Q

Qwen3.8-27B-Kimiko-2

RP Chat

4.0(1)
Prose
—(0)
Intelligence
—(0)
Knowledge
—(0)
Instruction Following
—(0)
Coding
—(0)
Steerability
—(0)
Sign in to vote

Ratings reflect this model as run on Arli AI.

Qwen3.8-27B-Kimiko-2 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 Models

Hourly Usage

Token Usage

Input (24H)

259K

Output (24H)

5K

Input (7D)

2M

Output (7D)

28K

Performance Metrics

Typical Total Time

38.06s

Typical TTFT

2.69s

Typical Input TPS

2339.50

Typical Output TPS

7.45

Model Information

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

Use Qwen3.8-27B-Kimiko-2 with the Arli AI API

Qwen3.8-27B-Kimiko-2 is available through an OpenAI-compatible chat completions endpoint. Point any OpenAI SDK at https://api.arliai.com/v1, pass Qwen3.8-27B-Kimiko-2 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-Kimiko-2",
    "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-Kimiko-2",
    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.

Similar models

base_model:

  • Qwen/Qwen3.8-27B
  • TeichAI/Qwen3.8-27B-Fable-Distill
  • beyoru/Kiwen1.1-27B
  • nlpguy/Qwen3.8-27B-Fimi-4 library_name: transformers tags:
  • mergekit
  • merge

merged

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the Karcher Mean merge method.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

chat_template: qwen
dtype: bfloat16
merge_method: karcher
modules:
  default:
    slices:
    - sources:
      - layer_range: [0, 0]
        model: nlpguy/Qwen3.8-27B-Fimi-4
      - layer_range: [0, 0]
        model: beyoru/Kiwen1.1-27B
      - layer_range: [0, 0]
        model: Qwen/Qwen3.8-27B
      - layer_range: [0, 0]
        model: TeichAI/Qwen3.8-27B-Fable-Distill
  model.language_model.layers:
    slices:
    - sources:
      - layer_range: [0, 64]
        model: nlpguy/Qwen3.8-27B-Fimi-4
      - layer_range: [0, 64]
        model: beyoru/Kiwen1.1-27B
      - layer_range: [0, 64]
        model: Qwen/Qwen3.8-27B
      - layer_range: [0, 64]
        model: TeichAI/Qwen3.8-27B-Fable-Distill
  model.visual.blocks:
    slices:
    - sources:
      - layer_range: [0, 27]
        model: nlpguy/Qwen3.8-27B-Fimi-4
      - layer_range: [0, 27]
        model: beyoru/Kiwen1.1-27B
      - layer_range: [0, 27]
        model: Qwen/Qwen3.8-27B
      - layer_range: [0, 27]
        model: TeichAI/Qwen3.8-27B-Fable-Distill
out_dtype: bfloat16