Z.ai · Open weights
GLM 5V Turbo
Z.ai's native multimodal agent model for vision-based coding and agent workflows. This is the standard non-thinking variant for image, video, and text inputs, tuned for perceive-plan-execute loops, complex coding, and tool-driven task execution.
- Tools
- Vision
- Structured output
- Video input
- Input
- Text, Images, Video
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $1.20
- Output
- $4.00
- Cache read
- $0.24
Reference prices as published by the model provider. API example
Specifications
- Context window
- 202.8K
- Max output
- 131.1K
- Average output (7 days)
- 214 tokens
- Longer than 22% of 468 models
Side by side
GLM 5V Turbo compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| GLM 5V TurboZ.aiThis model | GLM 5 TurboZ.aiRemove | |
|---|---|---|
| Provider | Z.ai | Z.ai |
| Discovery tier | Open weights | Open weights |
| Added | Apr 1, 2026 | Mar 15, 2026 |
| Limits | ||
| Context window | 202.8K | 202.8K |
| Max output | 131.07K | 131.07K |
| Average output | 214 tokens | 557 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $1.20 | $1.20 |
| Output | $4.00 | $4.00 |
| Cache read | $0.24 | $0.24 |
| Performance | ||
| Throughput | 122.6 tok/s | — |
| Time to first token | 6.3 s | — |
| Request success (24h) | 100.0% | 100.0% |
| Benchmark indexes | ||
| Intelligence Index | — | 26.6 |
| Capabilities | ||
| Tools | Yes | Yes |
| Vision | Yes | No |
| Structured output | Yes | Yes |
| Video input | Yes | No |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- GLM 5V Turbo
- GLM 5 Turbo
Intelligence Index
- GLM 5V Turbo—
- GLM 5 Turbo26.6
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- GLM 5V Turbo: —
- GLM 5 Turbo: 71.7%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- GLM 5V Turbo: —
- GLM 5 Turbo: 27.8%
GPQA Diamond
Graduate-level science questions
- GLM 5V Turbo: —
- GLM 5 Turbo: 84.7%
IFBench
Following precise output instructions
- GLM 5V Turbo: —
- GLM 5 Turbo: 73.2%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- GLM 5V Turbo: —
- GLM 5 Turbo: 33.3%
τ²-Bench Telecom
Tool use in a customer-support simulation
- GLM 5V Turbo: —
- GLM 5 Turbo: 98.5%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- GLM 5V Turbo: —
- GLM 5 Turbo: 71.7%
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
- GLM 5V Turbo
- GLM 5 Turbo
| Leaderboard | GLM 5V Turbo | GLM 5 Turbo |
|---|---|---|
| Vision Style Control · Captioning | #16 · 1179.8 | Not in top 20 |
Ranks among Noumen catalog models on LMArena leaderboards. Only top-20 placements are listed.LMArena
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Throughput
- 122.6 tok/s
- Faster than 70% of 254 models
- Time to first token
- 6.3 s
- Quicker than 28% of 254 models
- Prompt cache hits
- 88.0%
- About $0.35 per 1M input tokens with caching
- Request success (24h)
- 100.0%
- Reliable
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
- Healthy (98% or more)
- Degraded (90–98%)
- Down (under 90%)
- No requests
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-5v-turbo",
"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-5v-turbo",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Z.ai
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