Preference 52.5
10.  020406080

GLM-4.5V category ranks
| Category | Score | Rank | Results |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 39.5 | #155 | 1 |
| [Reasoning](https://noometry.com/best/reasoning) | 27.4 | #119 | 2 |
| [Math](https://noometry.com/best/math) | 37.4 | #159 | 1 |
| [Knowledge](https://noometry.com/best/knowledge) | 37.5 | #156 | 1 |
| [Multimodal](https://noometry.com/best/multimodal) | 34.3 | #92 | 1 |
| [Multilingual](https://noometry.com/best/multilingual) | 44.6 | #177 | 1 |
| [Instruction Following](https://noometry.com/best/instruction-following) | 69.2 | #175 | 1 |
| [Long Context](https://noometry.com/best/long-context) | 39.6 | #171 | 1 |
| [Writing & Preference](https://noometry.com/best/writing) | 52.5 | #170 | 3 |

## Strengths and weaknesses

Categories where GLM-4.5V places highest and lowest among the models ranked in each, with its score against that category's median.

### Strongest categories

GLM-4.5V: strongest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Reasoning](https://noometry.com/best/reasoning) | 27.4 | +3.8 | #119 of 350, top 34% |
| [Coding](https://noometry.com/best/coding) | 39.5 | +0.8 | #155 of 340, top 46% |
| [Math](https://noometry.com/best/math) | 37.4 | +0.8 | #159 of 327, top 49% |

### Weakest categories

GLM-4.5V: weakest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Multimodal](https://noometry.com/best/multimodal) | 34.3 | −4.3 | #92 of 128, top 72% |
| [Multilingual](https://noometry.com/best/multilingual) | 44.6 | −2.8 | #177 of 297, top 60% |
| [Long Context](https://noometry.com/best/long-context) | 39.6 | −1.3 | #171 of 296, top 58% |

## Closest competitors

The models ranked just above and below GLM-4.5V. When scores are this close, price and speed are often the better way to choose.

Models ranked closest to GLM-4.5V
| Model | Rank | Score | Blended $/M | Speed |  |
| --- | --- | --- | --- | --- | --- |
| [Llama 3.3 Nemotron 49b Super v1](https://noometry.com/models/llama-3-3-nemotron-49b-super-v1) | #154 | 40.1 | — | — | [Compare](https://noometry.com/compare/glm-4-5v-vs-llama-3-3-nemotron-49b-super-v1) |
| [Nemotron 3.5 Lightning](https://noometry.com/models/nemotron-3-5-lightning) | #155 | 40.0 | $0.0875 | — | [Compare](https://noometry.com/compare/glm-4-5v-vs-nemotron-3-5-lightning) |
| [Qwen3.7 Flash](https://noometry.com/models/qwen3-7-flash) | #156 | 39.9 | $0.055 | — | [Compare](https://noometry.com/compare/glm-4-5v-vs-qwen3-7-flash) |
| [Grok 3](https://noometry.com/models/grok-3) | #157 | 39.9 | — | 42 | [Compare](https://noometry.com/compare/glm-4-5v-vs-grok-3) |
| [QwQ-32B](https://noometry.com/models/qwq-32b) | #159 | 39.8 | — | — | [Compare](https://noometry.com/compare/glm-4-5v-vs-qwq-32b) |
| [Step 1o Turbo 202506](https://noometry.com/models/step-1o-turbo-202506) | #160 | 39.7 | — | — | [Compare](https://noometry.com/compare/glm-4-5v-vs-step-1o-turbo-202506) |
| [Nova 2 Lite](https://noometry.com/models/nova-2-lite) | #161 | 39.7 | $0.85 | — | [Compare](https://noometry.com/compare/glm-4-5v-vs-nova-2-lite) |
| [DeepSeek-V3.2-Speciale](https://noometry.com/models/deepseek-v3-2-speciale) | #162 | 39.7 | $0.85 | — | [Compare](https://noometry.com/compare/deepseek-v3-2-speciale-vs-glm-4-5v) |

Sponsored placements are available on pages like this one. [Advertise on Noometry](https://noometry.com/advertise)

## Benchmark results

Every published result we track, with its source. Bold rows are the ones used for ranking; where several exist we prefer independent runs over self-reported numbers.

### Coding

GLM-4.5V Coding benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Coding](https://noometry.com/benchmarks/arena-coding) | 1347 | #174 of 294, top 60% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Reasoning

GLM-4.5V Reasoning benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [Kagi LLM Benchmark](https://noometry.com/benchmarks/kagi-reasoning) | 59.8% | #42 of 99, top 43% |  | [Kagi LLM Benchmark](https://help.kagi.com/kagi/ai/llm-benchmark.html) |  |
| [LMArena Hard Prompts](https://noometry.com/benchmarks/arena-hard-prompts) | 1334 | #171 of 297, top 58% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Math

GLM-4.5V Math benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Math](https://noometry.com/benchmarks/arena-math) | 1354 | #163 of 285, top 58% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Knowledge

GLM-4.5V Knowledge benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Expert](https://noometry.com/benchmarks/arena-expert) | 1353 | #155 of 273, top 57% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Multimodal

GLM-4.5V Multimodal benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Vision](https://noometry.com/benchmarks/arena-vision) | 1154 | #98 of 122, top 81% |  | [LMArena](https://lmarena.ai/leaderboard/vision) | 2026-10-09 |

### Multilingual

GLM-4.5V Multilingual benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Non-English](https://noometry.com/benchmarks/arena-non-english) | 1303 | #177 of 297, top 60% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Chinese](https://noometry.com/benchmarks/arena-chinese) | 1337 | #174 of 285, top 62% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Russian](https://noometry.com/benchmarks/arena-russian) | 1298 | #177 of 283, top 63% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Spanish](https://noometry.com/benchmarks/arena-spanish) | 1336 | #152 of 226, top 68% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Instruction Following

GLM-4.5V Instruction Following benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Instruction Following](https://noometry.com/benchmarks/arena-instruction-following) | 1311 | #167 of 298, top 57% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Long Context

GLM-4.5V Long Context benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Longer Query](https://noometry.com/benchmarks/arena-longer-query) | 1304 | #185 of 291, top 64% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Writing & Preference

GLM-4.5V Writing & Preference benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Text](https://noometry.com/benchmarks/arena-text) | 1333 | #171 of 297, top 58% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Creative Writing](https://noometry.com/benchmarks/arena-creative-writing) | 1295 | #169 of 295, top 58% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Multi-Turn](https://noometry.com/benchmarks/arena-multi-turn) | 1332 | #171 of 295, top 58% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

## API pricing by provider

GLM-4.5V API prices
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
| --- | --- | --- | --- | --- |
| [openrouter](https://openrouter.ai/z-ai/glm-4.5v) | $0.60 | $1.80 | $0.11 | 2026-10-10 |
| [zai](https://docs.z.ai/guides/overview/pricing) | $0.60 | $1.80 | — | 2026-10-10 |

[All Z.ai (Zhipu) API prices →](https://noometry.com/llm-pricing/zai) [Estimate your cost →](https://noometry.com/tools/cost-calculator)

## Compare GLM-4.5V

-   [GLM-4.5V vs GLM-4.5](https://noometry.com/compare/glm-4-5-vs-glm-4-5v)
-   [GLM-4.5V vs Grok 3](https://noometry.com/compare/glm-4-5v-vs-grok-3)
-   [GLM-4.5V vs QwQ-32B](https://noometry.com/compare/glm-4-5v-vs-qwq-32b)
-   [GLM-4.5V vs Qwen3.7 Flash](https://noometry.com/compare/glm-4-5v-vs-qwen3-7-flash)
-   [GLM-4.5V vs Step 1o Turbo 202506](https://noometry.com/compare/glm-4-5v-vs-step-1o-turbo-202506)
-   [GLM-4.5V vs Nemotron 3.5 Lightning](https://noometry.com/compare/glm-4-5v-vs-nemotron-3-5-lightning)
-   [GLM-4.5V vs Nova 2 Lite](https://noometry.com/compare/glm-4-5v-vs-nova-2-lite)
-   [GLM-4.5V vs GPT-6 Astra](https://noometry.com/compare/glm-4-5v-vs-gpt-6-astra)
-   [GLM-4.5V vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-glm-4-5v)
-   [GLM-4.5V vs Gemini 3.8 Flash](https://noometry.com/compare/gemini-3-8-flash-vs-glm-4-5v)
-   [GLM-4.5V vs Kimi K3](https://noometry.com/compare/glm-4-5v-vs-kimi-k3)
-   [GLM-4.5V vs Grok 4.6](https://noometry.com/compare/glm-4-5v-vs-grok-4-6)
-   [GLM-4.5V vs Qwen3.8 Max](https://noometry.com/compare/glm-4-5v-vs-qwen3-8-max)
-   [GLM-4.5V vs Muse Spark 1.3](https://noometry.com/compare/glm-4-5v-vs-muse-spark-1-3)

## Other Z.ai (Zhipu) models

-   [GLM-5.3](https://noometry.com/models/glm-5-3)54.8
-   [GLM-5.3-Flash](https://noometry.com/models/glm-5-3-flash)51.8
-   [GLM-5.2](https://noometry.com/models/glm-5-2)51.1
-   [GLM-5.1](https://noometry.com/models/glm-5-1)47.8
-   [GLM-5](https://noometry.com/models/glm-5)46.1
-   [GLM-5V-Turbo](https://noometry.com/models/glm-5v-turbo)43.8
-   [GLM-4.5](https://noometry.com/models/glm-4-5)42.0
-   [GLM-4.7](https://noometry.com/models/glm-4-7)42.0

## Frequently asked questions

### How good is GLM-4.5V?

GLM-4.5V by Z.ai (Zhipu) ranks 158th of 354 ranked models on the Noometry Index as of October 2026, with a score of 39.8. Its strongest category is multimodal, where it ranks 92nd. API pricing starts at $0.60 per million input tokens and $1.80 per million output tokens, with a 64K-token context window.

### How much does GLM-4.5V cost?

GLM-4.5V costs $0.60 per million input tokens and $1.80 per million output tokens on Z.ai (Zhipu)'s own API.

### What is GLM-4.5V's context window?

GLM-4.5V accepts up to 64K tokens of input and can write up to 16K tokens in one response.

### Is GLM-4.5V open source?

Yes. GLM-4.5V's weights are downloadable from Hugging Face (zai-org/GLM-4.5V); check the license for commercial terms.

### How fast is GLM-4.5V?

GLM-4.5V generated about 34 output tokens per second in the Kagi LLM Benchmark's timed runs. Speed varies by provider, load and reasoning effort.

### What are GLM-4.5V's strengths and weaknesses?

Relative to other ranked models, GLM-4.5V places best in reasoning, coding, math and lowest in multimodal, multilingual, long context.

### What is GLM-4.5V best at?

Its best category is multimodal, where it ranks 92nd on Noometry.

### Cite this page

Noometry. (2026). GLM-4.5V benchmarks and pricing. Retrieved October 10, 2026, from https://noometry.com/models/glm-4-5v

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/models/glm-4-5v.md).