Z.ai · Open weights
GLM 4.6 Original
GLM-4.6, Zhipu's flagship text model with 256K context window and advanced reasoning capabilities. Direct via Z-AI (Zhipu).
- Reasoning
- Tools
- Input
- Text
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.50
- Output
- $2.00
- Cache read
- $0.10
Reference prices as published by the model provider. API example
Specifications
- Context window
- 256K
- Max output
- 65.5K
- Average output (7 days)
- 1.3K tokens
- Longer than 81% of 468 models
Side by side
GLM 4.6 Original compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| GLM 4.6 OriginalZ.aiThis model | Qwen3.6 35B A3B TEEQwenRemove | |
|---|---|---|
| Provider | Z.ai | Qwen |
| Discovery tier | Open weights | Open weights |
| Added | Dec 11, 2025 | Jun 9, 2026 |
| Limits | ||
| Context window | 256K | 262.14KBest |
| Max output | 65.54K | 262.14KBest |
| Average output | 1.3K tokens | 3.9K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.50 | $0.20Best |
| Output | $2.00 | $1.27Best |
| Cache read | $0.10 | — |
| Performance | ||
| Request success (24h) | 99.4% | 99.5%Best |
| Benchmark indexes | ||
| Intelligence Index | 14.9 | 15.2Best |
| Coding Index | — | 28.1 |
| Math Index | 44.3 | — |
| Capabilities | ||
| Reasoning | Yes | No |
| Tools | Yes | No |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- GLM 4.6 Original
- Qwen3.6 35B A3B TEE
Intelligence Index
- GLM 4.6 Original14.9
- Qwen3.6 35B A3B TEE15.2
GLM 4.6 Original: Better than 37% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- GLM 4.6 Original: —
- Qwen3.6 35B A3B TEE: 28.1
Math Index
Composite of the math evaluations
- GLM 4.6 Original: 44.3
- Qwen3.6 35B A3B TEE: —
Agentic work
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- GLM 4.6 Original: —
- Qwen3.6 35B A3B TEE: 847 Elo
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- GLM 4.6 Original: 26.3%
- Qwen3.6 35B A3B TEE: 64.3%Top
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- GLM 4.6 Original: 5.5%
- Qwen3.6 35B A3B TEE: 13.9%Top
GPQA Diamond
Graduate-level science questions
- GLM 4.6 Original: 63.2%
- Qwen3.6 35B A3B TEE: 81.7%Top
MMLU-Pro
Multi-subject knowledge and reasoning
- GLM 4.6 Original: 78.4%
- Qwen3.6 35B A3B TEE: —
IFBench
Following precise output instructions
- GLM 4.6 Original: 36.7%Top
- Qwen3.6 35B A3B TEE: 36.2%
Coding
LiveCodeBench
Recent competitive programming problems
- GLM 4.6 Original: 56.1%
- Qwen3.6 35B A3B TEE: —
Math
AIME 2025
Competition mathematics, 2025 problems
- GLM 4.6 Original: 44.3%
- Qwen3.6 35B A3B TEE: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- GLM 4.6 Original: 28.8%Top
- Qwen3.6 35B A3B TEE: 25.8%
τ²-Bench Telecom
Tool use in a customer-support simulation
- GLM 4.6 Original: 76.9%
- Qwen3.6 35B A3B TEE: 85.1%Top
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- GLM 4.6 Original: 26.3%
- Qwen3.6 35B A3B TEE: 64.3%Top
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
- 24.4%
- About $0.40 per 1M input tokens with caching
- Request success (24h)
- 99.4%
- 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-4.6-original",
"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-4.6-original",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Z.ai
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