abliteration · Frontier
Abliterated Model Large
Abliteration.ai's unrestricted large text reasoning model is derived from GLM-5.2 and weight-modified to reduce refusals compared with the base model. It supports native tool calling, structured output, automatic prompt caching, and a one-million-token context window.
- Reasoning
- Tools
- Structured output
- Input
- Text
- Output
- Text
- Reasoning effort
- none · minimal · low · medium · high · xhigh · max
- Discovery tier
- Frontier
Pricing
USD per 1M tokens- Input
- $3.00
- Output
- $5.00
- Cache read
- $0.30
Reference prices as published by the model provider. API example
Specifications
- Context window
- 1M
- Max output
- 1M
- Average output (7 days)
- 467 tokens
- Longer than 47% of 473 models
Side by side
Abliterated Model Large compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Abliterated Model LargeabliterationThis model | Abliterated Large FlashabliterationRemove | |
|---|---|---|
| Provider | abliteration | abliteration |
| Discovery tier | Frontier | Efficient |
| Added | Aug 27, 2026 | Oct 23, 2026 |
| Limits | ||
| Context window | 1M | 1.05MBest |
| Max output | 999.99KBest | 262.14K |
| Average output | 467 tokens | 1.1K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $3.00 | $1.00Best |
| Output | $5.00 | $2.00Best |
| Cache read | $0.30 | $0.10Best |
| Performance | ||
| Throughput | 131.7 tok/s | 387.2 tok/sBest |
| Time to first token | 3.7 s | 3.1 sBest |
| Request success (24h) | 98.9% | 98.9% |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | No | Yes |
| Structured output | Yes | Yes |
| Parallel tools | No | Yes |
| Reasoning effort | none, minimal, low, medium, high, xhigh, max | none, minimal, low, medium, high, xhigh, max |
Public evaluations
Benchmarks
There are no public benchmark results for these models yet.
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
- 131.7 tok/s
- Faster than 70% of 256 models
- Time to first token
- 3.7 s
- Quicker than 43% of 256 models
- Prompt cache hits
- 97.3%
- About $0.37 per 1M input tokens with caching
- Request success (24h)
- 98.9%
- 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": "abliteration-ai/abliterated-model-large",
"reasoning_effort": "medium",
"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="abliteration-ai/abliterated-model-large",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)abliteration
Related models
Other abliteration models, starting with the same family.