Z.ai · Open weights
GLM 5.3 Uncensored
An experimental uncensored version of the full GLM 5.3 reasoning model for chat, creative writing, coding, and tool use. It may show unusual behavior or inconsistent response quality.
- Reasoning
- Tools
- Input
- Text
- Output
- Text
- Reasoning effort
- low · high · max
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $1.25
- Output
- $2.25
- Cache read
- $0.30
Reference prices as published by the model provider. API example
Specifications
- Context window
- 1M
- Max output
- 131.1K
- Average output (7 days)
- 1.1K tokens
- Longer than 74% of 465 models
Side by side
GLM 5.3 Uncensored compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| GLM 5.3 UncensoredZ.aiThis model | GLM 5.3 FlashZ.aiRemove | |
|---|---|---|
| Provider | Z.ai | Z.ai |
| Discovery tier | Open weights | Open weights |
| Added | Sep 26, 2026 | Aug 26, 2026 |
| Limits | ||
| Context window | 1.05M | 1.05M |
| Max output | 131.07K | 131.07K |
| Average output | 1.1K tokens | 1.3K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $1.25 | $0.10Best |
| Output | $2.25 | $0.30Best |
| Cache read | $0.30 | $0.025Best |
| Performance | ||
| Throughput | 37.0 tok/s | 104.6 tok/sBest |
| Time to first token | 7.6 s | 4.0 sBest |
| Request success (24h) | 98.8% | 99.6%Best |
| Benchmark indexes | ||
| Intelligence Index | — | 41.8 |
| Coding Index | — | 71.5 |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | No | Yes |
| Structured output | No | Yes |
| Video input | No | Yes |
| Reasoning effort | low, high, max | low, high, max |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- GLM 5.3 Uncensored
- GLM 5.3 Flash
Intelligence Index
- GLM 5.3 Uncensored—
- GLM 5.3 Flash41.8
Indexes
Coding Index
Composite of the coding evaluations
- GLM 5.3 Uncensored: —
- GLM 5.3 Flash: 71.5
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- GLM 5.3 Uncensored: —
- GLM 5.3 Flash: 60.4%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- GLM 5.3 Uncensored: —
- GLM 5.3 Flash: 25.4%
Harvey LAB-AAv1.1
Legal tasks passed in full, with no material hallucination
- GLM 5.3 Uncensored: —
- GLM 5.3 Flash: 0.8%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- GLM 5.3 Uncensored: —
- GLM 5.3 Flash: 1,452 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- GLM 5.3 Uncensored: —
- GLM 5.3 Flash: 1,642 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- GLM 5.3 Uncensored: —
- GLM 5.3 Flash: 15.4%
AA-LCRv1.1
Reasoning across long documents
- GLM 5.3 Uncensored: —
- GLM 5.3 Flash: 80.0%
MLCR-AA
Long-context reasoning over medical records
- GLM 5.3 Uncensored: —
- GLM 5.3 Flash: 11.7%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- GLM 5.3 Uncensored: —
- GLM 5.3 Flash: 39.9%
GPQA Diamond
Graduate-level science questions
- GLM 5.3 Uncensored: —
- GLM 5.3 Flash: 91.2%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- GLM 5.3 Uncensored: —
- GLM 5.3 Flash: 32.8%
SciCode
Scientific computing in Python
- GLM 5.3 Uncensored: —
- GLM 5.3 Flash: 51.6%
Legacy evaluations
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- GLM 5.3 Uncensored: —
- GLM 5.3 Flash: 80.0%
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
- GLM 5.3 Uncensored
- GLM 5.3 Flash
| Leaderboard | GLM 5.3 Uncensored | GLM 5.3 Flash |
|---|---|---|
| Usage Share | #8 · 4.8% | Not in top 20 |
Ranks among Noumen catalog models on Usage leaderboards. Only top-20 placements are listed.
- GLM 5.3 Uncensored
- GLM 5.3 Flash
| Leaderboard | GLM 5.3 Uncensored | GLM 5.3 Flash |
|---|---|---|
| Roleplay | Not in top 20 | #20 · 14.9% |
| Creative writing | Not in top 20 | #16 · 19.8% |
| Math | Not in top 20 | #13 · 10.6% |
Ranks among Noumen catalog models on Use cases leaderboards. Only top-20 placements are listed.
- GLM 5.3 Uncensored
- GLM 5.3 Flash
| Leaderboard | GLM 5.3 Uncensored | GLM 5.3 Flash |
|---|---|---|
| Math | Not in top 20 | #13 · 1503.6 |
| Chinese | Not in top 20 | #15 · 1532.0 |
| Vision Style Control · Chinese | Not in top 20 | #12 · 1337.8 |
Ranks among Noumen catalog models on LMArena leaderboards. Only top-20 placements are listed.LMArena
- GLM 5.3 Uncensored
- GLM 5.3 Flash
| Leaderboard | GLM 5.3 Uncensored | GLM 5.3 Flash |
|---|---|---|
| Creative Writing v3 | Not in top 20 | #10 · 1974 |
| Longform Writing | Not in top 20 | #17 · 79.9 |
Ranks among Noumen catalog models on EQ-Bench leaderboards. Only top-20 placements are listed.EQ-Bench
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
- 37.0 tok/s
- Faster than 27% of 251 models
- Time to first token
- 7.6 s
- Quicker than 19% of 251 models
- Prompt cache hits
- 94.7%
- About $0.35 per 1M input tokens with caching
- Request success (24h)
- 98.8%
- 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-5.3-uncensored",
"reasoning_effort": "low",
"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-5.3-uncensored",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Z.ai
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