Z.ai · Open weights
GLM 4.5V
Multimodal GLM 4.5V that handles images alongside text while keeping the balanced reasoning strength of the GLM 4.5 family.
- Reasoning
- Vision
- Input
- Text, Images
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.60
- Output
- $1.80
Reference prices as published by the model provider. API example
Specifications
- Context window
- 65.5K
- Max output
- 16.4K
- Average output (7 days)
- 732 tokens
- Longer than 63% of 468 models
Side by side
GLM 4.5V compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| GLM 4.5VZ.aiThis model | GLM 5.3Z.aiRemove | |
|---|---|---|
| Provider | Z.ai | Z.ai |
| Discovery tier | Open weights | Open weights |
| Added | Nov 22, 2025 | Aug 14, 2026 |
| Limits | ||
| Context window | 65.54K | 1.05MBest |
| Max output | 16.38K | 131.07KBest |
| Average output | 732 tokens | 776 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.60 | $0.60 |
| Output | $1.80 | $1.10Best |
| Cache read | — | $0.20 |
| Performance | ||
| Throughput | — | 161.2 tok/s |
| Time to first token | — | 4.5 s |
| Request success (24h) | — | 99.8% |
| Benchmark indexes | ||
| Intelligence Index | 6.7 | 44.8Best |
| Coding Index | — | 74.8 |
| Math Index | 15.3 | — |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | No | Yes |
| Vision | Yes | No |
| Structured output | No | Yes |
| Reasoning effort | — | low, high, max |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- GLM 4.5V
- GLM 5.3
Intelligence Index
- GLM 4.5V6.7
- GLM 5.344.8
GLM 4.5V: Better than 6% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- GLM 4.5V: —
- GLM 5.3: 74.8
Math Index
Composite of the math evaluations
- GLM 4.5V: 15.3
- GLM 5.3: —
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- GLM 4.5V: —
- GLM 5.3: 62.2%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- GLM 4.5V: —
- GLM 5.3: 29.4%
Harvey LAB-AAv1.1
Legal tasks passed in full, with no material hallucination
- GLM 4.5V: —
- GLM 5.3: 0.3%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- GLM 4.5V: —
- GLM 5.3: 1,505 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- GLM 4.5V: —
- GLM 5.3: 1,649 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- GLM 4.5V: —
- GLM 5.3: 11.2%
AA-LCRv1.1
Reasoning across long documents
- GLM 4.5V: 0.0%
- GLM 5.3: 79.7%Top
MLCR-AA
Long-context reasoning over medical records
- GLM 4.5V: —
- GLM 5.3: 17.2%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- GLM 4.5V: 3.5%
- GLM 5.3: 42.3%Top
GPQA Diamond
Graduate-level science questions
- GLM 4.5V: 57.3%
- GLM 5.3: 91.7%Top
MMLU-Pro
Multi-subject knowledge and reasoning
- GLM 4.5V: 75.1%
- GLM 5.3: —
IFBench
Following precise output instructions
- GLM 4.5V: 28.6%
- GLM 5.3: —
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- GLM 4.5V: —
- GLM 5.3: 41.9%
SciCode
Scientific computing in Python
- GLM 4.5V: —
- GLM 5.3: 59.0%
LiveCodeBench
Recent competitive programming problems
- GLM 4.5V: 35.2%
- GLM 5.3: —
Math
AIME 2025
Competition mathematics, 2025 problems
- GLM 4.5V: 15.3%
- GLM 5.3: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- GLM 4.5V: 6.8%
- GLM 5.3: —
τ²-Bench Telecom
Tool use in a customer-support simulation
- GLM 4.5V: 19.6%
- GLM 5.3: —
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- GLM 4.5V: 0.0%
- GLM 5.3: 79.7%Top
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
- GLM 4.5V
- GLM 5.3
| Leaderboard | GLM 4.5V | GLM 5.3 |
|---|---|---|
| Combined | Not in top 20 | #19 · 5.7% |
Ranks among Noumen catalog models on Combined leaderboards. Only top-20 placements are listed.
- GLM 4.5V
- GLM 5.3
| Leaderboard | GLM 4.5V | GLM 5.3 |
|---|---|---|
| Roleplay | Not in top 20 | #13 · 28.6% |
| Creative writing | Not in top 20 | #9 · 37.0% |
Ranks among Noumen catalog models on Use cases leaderboards. Only top-20 placements are listed.
- GLM 4.5V
- GLM 5.3
| Leaderboard | GLM 4.5V | GLM 5.3 |
|---|---|---|
| Creative Writing v3 | Not in top 20 | #6 · 2077 |
| Longform Writing | Not in top 20 | #11 · 81.8 |
Ranks among Noumen catalog models on EQ-Bench leaderboards. Only top-20 placements are listed.EQ-Bench
- GLM 4.5V
- GLM 5.3
| Leaderboard | GLM 4.5V | GLM 5.3 |
|---|---|---|
| Mobile Apps | Not in top 20 | #17 · 1192 |
Ranks among Noumen catalog models on Design Arena leaderboards. Only top-20 placements are listed.Design Arena
- GLM 4.5V
- GLM 5.3
| Leaderboard | GLM 4.5V | GLM 5.3 |
|---|---|---|
| Usage Share | Not in top 20 | #6 · 5.6% |
Ranks among Noumen catalog models on Usage leaderboards. Only top-20 placements are listed.
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "z-ai/glm-4.5v",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="z-ai/glm-4.5v",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Z.ai
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