abliteration · Efficient
Abliterated Large Flash
Abliterated Large Flash is an uncensored reasoning model based on DeepSeek V4.1-Flash-1017. It accepts text and images and returns text, with tool calling, JSON mode, JSON Schema output, and automatic prompt caching. Its shared input/output context is 1,048,576 tokens, with up to 262,144 output tokens when space permits. Reasoning defaults to high and can be turned off or set to low, high, or max. Supports up to four images across the request history.
- Reasoning
- Tools
- Vision
- Structured output
- Parallel tools
- Input
- Text, Images
- Output
- Text
- Reasoning effort
- none · minimal · low · medium · high · xhigh · max
- Discovery tier
- Efficient
Pricing
USD per 1M tokens- Input
- $1.00
- Output
- $2.00
- Cache read
- $0.10
Reference prices as published by the model provider. API example
Specifications
- Context window
- 1M
- Max output
- 262.1K
- Average output (7 days)
- 1.1K tokens
- Longer than 73% of 473 models
Side by side
Abliterated Large Flash compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Abliterated Large FlashabliterationThis model | Abliterated Model Large V2abliterationRemove | |
|---|---|---|
| Provider | abliteration | abliteration |
| Discovery tier | Efficient | Frontier |
| Added | Oct 23, 2026 | Aug 31, 2026 |
| Limits | ||
| Context window | 1.05M | 1.05M |
| Max output | 262.14K | 999.99KBest |
| Average output | 1.1K tokens | 844 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $1.00Best | $3.00 |
| Output | $2.00Best | $5.00 |
| Cache read | $0.10Best | $0.30 |
| Performance | ||
| Throughput | 329.9 tok/sBest | 181.4 tok/s |
| Time to first token | 3.0 s | 2.8 sBest |
| Request success (24h) | 98.9% | 99.6%Best |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | Yes | No |
| Structured output | Yes | Yes |
| Parallel tools | Yes | No |
| Reasoning effort | none, minimal, low, medium, high, xhigh, max | low, high, max |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Abliterated Large Flash
- Abliterated Model Large V2
| Leaderboard | Abliterated Large Flash | Abliterated Model Large V2 |
|---|---|---|
| Combined | Not in top 20 | #6 · 22.6% |
Ranks among Noumen catalog models on Combined leaderboards. Only top-20 placements are listed.
- Abliterated Large Flash
- Abliterated Model Large V2
| Leaderboard | Abliterated Large Flash | Abliterated Model Large V2 |
|---|---|---|
| Usage Share | Not in top 20 | #2 · 11.7% |
Ranks among Noumen catalog models on Usage leaderboards. Only top-20 placements are listed.
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
- 329.9 tok/s
- Faster than 93% of 260 models
- Time to first token
- 3.0 s
- Quicker than 54% of 260 models
- Prompt cache hits
- 96.2%
- About $0.13 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-flash",
"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-flash",
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.