LOADING DATASHEET
LOADING DATASHEET
by Meta
RANKED #198 OF 313 ASSISTANTS · OVERALL #304 OF 493 RANKED · VIBE SCORE 5.8 · 133 VOICES ·
COPY BADGE pastes a README snippet with the rank SVG.
Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis. Its smaller size allows it to operate...
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26 weeks · 143 voices in this window
HONEYMOON FADING
Early praise is cooling off in recent weeks.
Open weights. You can use a hosted service, or download it and run it yourself, free.
Open weights: download Llama 3.2 1B Instruct once and it's yours. No subscription, no rate limits, works offline.
1.24B parameters, a Q4_K_M GGUF file is about 800 MB, while Q8/FP16 files are 1.3 GB to 2.5 GB
Raspberry Pi 5 (4GB RAM) or any basic Intel Core i3 PC
4 GB RAM
~$60 USEDQ4_K_M, CPU-only, ~18 tok/s, 8k context
Apple Mac mini M2 (8GB RAM)
8 GB UNIFIED MEMORY
~$450 USEDQ8_0 or FP16, fully in unified memory, ~75 tok/s, 32k context
NVIDIA GeForce RTX 3060 12GB Desktop GPU
12 GB VRAM
~$250 USEDFP16 full precision, max 128k context entirely in VRAM, ~140 tok/s
The three cards above are researched picks. Search the machine you actually have — we only say yes if it should reply at a usable speed, not just load the weights and crawl.
HARDWARE PICKS & PRICES ARE RESEARCHED FROM THE LIVE WEB AND REFRESHED AUTOMATICALLY. TREAT THEM AS BALLPARK, NOT GOSPEL.
Everyday jobs on each of those rigs: how long Llama 3.2 1B Instruct takes, and how good the crowd says it is at that kind of work.
| THE JOB | BARE MINIMUMRaspberry Pi 5 (4GB RAM) or any basic Intel Core i3 PC | SWEET SPOTApple Mac mini M2 (8GB RAM) | FULL POWERNVIDIA GeForce RTX 3060 12GB Desktop GPU |
|---|---|---|---|
| Write an emaila paragraph or two, drafted from a one-line brief | ~28 S | ~7 S | ~4 S |
| Summarize a documenta long report boiled down to the points that matter | ~83 S★★★★★ | ~20 S★★★★★ | ~11 S★★★★★ |
| Build a websitea small landing page, markup and styles together | ~7.4 MIN★★★★★ | ~1.8 MIN★★★★★ | ~57 S★★★★★ |
| Build a backendan API with routes, storage and tests | ~23 MIN★★★★★ | ~5.6 MIN★★★★★ | ~3 MIN★★★★★ |
| Build a gamea playable browser game in one file | ~14 MIN★★★★★ | ~3.3 MIN★★★★★ | ~1.8 MIN★★★★★ |
STARS ARE THE COMMUNITY SCORE FOR THAT KIND OF WORK, DOCKED FOR HOW SQUASHED THE WEIGHTS GET AT EACH TIER. TIMES ARE COMPUTED FROM RESEARCHED SPEEDS. BALLPARK, NOT GOSPEL.
Not enough discussion about Llama 3.2 1B Instruct yet to call it. We found 135 posts but people did not say much either way.
133 POSTS · 2 COMMENTS · HACKER NEWS · GITHUB · REDDIT · X
Other models the crowd has fully reviewed, starting with text models like this one.
Guide on how to rip JanitorAI character definitions for upload to SillyTavern
We trained SLM-powered assistants for personal expenses summaries that you can run locally via Ollama.
[P] Llama 3.2 1B-Based Conversational Assistant Fully On-Device (No Cloud, Works Offline)
Fine-tuned Llama 3.2 1B on 480 examples, shipped to Android via Q4_K_M
We built a 1 and 3B local Git agents that turns plain English into correct git commands. They matche GPT-OSS 120B accuracy (gitara)
Do you think you can find the password ? I made a small LLM challenge
How to load finetuned LLM to ollama??
JSON and Pandas RAG using LlamaIndex
Fine-tuned Llama 3.2 1B for Indian Legal QA on a free Google Colab T4 (0.90% Trainable Params
How to load a fine tuned Model to Ollama? (Nothing is working)
Difference in Llama 3.2 1B instruct and Llama 3.1 8B
How to load a Finetuned LLM to Ollama?