u/No-Concentrate-8909

Hi everyone,

I’m looking for some advice or experiences regarding a Walmart Seller account suspension and the subsequent appeal process.

Our account was suspended recently, and we submitted our appeal 13 days ago. Since then, we haven't received any response or update from the Trust & Safety team. We have a significant amount of funds currently held in the account, which is starting to impact our cash flow and operations.

We’ve heard that opening a new appeal can reset the clock or cause further delays, so we haven’t submitted a second one. However, the silence is concerning.

• Current Status: Under Review / Pending.
• Time since appeal: 13 days.
• Actions taken: Sent one follow-up message via the existing case log.

Has anyone dealt with a similar delay recently? Is 13+ days normal for Walmart right now, or should I be trying to reach out through other channels like LinkedIn or specific support emails? Also, does anyone know if there's a way to at least get a timeline for the fund release?

Any insights or tips on how to get a human to look at the case would be greatly appreciated.

Thanks in advance!

Walmart don't give me buybox in any of my listed items even if im the best option. why can this happen? usually, if there is a investigation for the account, it gets you out of the list for the item. im on the list, but Walmart doesn't give me the buybox even my metrics and other parameters are good.

Location:  Arkansas, USA (Walmart HQ)
Hi everyone,

I’m seeking legal guidance on how to handle a fund withholding issue with Walmart Marketplace. I am an international seller operating from Turkey.

Recently, our account was terminated. The only explanation provided was an email stating that we violated Section 5 of the Retailer Agreement (claims of "fraudulent, deceptive, or illegal activity"). They have placed a permanent hold on our entire balance—a significant five-figure amount—and explicitly stated that this decision is "not appealable."

We are a legitimate business and have not engaged in any illegal activity. This feels like an automated system error, but because they’ve labeled it "non-appealable," the standard support channels are closed to us.

The constraint: As a small business, we currently do not have the budget to hire a US-based attorney to represent us in arbitration or litigation. We need to handle this pro se (representing ourselves).

My questions:

1. Since the Retailer Agreement usually has an Arbitration Clause, is there a way to trigger a "Pre-Arbitration Notice of Dispute" or a formal Demand Letter on our own that actually gets a response from their legal/compliance team?
2. Would filing a complaint with the Arkansas Attorney General or the Better Business Bureau (BBB) be effective for an international seller in this specific "Section 5" scenario?
3. Does Walmart have a specific legal department email or address where a self-represented person can send evidence to dispute "non-appealable" fraud claims?

I am not looking for a lawyer here; I am looking for the correct legal steps an international seller can take independently to force a manual review of withheld funds.

Thank you for your time.

I’m a 3rd-year Computer Engineering student based in Istanbul, currently diving deep into the world of AI engineering. After spending a lot of time building AI-powered visual platforms and automation workflows, I’ve decided it’s time to move beyond being just an "API consumer" and start understanding the infrastructure under the hood.

I recently got my hands on a Lenovo ThinkCentre M70q Gen 4, and I'm planning to turn it into my personal AI lab.

The Rig:

• OS: Ubuntu 26.04 LTS
• CPU: 13th Gen Intel® Core™ i7-13700T (24 cores)
• RAM: 64.0 GiB (This is where I'm putting my hopes for larger models) (image_3612b3.jpg)
• Storage: 1.0 TB NVMe

The Learning Roadmap:

1. Local Inference: Setting up Ollama and llama.cpp to run Llama 3.1 (8B/70B) and Gemma 4. My goal is to see how far I can push the 64GB RAM with high-quantization models since I don't have a dedicated NVIDIA GPU.
2. RAG (Retrieval-Augmented Generation): Implementing a local RAG system using LangChain and ChromaDB. I want to feed it my own technical documentation and vintage tech collection reports to see how well a CPU-bound system handles vector embeddings.
3. Fine-Tuning Experiments: I know I'm in "CPU territory," but I'm planning to experiment with Intel IPEX-LLMfor LoRA/QLoRA fine-tuning on smaller models like Phi-3.5.

The Question for the Experts: Since I'm running on a high-spec Intel CPU without a dGPU:

• Are there any specific Intel-optimized libraries (other than OpenVINO or IPEX) you’d recommend for RAG performance?
• With 64GB of RAM, what’s the largest model you’ve realistically run on a CPU that still maintains a "usable" tokens-per-second rate for development?
• Any Ubuntu 26.04 specific tweaks I should be aware of for local LLM stability?

I'm excited to finally stop worrying about token costs and start breaking things locally! Any advice, warnings, or "I wish I knew this before" tips would be greatly appreciated.

I’m a 3rd-year Computer Engineering student based in Istanbul, currently diving deep into the world of AI engineering. After spending a lot of time building AI-powered visual platforms and automation workflows, I’ve decided it’s time to move beyond being just an "API consumer" and start understanding the infrastructure under the hood.

I recently got my hands on a Lenovo ThinkCentre M70q Gen 4, and I'm planning to turn it into my personal AI lab.

The Rig:

• OS: Ubuntu 26.04 LTS
• CPU: 13th Gen Intel® Core™ i7-13700T (24 cores)
• RAM: 64.0 GiB (This is where I'm putting my hopes for larger models) (image_3612b3.jpg)
• Storage: 1.0 TB NVMe

The Learning Roadmap:

1. Local Inference: Setting up Ollama and llama.cpp to run Llama 3.1 (8B/70B) and Gemma 4. My goal is to see how far I can push the 64GB RAM with high-quantization models since I don't have a dedicated NVIDIA GPU.
2. RAG (Retrieval-Augmented Generation): Implementing a local RAG system using LangChain and ChromaDB. I want to feed it my own technical documentation and vintage tech collection reports to see how well a CPU-bound system handles vector embeddings.
3. Fine-Tuning Experiments: I know I'm in "CPU territory," but I'm planning to experiment with Intel IPEX-LLMfor LoRA/QLoRA fine-tuning on smaller models like Phi-3.5.

The Question for the Experts: Since I'm running on a high-spec Intel CPU without a dGPU:

• Are there any specific Intel-optimized libraries (other than OpenVINO or IPEX) you’d recommend for RAG performance?
• With 64GB of RAM, what’s the largest model you’ve realistically run on a CPU that still maintains a "usable" tokens-per-second rate for development?
• Any Ubuntu 26.04 specific tweaks I should be aware of for local LLM stability?

I'm excited to finally stop worrying about token costs and start breaking things locally! Any advice, warnings, or "I wish I knew this before" tips would be greatly appreciated.

Hi everyone,

I’m looking for insights from sellers who have dealt with a specific, high-stakes suspension on Walmart Marketplace.

The Situation: Our account was recently flagged for "fraudulent, deceptive, or illegal activity" under Section 5 of the Retailer Agreement. The notice states that our balance is being permanently withheld and—crucially—that this decision is "not appealable."

The Context:

• We operate with full transparency and this came with zero prior warnings or policy violations.
• The withheld funds are substantial enough to impact our business operations significantly.

My Questions:

1. For those who received the "non-appealable" tag, did you manage to get a secondary manual review through disputeresolution@walmart.com or other internal channels?
2. Has anyone successfully used a "Demand Letter" or a formal legal notice to get the payments team to release funds?
3. I'm specifically looking for experiences from people who have navigated the Section 5 hurdle. Please no "reinstatement services" in the DMs—I'm looking for legitimate advice or legal precedents.

Thanks!