RP Chat
Ratings reflect this model as run on Arli AI.
Qwen3.8-27B-Fimi-4 is a text generation model available on Arli AI. It offers 27B parameters, 262K token context, reasoning support, vision input. Recommended use: RP Chat. Run it through the OpenAI-compatible chat completions API with unlimited requests and zero-log privacy.
View on Hugging FaceBack to ModelsInput (24H)
1K
Output (24H)
0
Input (7D)
8K
Output (7D)
27K
Typical Total Time
24.75s
Typical TTFT
1.71s
Typical Input TPS
5595.51
Typical Output TPS
16.36
Context Size
262144
Quantization
r128 on INT8
Engine
vllm
Creation Method
Unknown
Model Class
Qwen3.8-27B - LoRA
Chat Template
Qwen3.5
Reasoning
Yes
Vision
Yes
Parameters
27B
Added At
9/28/2026
Qwen3.8-27B-Fimi-4 is available through an OpenAI-compatible chat completions endpoint. Point any OpenAI SDK at https://api.arliai.com/v1, pass Qwen3.8-27B-Fimi-4 as the model, and requests are served without logging.
cURL
curl https://api.arliai.com/v1/chat/completions \
-H "Authorization: Bearer $ARLIAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "Qwen3.8-27B-Fimi-4",
"messages": [{"role": "user", "content": "Hello!"}]
}'Python
from openai import OpenAI
client = OpenAI(
base_url="https://api.arliai.com/v1",
api_key="YOUR_ARLIAI_API_KEY",
)
response = client.chat.completions.create(
model="Qwen3.8-27B-Fimi-4",
messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)See the text generation docs for every parameter, or read the quick start guide to make your first request.
base_model:
This is a merge of pre-trained language models created using mergekit.
This model was merged using the Reinforced Agent Merging Plus (Tensor-Local) merge method using Qwen/Qwen3.5-27B as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
base_model: Qwen/Qwen3.5-27B
chat_template: qwen
dtype: bfloat16
merge_method: ramplus_tl
modules:
default:
slices:
- sources:
- layer_range: [0, 0]
model: Danielbrdz/Barcenas-Qwen3.8-27B-Fable
- layer_range: [0, 0]
model: allenai/tmax-27b
- layer_range: [0, 0]
model: migtissera/Tess-4-27B
- layer_range: [0, 0]
model: beyoru/Kiwen1.1-27B
- layer_range: [0, 0]
model: empero-ai/Qwythos-27B-v1
- layer_range: [0, 0]
model: bottlecapai/ThinkingCap-Qwen3.6-27B
- layer_range: [0, 0]
model: TeichAI/Qwen3.8-27B-Fable-Distill
- layer_range: [0, 0]
model: Qwen/Qwen3.5-27B
model.language_model.layers:
slices:
- sources:
- layer_range: [0, 64]
model: Danielbrdz/Barcenas-Qwen3.8-27B-Fable
- layer_range: [0, 64]
model: allenai/tmax-27b
- layer_range: [0, 64]
model: migtissera/Tess-4-27B
- layer_range: [0, 64]
model: beyoru/Kiwen1.1-27B
- layer_range: [0, 64]
model: empero-ai/Qwythos-27B-v1
- layer_range: [0, 64]
model: bottlecapai/ThinkingCap-Qwen3.6-27B
- layer_range: [0, 64]
model: TeichAI/Qwen3.8-27B-Fable-Distill
- layer_range: [0, 64]
model: Qwen/Qwen3.5-27B
model.visual.blocks:
slices:
- sources:
- layer_range: [0, 27]
model: Danielbrdz/Barcenas-Qwen3.8-27B-Fable
- layer_range: [0, 27]
model: allenai/tmax-27b
- layer_range: [0, 27]
model: migtissera/Tess-4-27B
- layer_range: [0, 27]
model: beyoru/Kiwen1.1-27B
- layer_range: [0, 27]
model: empero-ai/Qwythos-27B-v1
- layer_range: [0, 27]
model: bottlecapai/ThinkingCap-Qwen3.6-27B
- layer_range: [0, 27]
model: TeichAI/Qwen3.8-27B-Fable-Distill
- layer_range: [0, 27]
model: Qwen/Qwen3.5-27B
out_dtype: bfloat16
parameters:
r: 0.25