Z.ai (Zhipu), open weights

# GLM-4.6V

> GLM-4.6V by Z.ai (Zhipu), released December 2025. Ranked #137 of 354 with a Noometry Index of 41.3. API: $0.30 in / $0.90 out per M tokens. 128K context. Scores, sources and comparisons.
- Canonical page: https://noometry.com/models/glm-4-6v
- Last updated: 2026-10-10
- Title: GLM-4.6V Benchmarks, Price & Rank (October 2026) | Noometry

GLM-4.6V by Z.ai (Zhipu) ranks 137th of 354 ranked models on the Noometry Index as of October 2026, with a score of 41.3. Its strongest category is multimodal, where it ranks 90th. API pricing starts at $0.30 per million input tokens and $0.90 per million output tokens, with a 128K-token context window.

Last verified October 10, 2026

## Specifications

- **Noometry rank:** #137 of 354
- **Index score:** 41.3
- **Evidence:** Confirmed 12 results
- **Provider:** [Z.ai (Zhipu)](https://noometry.com/providers/zai)
- **Released:** December 8, 2025
- **Weights:** Open weights
- **Reasoning:** Yes
- **Context window:** 128K
- **Max output:** 33K
- **Input price:** $0.30 / M
- **Output price:** $0.90 / M
- **Blended price:** $0.45 / M
- **Output speed:** Not measured
- **Value:** #69 of 219
- **Knowledge cutoff:** April 2025
- **Input:** text, image, video
- **Hugging Face:** [zai-org/GLM-4.6V](https://huggingface.co/zai-org/GLM-4.6V)

## Category scores

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

GLM-4.6V category scores

1.  Coding 40.9
2.  Reasoning 27.6
3.  Knowledge 38.0
4.  Multimodal 34.8
5.  Multilingual 48.6
6.  Instruction Following 71.4
7.  Long Context 41.3
8.  Writing & Preference 56.6
9.  020406080

GLM-4.6V category ranks
| Category | Score | Rank | Results |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 40.9 | #128 | 1 |
| [Reasoning](https://noometry.com/best/reasoning) | 27.6 | #115 | 1 |
| [Knowledge](https://noometry.com/best/knowledge) | 38.0 | #149 | 1 |
| [Multimodal](https://noometry.com/best/multimodal) | 34.8 | #90 | 1 |
| [Multilingual](https://noometry.com/best/multilingual) | 48.6 | #141 | 1 |
| [Instruction Following](https://noometry.com/best/instruction-following) | 71.4 | #151 | 1 |
| [Long Context](https://noometry.com/best/long-context) | 41.3 | #143 | 1 |
| [Writing & Preference](https://noometry.com/best/writing) | 56.6 | #137 | 3 |

## Strengths and weaknesses

Categories where GLM-4.6V places highest and lowest among the models ranked in each, with its score against that category's median.

### Strongest categories

GLM-4.6V: strongest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Reasoning](https://noometry.com/best/reasoning) | 27.6 | +4.0 | #115 of 350, top 33% |
| [Coding](https://noometry.com/best/coding) | 40.9 | +2.2 | #128 of 340, top 38% |
| [Writing & Preference](https://noometry.com/best/writing) | 56.6 | +2.8 | #137 of 312, top 44% |

### Weakest categories

GLM-4.6V: weakest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Multimodal](https://noometry.com/best/multimodal) | 34.8 | −3.8 | #90 of 128, top 71% |
| [Instruction Following](https://noometry.com/best/instruction-following) | 71.4 | +0.1 | #151 of 305, top 50% |
| [Long Context](https://noometry.com/best/long-context) | 41.3 | +0.4 | #143 of 296, top 49% |

## Closest competitors

The models ranked just above and below GLM-4.6V. When scores are this close, price and speed are often the better way to choose.

Models ranked closest to GLM-4.6V
| Model | Rank | Score | Blended $/M | Speed |  |
| --- | --- | --- | --- | --- | --- |
| [Gemini 3.5 Flash Lite](https://noometry.com/models/gemini-3-5-flash-lite) | #133 | 41.5 | $0.85 | — | [Compare](https://noometry.com/compare/gemini-3-5-flash-lite-vs-glm-4-6v) |
| [Grok 4.1](https://noometry.com/models/grok-4-1) | #134 | 41.5 | — | — | [Compare](https://noometry.com/compare/glm-4-6v-vs-grok-4-1) |
| [GLM-4.6](https://noometry.com/models/glm-4-6) | #135 | 41.4 | $1 | 12 | [Compare](https://noometry.com/compare/glm-4-6-vs-glm-4-6v) |
| [Grok 4.1 Fast](https://noometry.com/models/grok-4-1-fast) | #136 | 41.4 | $0.28 | — | [Compare](https://noometry.com/compare/glm-4-6v-vs-grok-4-1-fast) |
| [MiMo-V2-Flash](https://noometry.com/models/mimo-v2-flash) | #138 | 41.3 | $0.18 | — | [Compare](https://noometry.com/compare/glm-4-6v-vs-mimo-v2-flash) |
| [Hunyuan Turbos 20250226](https://noometry.com/models/hunyuan-turbos) | #139 | 41.3 | — | — | [Compare](https://noometry.com/compare/glm-4-6v-vs-hunyuan-turbos) |
| [Kimi K2 (Jul 2025)](https://noometry.com/models/kimi-k2) | #140 | 41.2 | $1 | 201 | [Compare](https://noometry.com/compare/glm-4-6v-vs-kimi-k2) |
| [Grok-3 mini](https://noometry.com/models/grok-3-mini) | #141 | 41.2 | — | 10 | [Compare](https://noometry.com/compare/glm-4-6v-vs-grok-3-mini) |

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-4.6V Coding benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Coding](https://noometry.com/benchmarks/arena-coding) | 1390 | #143 of 294, top 49% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Reasoning

GLM-4.6V Reasoning benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Hard Prompts](https://noometry.com/benchmarks/arena-hard-prompts) | 1368 | #148 of 297, top 50% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Knowledge

GLM-4.6V Knowledge benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Expert](https://noometry.com/benchmarks/arena-expert) | 1371 | #141 of 273, top 52% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Multimodal

GLM-4.6V Multimodal benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Vision](https://noometry.com/benchmarks/arena-vision) | 1164 | #94 of 122, top 78% |  | [LMArena](https://lmarena.ai/leaderboard/vision) | 2026-10-09 |

### Multilingual

GLM-4.6V Multilingual benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Non-English](https://noometry.com/benchmarks/arena-non-english) | 1359 | #141 of 297, top 48% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Chinese](https://noometry.com/benchmarks/arena-chinese) | 1425 | #124 of 285, top 44% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Russian](https://noometry.com/benchmarks/arena-russian) | 1340 | #152 of 283, top 54% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Instruction Following

GLM-4.6V Instruction Following benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Instruction Following](https://noometry.com/benchmarks/arena-instruction-following) | 1352 | #145 of 298, top 49% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Long Context

GLM-4.6V Long Context benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Longer Query](https://noometry.com/benchmarks/arena-longer-query) | 1358 | #148 of 291, top 51% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Writing & Preference

GLM-4.6V Writing & Preference benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Text](https://noometry.com/benchmarks/arena-text) | 1377 | #140 of 297, top 48% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Creative Writing](https://noometry.com/benchmarks/arena-creative-writing) | 1347 | #131 of 295, top 45% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Multi-Turn](https://noometry.com/benchmarks/arena-multi-turn) | 1360 | #149 of 295, top 51% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

## API pricing by provider

GLM-4.6V API prices
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
| --- | --- | --- | --- | --- |
| [openrouter](https://openrouter.ai/z-ai/glm-4.6v) | $0.30 | $0.90 | $0.055 | 2026-10-10 |
| [zai](https://docs.z.ai/guides/overview/pricing) | $0.30 | $0.90 | — | 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-4.6V

-   [GLM-4.6V vs GLM-4.6](https://noometry.com/compare/glm-4-6-vs-glm-4-6v)
-   [GLM-4.6V vs Grok 4.1 Fast](https://noometry.com/compare/glm-4-6v-vs-grok-4-1-fast)
-   [GLM-4.6V vs MiMo-V2-Flash](https://noometry.com/compare/glm-4-6v-vs-mimo-v2-flash)
-   [GLM-4.6V vs Hunyuan Turbos 20250226](https://noometry.com/compare/glm-4-6v-vs-hunyuan-turbos)
-   [GLM-4.6V vs Grok 4.1](https://noometry.com/compare/glm-4-6v-vs-grok-4-1)
-   [GLM-4.6V vs Kimi K2 (Jul 2025)](https://noometry.com/compare/glm-4-6v-vs-kimi-k2)
-   [GLM-4.6V vs GPT-6 Astra](https://noometry.com/compare/glm-4-6v-vs-gpt-6-astra)
-   [GLM-4.6V vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-glm-4-6v)
-   [GLM-4.6V vs Gemini 3.8 Flash](https://noometry.com/compare/gemini-3-8-flash-vs-glm-4-6v)
-   [GLM-4.6V vs Kimi K3](https://noometry.com/compare/glm-4-6v-vs-kimi-k3)
-   [GLM-4.6V vs Grok 4.6](https://noometry.com/compare/glm-4-6v-vs-grok-4-6)
-   [GLM-4.6V vs Qwen3.8 Max](https://noometry.com/compare/glm-4-6v-vs-qwen3-8-max)
-   [GLM-4.6V vs Muse Spark 1.3](https://noometry.com/compare/glm-4-6v-vs-muse-spark-1-3)
-   [GLM-4.6V vs DeepSeek V4 Pro](https://noometry.com/compare/deepseek-v4-pro-vs-glm-4-6v)

## 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-4.6V?

GLM-4.6V by Z.ai (Zhipu) ranks 137th of 354 ranked models on the Noometry Index as of October 2026, with a score of 41.3. Its strongest category is multimodal, where it ranks 90th. API pricing starts at $0.30 per million input tokens and $0.90 per million output tokens, with a 128K-token context window.

### How much does GLM-4.6V cost?

GLM-4.6V costs $0.30 per million input tokens and $0.90 per million output tokens on Z.ai (Zhipu)'s own API.

### What is GLM-4.6V's context window?

GLM-4.6V accepts up to 128K tokens of input and can write up to 33K tokens in one response.

### Is GLM-4.6V open source?

Yes. GLM-4.6V's weights are downloadable from Hugging Face (zai-org/GLM-4.6V); check the license for commercial terms.

### What are GLM-4.6V's strengths and weaknesses?

Relative to other ranked models, GLM-4.6V places best in reasoning, coding, writing & preference and lowest in multimodal, instruction following, long context.

### What is GLM-4.6V best at?

Its best category is multimodal, where it ranks 90th on Noometry.

### Cite this page

Noometry. (2026). GLM-4.6V benchmarks and pricing. Retrieved October 10, 2026, from https://noometry.com/models/glm-4-6v

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/models/glm-4-6v.md).