Z.ai (Zhipu), open weights
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.
Last verified
Specifications
- Noometry rank
- #158 of 354
- Index score
- 39.8
- Evidence
- Confirmed 15 results
- Provider
- Z.ai (Zhipu)
- 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
- Value
- #107 of 219
- Knowledge cutoff
- April 2025
- Input
- text, image, video
- Hugging Face
- zai-org/GLM-4.5V
Category scores
Each category score combines every public result we have in that category.
- Coding 39.5
- Reasoning 27.4
- Math 37.4
- Knowledge 37.5
- Multimodal 34.3
- Multilingual 44.6
- Instruction Following 69.2
- Long Context 39.6
- Writing & Preference 52.5
| Category | Score | Rank | Results |
|---|---|---|---|
| Coding | 39.5 | #155 | 1 |
| Reasoning | 27.4 | #119 | 2 |
| Math | 37.4 | #159 | 1 |
| Knowledge | 37.5 | #156 | 1 |
| Multimodal | 34.3 | #92 | 1 |
| Multilingual | 44.6 | #177 | 1 |
| Instruction Following | 69.2 | #175 | 1 |
| Long Context | 39.6 | #171 | 1 |
| Writing & Preference | 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
Weakest categories
| Category | Score | vs median | Rank |
|---|---|---|---|
| Multimodal | 34.3 | −4.3 | #92 of 128, top 72% |
| Multilingual | 44.6 | −2.8 | #177 of 297, top 60% |
| 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.
| Model | Rank | Score | Blended $/M | Speed | |
|---|---|---|---|---|---|
| Llama 3.3 Nemotron 49b Super v1 | #154 | 40.1 | — | — | Compare |
| Nemotron 3.5 Lightning | #155 | 40.0 | $0.0875 | — | Compare |
| Qwen3.7 Flash | #156 | 39.9 | $0.055 | — | Compare |
| Grok 3 | #157 | 39.9 | — | 42 | Compare |
| QwQ-32B | #159 | 39.8 | — | — | Compare |
| Step 1o Turbo 202506 | #160 | 39.7 | — | — | Compare |
| Nova 2 Lite | #161 | 39.7 | $0.85 | — | Compare |
| DeepSeek-V3.2-Speciale | #162 | 39.7 | $0.85 | — | Compare |
Sponsored placements are available on pages like this one. Advertise on Noometry
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
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Coding | 1347 | #174 of 294, top 60% | LMArena | 2026-10-08 |
Reasoning
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| Kagi LLM Benchmark | 59.8% | #42 of 99, top 43% | Kagi LLM Benchmark | ||
| LMArena Hard Prompts | 1334 | #171 of 297, top 58% | LMArena | 2026-10-08 |
Math
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Math | 1354 | #163 of 285, top 58% | LMArena | 2026-10-08 |
Knowledge
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Expert | 1353 | #155 of 273, top 57% | LMArena | 2026-10-08 |
Multimodal
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Vision | 1154 | #98 of 122, top 81% | LMArena | 2026-10-09 |
Multilingual
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Non-English | 1303 | #177 of 297, top 60% | LMArena | 2026-10-08 | |
| LMArena Chinese | 1337 | #174 of 285, top 62% | LMArena | 2026-10-08 | |
| LMArena Russian | 1298 | #177 of 283, top 63% | LMArena | 2026-10-08 | |
| LMArena Spanish | 1336 | #152 of 226, top 68% | LMArena | 2026-10-08 |
Instruction Following
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Instruction Following | 1311 | #167 of 298, top 57% | LMArena | 2026-10-08 |
Long Context
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Longer Query | 1304 | #185 of 291, top 64% | LMArena | 2026-10-08 |
Writing & Preference
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Text | 1333 | #171 of 297, top 58% | LMArena | 2026-10-08 | |
| LMArena Creative Writing | 1295 | #169 of 295, top 58% | LMArena | 2026-10-08 | |
| LMArena Multi-Turn | 1332 | #171 of 295, top 58% | LMArena | 2026-10-08 |
API pricing by provider
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
|---|---|---|---|---|
| openrouter | $0.60 | $1.80 | $0.11 | 2026-10-10 |
| zai | $0.60 | $1.80 | — | 2026-10-10 |
Compare GLM-4.5V
- GLM-4.5V vs GLM-4.5
- GLM-4.5V vs Grok 3
- GLM-4.5V vs QwQ-32B
- GLM-4.5V vs Qwen3.7 Flash
- GLM-4.5V vs Step 1o Turbo 202506
- GLM-4.5V vs Nemotron 3.5 Lightning
- GLM-4.5V vs Nova 2 Lite
- GLM-4.5V vs GPT-6 Astra
- GLM-4.5V vs Claude Fable 5.1
- GLM-4.5V vs Gemini 3.8 Flash
- GLM-4.5V vs Kimi K3
- GLM-4.5V vs Grok 4.6
- GLM-4.5V vs Qwen3.8 Max
- GLM-4.5V vs Muse Spark 1.3
Other Z.ai (Zhipu) models
- GLM-5.354.8
- GLM-5.3-Flash51.8
- GLM-5.251.1
- GLM-5.147.8
- GLM-546.1
- GLM-5V-Turbo43.8
- GLM-4.542.0
- GLM-4.742.0
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.