Workflows/Set up private desktop chat with LFM3-1.7B Uncensored
Text / WORKFLOW
Set up private desktop chat with LFM3-1.7B Uncensored
Chat privately with LFM3-1.7B Uncensored in your own browser. Download the exact AtomicChat GGUF, run llama.cpp on Windows, macOS, or Linux, and keep conversations on your computer without a cloud account.
Verified sourceSource checked 10/30/2026
LOCAL
Freshness unavailable. Date pending.—pendingFreshnessDate pendingDate pending
Popularity unavailable. Stats pending.—pendingPopularityStats pendingLikes unavailableRefresh due
What do these scores mean?+
Two ways to compare models. Neither score measures answer quality, benchmark performance, or whether a model fits your machine.
Freshness · release age
A new release starts at 100. The score halves every 180 days: 100 × 2^(−age in days / 180). When the release date is unavailable, a repository date is a fallback—not proof of when the model was released. Missing dates stay unscored.
Downloads over the past 30 days carry 80% of the score; lifetime likes carry 20%. Both use a logarithmic scale, capped at 10 million downloads and 100,000 likes. If likes are unavailable, downloads carry all the weight. Missing download statistics stay unscored.
Scores as of Oct 31, 2026. Statistics check pending. Statistics are marked for refresh after 72 hours. These statistics are due for a refresh.Full scoring method →
Before you begin
Hardware
Memory figures are conservative planning estimates for one text conversation at 4,096 context tokens, not measured speed or minimum requirements.
Machine
AD-Q4_K_M · 1.13 GB
AD-Q6_K · 1.59 GB
Windows or compatible Linux · CPU · 8 GB RAM
Recommended starting configuration; no GPU required.
More weight memory; leave room for the OS and context.
Apple Silicon Mac · 8 GB unified memory
Metal route; close other memory-heavy apps.
Metal route; more memory used by weights.
Intel Mac · 8 GB RAM
CPU mode (-ngl 0); speed depends on CPU.
CPU mode (-ngl 0); larger weight file.
CPU computer · 4 GB RAM
Constrained experiment; reduce context if needed. Prefer 8 GB.
Prefer Q4 or more RAM.
Allow at least 3 GB free disk for one model and the runtime, or 5 GB if keeping both packages. File size is not runtime RAM use.
Context window
Machine
Starting context
If memory is tight
All desktop routes · one chat slot
4,096 tokens with -c 4096 -np 1
Stop the server and retry with -c 2048.
The base model’s 256K maximum is not the default for this setup. Conversation history, instructions and the answer share the active context budget.
YOUR COMPUTER · YOUR PRIVATE CHATSOURCE-LINKED SETUP
Set up private desktop chat with LFM3-1.7B Uncensored
Choose Q4 or Q6, select your operating system, and open llama.cpp’s built-in chat in your browser. Downloads need internet access; conversations can then run offline.
Choose a package Run its commands Check the result
01
BEFORE YOU BEGIN
Choose your package
Select the weights you want. The instructions, downloads and settings change with your choice.
Save your machine in My Hardware to get an automatic starting choice. You can always choose any package yourself.
CURRENT SETUP
AD-Q4_K_M · community-modified weights
Planning estimates at 4K context: 8 GB total system/unified memory recommended. A 4 GB CPU system is a constrained experiment, not a tested minimum. Leave at least 3 GB free storage for one package and runtime; allow more if keeping both files.
Freshness unavailable. Date pending.—pendingFreshnessDate pendingDate pending
Popularity unavailable. Stats pending.—pendingPopularityStats pendingLikes unavailableRefresh due
What do these scores mean?+
Two ways to compare models. Neither score measures answer quality, benchmark performance, or whether a model fits your machine.
Freshness · release age
A new release starts at 100. The score halves every 180 days: 100 × 2^(−age in days / 180). When the release date is unavailable, a repository date is a fallback—not proof of when the model was released. Missing dates stay unscored.
Downloads over the past 30 days carry 80% of the score; lifetime likes carry 20%. Both use a logarithmic scale, capped at 10 million downloads and 100,000 likes. If likes are unavailable, downloads carry all the weight. Missing download statistics stay unscored.
Scores as of Oct 31, 2026. Statistics check pending. Statistics are marked for refresh after 72 hours. These statistics are due for a refresh.Full scoring method →
Choose where you want to run it. The instructions below update to match your selection.
CHOOSE YOUR SETUPWindows
CPU inference requires system RAM, not a dedicated GPU. GPU acceleration is optional.
01
Download and extract llama.cpp for Windows
Open Settings → System → About to check System type. Download the linked CPU x64 ZIP for an Intel/AMD Windows PC, or CPU ARM64 ZIP for Windows on ARM. Extract the entire archive into a new folder such as Documents/LocalChat/llama. Keep all DLLs beside llama-server.exe. In File Explorer open that extracted folder, right-click empty space and choose Open in Terminal; use a PowerShell tab. No Python, compiler, or dedicated GPU is required for this CPU route.
Download LFM3-1.7B-Uncensored-AD-Q4_K_M.gguf (1.13 GB) using the link below. Move the completed file into the extracted folder containing llama-server.exe. The next command assumes your terminal is in that same folder. Keep the original filename and wait for the download to finish. No Hugging Face account or API key is required for these public weights.
Run this command and leave the terminal open. Wait for the model to finish loading and the server to listen on port 8080. It uses one chat slot, a 4,096-token context, and a zero-token reasoning budget for direct everyday answers. Remove --reasoning-budget 0 if you prefer to allow thinking; answers may take longer. The 127.0.0.1 address makes the server accessible only on this computer. The GGUF supplies its chat template; do not substitute a template for another model.
Open http://127.0.0.1:8080 in your browser on the same computer. In the built-in chat interface, start a new conversation and send the sample prompt below. Read the answer, then ask “Make the second item more specific.” The follow-up should refer to the original list. You can use this chat for drafting, rewriting, summaries, and everyday questions; check important facts yourself.
Plain text
Suggest three ways to organize my weekly tasks. Keep each suggestion to one sentence.
05
Use it privately, then stop and restart
After downloading the runtime and weights, disconnect internet access and send a new prompt in the open chat page. The model should still respond. Keep web integrations and remote tools disabled; prompts are processed by this local server. Chat history can remain in the browser’s local storage, so use its delete/export controls and avoid shared browser profiles for private conversations. To stop the model, press Ctrl+C in the terminal. Next time, open the same folder in PowerShell, run the same launch command, and reopen http://127.0.0.1:8080. The local -m file path needs no model download.
03
SUCCESS CHECK · AD-Q4_K_M
Your private desktop chat is ready
The browser shows a coherent reply and a follow-up that uses the previous answer. A new message still generates with internet access disconnected. Stop with Ctrl+C; reopen the same model file to resume local chat.
LFM3 support merged into llama.cpp on October 27, 2026. The Windows/Linux download links pin b12017. Mac uses the current Homebrew package. Hardware sizing is estimated; no speed is promised. This guide covers CPU inference and Mac Metal, not dedicated Windows/Linux GPU configuration.
Use the linked b12017 release or a newer build with LFM3 support. On Mac run brew update and brew upgrade llama.cpp. Older package-manager versions may lack this architecture. Keep the new executable and all of its libraries together.
The terminal cannot find the executable or model
Open the extracted folder containing llama-server in Terminal or PowerShell. On Windows use .\llama-server.exe; on Linux use ./llama-server. Ensure the model filename matches the selected package exactly and has no added .txt or duplicate download suffix. On Mac finish Homebrew’s shell setup and open a new Terminal.
Linux reports missing libraries or GLIBC
The downloadable archive targets compatible Ubuntu systems. Use the linked official package-manager installation or build instructions for your distribution. Keep included shared libraries beside the executable. Do not copy only the executable.
The page will not open, or port 8080 is occupied
Wait for model loading to finish and keep the terminal running. If 8080 is occupied, stop this server, change --port 8080 to --port 8081 and open http://127.0.0.1:8081. Use HTTP, not HTTPS. Keep --host 127.0.0.1 for private access on this computer.
Loading is slow or memory runs out
Choose Q4, close memory-heavy applications, and reduce -c 4096 to -c 2048. On Mac, change -ngl 99 to -ngl 0 if Metal fails. The CPU path may be slower than GPU inference. Never treat download size as the complete RAM requirement.
Replies are repetitive or unrelated
Start a new conversation and use the embedded GGUF chat template. Keep sampling defaults initially. Try a shorter request and check the selected file. This 1.7B model has limited reasoning and factual reliability.
REFERENCE LIBRARY
Sources and files
Original instructions, model files, and compatibility notes behind this setup.