Z.ai · Open weights
GLM 5 Turbo
Fast GLM 5 Turbo variant from Z-AI for general chat, coding, and tool use.
- Tools
- Structured output
- Input
- Text
- 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)
- 557 tokens
- Longer than 52% of 465 models
Side by side
GLM 5 Turbo compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| GLM 5 TurboZ.aiThis model | Solar Pro 4upstageRemove | |
|---|---|---|
| Provider | Z.ai | upstage |
| Discovery tier | Open weights | Efficient |
| Added | Mar 15, 2026 | Aug 11, 2026 |
| Limits | ||
| Context window | 202.8K | 524.29KBest |
| Max output | 131.07K | 131.07K |
| Average output | 557 tokens | 546 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $1.20 | $0.03Best |
| Output | $4.00 | $0.12Best |
| Cache read | $0.24 | $0.006Best |
| Performance | ||
| Throughput | — | 101.4 tok/s |
| Time to first token | — | 3.1 s |
| Request success (24h) | 100.0%Best | 99.9% |
| Benchmark indexes | ||
| Intelligence Index | 26.6 | 26.6 |
| Capabilities | ||
| Tools | Yes | Yes |
| Structured output | Yes | Yes |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- GLM 5 Turbo
- Solar Pro 4
Intelligence Index
- GLM 5 Turbo26.6
- Solar Pro 426.6
GLM 5 Turbo: Better than 67% of 326 scored models
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- GLM 5 Turbo: —
- Solar Pro 4: 13.6%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- GLM 5 Turbo: —
- Solar Pro 4: 2.4%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- GLM 5 Turbo: —
- Solar Pro 4: 1,093 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- GLM 5 Turbo: —
- Solar Pro 4: 1,106 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- GLM 5 Turbo: —
- Solar Pro 4: 7.0%
AA-LCRv1.1
Reasoning across long documents
- GLM 5 Turbo: 71.7%Top
- Solar Pro 4: 70.7%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- GLM 5 Turbo: 27.8%
- Solar Pro 4: 29.8%Top
GPQA Diamond
Graduate-level science questions
- GLM 5 Turbo: 84.7%
- Solar Pro 4: 89.1%Top
IFBench
Following precise output instructions
- GLM 5 Turbo: 73.2%
- Solar Pro 4: —
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- GLM 5 Turbo: —
- Solar Pro 4: 0.0%
SciCode
Scientific computing in Python
- GLM 5 Turbo: —
- Solar Pro 4: 48.0%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- GLM 5 Turbo: 33.3%
- Solar Pro 4: —
τ²-Bench Telecom
Tool use in a customer-support simulation
- GLM 5 Turbo: 98.5%
- Solar Pro 4: —
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- GLM 5 Turbo: 71.7%Top
- Solar Pro 4: 70.7%
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
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.
- Prompt cache hits
- 31.9%
- About $0.89 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-5-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-5-turbo",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Z.ai
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