Models › Llama-3.2 family

meta-llama Llama 3.2 Community License out 2 years ago

1.24B parameters, text in, text out, 59K tokens of context. 2 providers serve it from $0.027 per million input tokens.

Verified 2026-10-25 Rank #67 in LLMs · score 104.5 method v1 Sources 3 Downloads 30d 545.4k · #160 of 619 tracked

Can I run it?0.7GB at INT4Estimatefits a 16 GB cardmethod
What does it cost?$0.027/1M incheapest of 1Cloudflare2026-10-24
Can I use it?Llama 3.2 Community LicenseAs 3.1; EU multimodal restriction in the textlicence file2026-10-24
Do people use it?545.4kdownloads, 30 days#160 of 619 we track · top 26%+19 likes, downloads −8% this week2,716 likesHugging Face2026-10-24

Worth reading

Picked by rule from 38 tracked pieces: the lab's own post, the most shared, a field report, the latest.

25 best of 38 tracked

The 3 picks above, plus these 22. Top is the radar's score: discussion, source authority and the lab's own posts, fading with age.

  1. ArticleLlama 3.2: Revolutionizing edge AI and vision with open, customizable modelsai.meta.com · 2024-09-25 · 924 HN pts · official
  2. ArticleLlama 3.2 released: Multimodal, 1B to 90B sizesllama.com · 2024-09-25 · 89 HN pts · official
  3. ArticleI Self-Hosted Llama 3.2 with Coolify on My Home Servergeek.sg · 2024-10-16 · 221 HN pts
  4. ArticleOllama 0.4 is released with support for Meta's Llama 3.2 Vision models locallyollama.com · 2024-11-06 · 182 HN pts
  5. ArticleLlama 3.2 Instruct 1B Intelligence, Performance & Price Analysisartificialanalysis.ai · undated
  6. ArticleLlama can now see and run on your device – welcome Llama 3.2huggingface.co · 2024-09-25 · 26 HN pts
  7. ArticleShow HN: Fine-tuned Llama 3.2 3B to match 70B models for local transcriptsbilawal.net · 2025-09-01
  8. ArticleShow HN: Llama 3.2 3B and Keiro Research achieves 85% on SimpleQAkeirolabs.cloud · 2026-03-07
  9. ArticleVerbatim AI – on-device transcription (Whisper) + summaries (Llama 3.2)apps.apple.com · 2026-04-21 · 2 HN pts
  10. CodeLlama 3.2 Releasegithub.com · 2024-09-25
  11. ArticleLoad Llama-3.2 WebGPU in the browser from a local foldersimonwillison.net · 2025-09-09
  12. ArticleRWKV-7 beats Llama 3.2 with 3x fewer training tokens and formally exceeds TC^0ai.gopubby.com · 2026-02-23
  13. CodePydanticAI using Ollama (llama3.2) running locallygithub.com · 2024-12-06
  14. CodeShow HN: Recall – open-source local file organizer using Llama 3.2 and Ollamagithub.com · 2025-12-10
  15. CodeImplementing the Llama 3.2 1B and 3B Architectures from Scratchgithub.com · 2024-10-05
  16. CodeShow HN: MLX.zig – Llama 3.2 in Ziggithub.com · 2025-03-14
  17. ArticleOpen Source wireframe to app powered by Llama 3.2 Visionnapkins.dev · 2024-09-25
  18. ArticleShow HN: Finetune Llama 3.2 Vision in a Colabcolab.research.google.com · 2024-11-21
  19. Discussion90T/s on my iPhone llama3.2-1B-fp16reddit.com · 2025-04-02
  20. DiscussionLlama 3.2: Lightweight models for edge devicestwitter.com · 2024-09-25
  21. DiscussionLlama 3.2 1B and 3B on-device modelstwitter.com · 2024-09-25
  22. ArticleRun Llama 3.2 3B on your phoneapps.apple.com · 2025-01-18

Where to run it

Live hosted endpoints, cheapest first, USD per million tokens. Ties break on output price, then provider name.

#Cheapest 2In /1MOut /1MContextQuantSeen
1 Cloudflare $0.027 $0.20 59K unknown Oct 24
2 Featherless — — — — Oct 25

All 2 providers →

Where it's used

Hugging Face does not say who downloads a model or with what. These are the proxies: API providers listing it, quantized builds, fine-tunes/adapters/merges, and Spaces that load it.

Served by 2 API providers; heavily run locally (263 quantized builds); a big base for builders (1,723 fine-tunes, adapters and merges).

  • As a service2Cloudflare, Featherless
  • On own hardware263quantized builds
  • Built on1,723944 fine-tunes · 753 adapters · 26 merges
  • In apps100+Hugging Face Spaces

Top Spaces running it: sesame/csm-1b ♥ 864 · OpenEvals/evaluation-guidebook ♥ 367 · HuggingFaceFW/finephrase ♥ 285 · lerobot/robot-folding ♥ 158

Will it fit?

Weights only, an estimate: leave room for the KV cache. Method

Fits a 16 GB card at INT4

About 0.7 GB at INT4, 1.5 GB at FP8, 3.0 GB at BF16: weights only, so leave room for the KV cache.

16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 0.7 GB of weights (estimate; KV cache and activations extra)INT40.7 GBFP8: about 1.5 GB of weights (estimate; KV cache and activations extra)FP81.5 GBBF16: about 3.0 GB of weights (estimate; KV cache and activations extra)BF163.0 GB
16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 0.7 GB of weights (estimate; KV cache and activations extra)INT40.7 GBFP8: about 1.5 GB of weights (estimate; KV cache and activations extra)FP81.5 GBBF16: about 3.0 GB of weights (estimate; KV cache and activations extra)BF163.0 GB

Estimate params × bytes per param × 1.2 · how we estimate

The story so far

Weights, every dated article, and repo commits on one rail.

9 dated articles and 0 repo commits so far

Teal is the weights (2024-09-18), amber triangles are 9 dated articles (each links to it).

What people built on it

1,986 derivatives on the Hub. Which build to run, by runtime: the most downloaded in each class.

1,986 derivatives on the Hub, led by 944 fine-tunes

From the Hugging Face model tree; quantized builds in teal, fine-tunes, merges and adapters in greys.

263 quantized (Hugging Face model tree)944 fine-tunes (Hugging Face model tree)26 merges (Hugging Face model tree)753 adapters (Hugging Face model tree)263 quantized944 fine-tunes26 merges753 adapters
263 quantized (Hugging Face model tree)944 fine-tunes (Hugging Face model tree)26 merges (Hugging Face model tree)753 adapters (Hugging Face model tree)263 quantized944 fine-tunes26 merges753 adapters

All variants →

Reference

Everything else, folded: the full tables, every source.

Use-case evidence

1 use case

What it is good at 1 use case

Labels are evidence, not verdicts: measured a third-party leaderboard row for this model; author-reported a number the model author published in the card or eval files; structural a deterministic signal from the name, config or chat template, or a decision-model estimate. Each chip links to its source. All use cases.

Facts

19 fields

Listed in LLMs

Facts

Pipeline tagtext-generation
Librarytransformers
ArchitecturesLlamaForCausalLM
Model typellama
Params by dtypeBF16: 1,235,814,400
Size bandS
MoEno
Context length60,000 (provider listing)
Gatedmanual
PapersarXiv:2204.05149, arXiv:2405.16406
LicenseLlama 3.2 Community License (llama3.2)
Hub snapshot2026-10-25

Servability

vLLM · SGLang

Servability

vLLM: supported · LlamaForCausalLM · 7050ef881ff0835f6890a47db1859a24c65481d6SGLang: supported · LlamaForCausalLM · 773cb938fe9484a8f7e7e46fb1b1fe96412c59ed

vLLM registry (7050ef881ff0835f6890a47db1859a24c65481d6) · SGLang registry (773cb938fe9484a8f7e7e46fb1b1fe96412c59ed) · Matched by architecture class name against each project's registry on main; 'supported' means the architecture is registered, not that this checkpoint was tested.

Hardware fit

3 estimates

Hardware fit ESTIMATE

Weights-only memory for Llama-3.2-1B: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)3.0 GB · Edge (<4 GB)
FP8 (1 byte/param)1.5 GB · Edge (<4 GB)
INT4 (0.5 bytes/param)0.7 GB · Edge (<4 GB)

Weights only (params × bytes/param × 1.2 overhead); KV cache and activations extra.

All variants

40 variants

Lineage

Original model Family: meta-llama/Llama-3.2 1,986 derivatives on the Hub

finetune: 944quantized: 263adapter: 753merge: 26

Top variants (40 shown, ranked by downloads)

Relation
Quant
Size
40 rows
Variant Relation Quant Params Band License Author Likes Downloads
unsloth/Llama-3.2-1B finetune — 1.24B S llama3.2 unsloth 66 2.4M
unsloth/Llama-3.2-1B-bnb-4bit quantized -bnb 1.27B S llama3.2 unsloth 18 678.7k
unsloth/Llama-3.2-1B-unsloth-bnb-4bit quantized -bnb 1.26B S llama3.2 unsloth 2 386.4k
RedHatAI/Llama-3.2-1B-FP8 quantized -FP8 1.50B S — RedHatAI 1 306.7k
HumeAI/tada-1b finetune — 2.16B M llama3.2 HumeAI 242 196k
osllmai-community/Llama-3.2-1B finetune — 1.24B S llama3.2 osllmai-community 0 195.6k
AdamLucek/Orpo-Llama-3.2-1B-15k finetune — 1.24B S mit AdamLucek 0 81.8k
ahczhg/Llama-3.2-1B-Aegis-SFT-DPO adapter — 1.24B S llama3.2 ahczhg 1 81k
ShahriarFerdoush/llama-3.2-1b-code-instruct finetune — 1.24B S apache-2.0 ShahriarFerdoush 0 78.4k
slseanwu/MIDI-LLM_Llama-3.2-1B finetune — 1.72B S llama3.2 slseanwu 39 49.4k
dphn/Dolphin3.0-Llama3.2-1B finetune — 1.24B S llama3.2 dphn 41 47.9k
facebook/layerskip-llama3.2-1B finetune — 1.24B S other facebook 32 39.2k
meta-llama/Llama-3.2-1B-Instruct-QLORA_INT4_EO8 finetune — — — llama3.2 meta-llama 49 28.1k
AliMaatouk/Llama-3.2-1B-Tele finetune — 1.24B S llama3.2 AliMaatouk 1 23.9k
torchtorchkimtorch/Llama-3.2-Korean-GGACHI-1B-Instruct-v1 finetune — 1.24B S — torchtorchkimtorch 8 15.9k
QuantFactory/Dolphin3.0-Llama3.2-1B-GGUF quantized GGUF — — llama3.2 QuantFactory 2 15.7k
prithivMLmods/Meta-Llama-3.2-1B-GGUF-QX quantized GGUF — — apache-2.0 prithivMLmods 2 11.7k
DevQuasar-3/meta-llama.Llama-3.2-1B-GGUF quantized GGUF — — llama3.2 DevQuasar-3 1 11k
MediaTek-Research/Llama-1B-TASTE-V0 quantized — 2.46B M apache-2.0 MediaTek-Research 14 9.9k
yash3056/Llama-3.2-1B-imdb finetune — 1.24B S llama3.2 yash3056 2 9.5k
meta-llama/Llama-3.2-1B-Instruct-SpinQuant_INT4_EO8 finetune — — — llama3.2 meta-llama 42 7.5k
prithivMLmods/Llama-3.2-1B-GGUF quantized GGUF — — creativeml-openrail-m prithivMLmods 2 8.6k
celestialcreator/Llama-3.2-1B-MTP-k8 finetune — — — llama3.2 celestialcreator 3 8.1k
artificialguybr/LLAMA-3.2-1B-OpenHermes2.5 finetune — 1.24B S llama3.2 artificialguybr 3 7.5k
SEOKDONG/llama3.2_1B_korean_v0.2_sft_by_aidx finetune — 1.24B S apache-2.0 SEOKDONG 3 7k
QuantFactory/HTML-Pruner-Llama-1B-GGUF quantized GGUF — — apache-2.0 QuantFactory 4 6.2k
hishab/titulm-llama-3.2-1b-v1.1 finetune — 1.24B S llama3.2 hishab 2 6.1k
zstanjj/HTML-Pruner-Llama-1B finetune — 1.24B S apache-2.0 zstanjj 15 5.3k
OctoThinker/OctoThinker-1B-Hybrid-Base finetune — 1.24B S llama3.2 OctoThinker 0 5.9k
Sheikhaei/llama-3.2-1b-english-persian-translator quantized GGUF 1.24B S apache-2.0 Sheikhaei 4 5.7k
NeuraLakeAi/iSA-02-Nano-Llama-3.2-1B finetune — — — apache-2.0 NeuraLakeAi 3 5.6k
BioTorch/UI_Llama_3_2_1B finetune — 1.24B S apache-2.0 BioTorch 1 5.5k
kmaurinjones/grammar-llama-3.2-1B quantized GGUF — — apache-2.0 kmaurinjones 3 5.1k
llm-jp/Llama-Mimi-1.3B finetune — 1.25B S llama3.2 llm-jp 11 4.6k
callgg/llama-3.2-1b-gguf quantized gguf — — llama3.2 callgg 0 4.7k
amd/Llama-3.2-1B-FP8-KV quantized -FP8 1.24B S llama3.2 amd 0 4.7k
dkp2701/conversation_summarizer_v1 quantized GGUF — — mit dkp2701 2 4.5k
pthinc/prettybird_bce_basic_simplesecurity quantized GGUF — — other pthinc 1 4.5k
skshmjn/Llama-3.2-1B-awq-4-bit quantized awq 1.24B S — skshmjn 0 4.5k
yueliu1999/GuardReasoner-1B finetune — 1.24B S other yueliu1999 7 4.1k

All providers

2 providers · 2 endpoints

Where to run 2 providers · 2 endpoints

Hosted endpoints observed for Llama-3.2-1B, sorted by input price (USD per million tokens). Each row names its observer and date; prices change daily, so check the source before quoting. Cheapest observed input price: $0.03/M.

ProviderModel refContextQuant$/M in$/M outtok/sTTFTToolsStatusObserved
Cloudflare
openrouter
meta-llama/llama-3.2-1b-instruct 59K unknown $0.03 $0.20 — — — live 2026-10-24
Featherless
hf
meta-llama/Llama-3.2-1B — — — — — — — live 2026-10-25

Articles and coverage

38 pieces

Ranked by source signals (HN, Lobsters, authority domains, official posts) and recency. Summaries are generated from a stored copy of the article text; every sentence cites a span of that text, and nothing is shown that failed the citation check.

Official3

ai.meta.com2024-09-25officialauthorityHN front pageabout the Llama 3.2 familyHN 924 pts · 328 comments2,460 words
Meta releases Llama 3.2, featuring small and medium-sized vision LLMs (11B and 90B) alongside lightweight text-only models (1B and 3B) designed for edge and mobile devices. The 11B and 90B models serve as drop-in replacements for their corresponding text model equivalents while the 1B and 3B models support a context length of 128K tokens and are enabled on day one for Qualcomm and MediaTek hardware. Both pre-trained and aligned vision models are available for fine-tuning using torchtune and local deployment via torchchat, with weights based on BFloat16 numerics.written, reviewed, cited
  • The 11B and 90B vision models require an entirely new model architecture that supports image reasoning.
  • Developers can keep all text-only capabilities intact because the adapter training intentionally did not update the language-model parameters.
  • The 1B and 3B models are created by using structured pruning in a single shot manner from the Llama 3.1 8B.
llama.com2024-09-25officialauthorityabout the Llama 3.2 familyHN 89 pts · 19 comments42 words
llama.com2024-09-25officialauthorityHN 7 pts · 0 comments42 words

Analysis7

github.com2024-11-21authorityHN front pageabout the Llama 3.2 familyHN 579 pts · 99 comments5,768 words
The project trained a Sparse Autoencoder on 6.5 Billion activations from Llama 3.2-3B layer 23 over 10 epochs. Data capture processed 25 million sentences totaling 4TB of raw activation data compressed to 3.2TB.generated, cited
geek.sg2024-10-16HN front pageabout the Llama 3.2 familyHN 221 pts · 90 comments2,289 words
A guide details self-hosting Llama 3.2 on a home server using Coolify and Ollama. The author achieved a 10x reduction in inference time by enabling GPU acceleration on an NVIDIA GeForce RTX 2060 using the CUDA toolkit and nvidia-container-toolkit. The setup involves installing Ubuntu 24, configuring Cloudflare Tunnels, and managing CUDA toolkits.written, reviewed, cited
  • Anyone with physical access can read your data if you avoid LVM or disk encryption for smoother reboots.
  • Cloudflare provides free SSL certificates only for wildcard domains at the top level, not on subdomains.
  • The Ollama service initially runs on the CPU until the NVIDIA Container Toolkit is installed and configured.
github.com2026-06-23authorityabout the Llama 3.2 familyHN 2 pts · 0 comments196 words
A minimal implementation of Llama 3.2 Instruct inference runs in ~100 lines of pure Numpy code. The project supports Python ≥ 3.10 and includes backends for PyTorch and Jax alongside the primary Numpy version. Ingredients in Llama 3.2 include RoPE with the Llama-3 frequency scaling, GQA, RMSNorm, SwiGLU MLP, and a shared unembedding / embedding matrix.written, reviewed, cited
ollama.com2024-11-06HN front pageabout the Llama 3.2 familyHN 182 pts · 25 comments202 words
artificialanalysis.aiauthorityabout the Llama 3.2 family740 words
huggingface.co2024-09-25authorityabout the Llama 3.2 familyHN 26 pts · 1 comments3,434 words
apps.apple.com2026-04-21about the Llama 3.2 familyHN 2 pts · 1 comments
All coverage tracked for this model (38) — append-only, nothing is ever removed
TitleSourcePublishedFirst seenSignals
Llama 3.2 Instruct 1B Intelligence, Performance & Price Analysisartificialanalysis.ai—2026-10-07exa
Llama 3.2: Specs, Benchmarks & Pricing | AI/TLDRai-tldr.dev—2026-10-07exa
Llama 3.2: A Deep Dive into Meta's Vision for Edge AIdeveloper.tenten.co—2026-10-07exa
How good is llama 3.2 REALLY? Ollama SLM & LLM Prompt ...youtube.com—2026-10-07exa
Meta: Llama 3.2 1B Instruct - AI Model Details & Benchmarksbenchable.ai—2026-10-07exa
Llama 3.2 Guide: How It Works, Use Cases & More - DataCampdatacamp.com—2026-10-07exa
Llama-3.2-1B (Meta) Benchmarks, Context Window, Architecture & API Pricing (2026) | TheModelverse | TheModelversethemodelverse.in—2026-10-07exa
Llama 3.2 Deep Dive - Tiny LM & NEW VLM Unleashed By Metayoutube.com—2026-10-07exa
Show HN: MinLlama – Llama 3.2 inference in ~100 lines of NumPygithub.com2026-06-232026-10-07hn
Verbatim AI – on-device transcription (Whisper) + summaries (Llama 3.2)apps.apple.com2026-04-212026-10-07hn
Show HN: Llama 3.2 3B and Keiro Research achieves 85% on SimpleQAkeirolabs.cloud2026-03-072026-10-07hn
RWKV-7 beats Llama 3.2 with 3x fewer training tokens and formally exceeds TC^0ai.gopubby.com2026-02-232026-10-07hn
Show HN: Recall – open-source local file organizer using Llama 3.2 and Ollamagithub.com2025-12-102026-10-07hn
Load Llama-3.2 WebGPU in the browser from a local foldersimonwillison.net2025-09-092026-10-07hn
Show HN: Fine-tuned Llama 3.2 3B to match 70B models for local transcriptsbilawal.net2025-09-012026-10-07hn
Llama 3.2 | meta-llama/llama-models | DeepWikideepwiki.com2025-07-302026-10-07exa
Exploring vocabulary alignment of neurons in Llama-3.2-1Bgrgv.xyz2025-06-082026-10-07hn
90T/s on my iPhone llama3.2-1B-fp16reddit.com2025-04-022026-10-07hn
Show HN: MLX.zig – Llama 3.2 in Ziggithub.com2025-03-142026-10-07hn
Run Llama 3.2 3B on your phoneapps.apple.com2025-01-182026-10-07hn
M5Stack LLM630 kit can run Llama3.2-1Bshop.m5stack.com2025-01-172026-10-07hn
I built this robot and gave it a llama3.2 braintwitter.com2025-01-142026-10-07hn
PydanticAI using Ollama (llama3.2) running locallygithub.com2024-12-062026-10-07hn
Show HN: Llama 3.2 Interpretability with Sparse Autoencodersgithub.com2024-11-212026-10-07hn
Show HN: Finetune Llama 3.2 Vision in a Colabcolab.research.google.com2024-11-212026-10-07hn
LLama3.2-vision as almost perfect OCR?demo.doctractor.com2024-11-182026-10-07hn
Ollama 0.4 is released with support for Meta's Llama 3.2 Vision models locallyollama.com2024-11-062026-10-07hn
I Self-Hosted Llama 3.2 with Coolify on My Home Servergeek.sg2024-10-162026-10-07hn
Implementing the Llama 3.2 1B and 3B Architectures from Scratchgithub.com2024-10-052026-10-07hn
Llama can now see and run on your device – welcome Llama 3.2huggingface.co2024-09-252026-10-07hn
Open Source wireframe to app powered by Llama 3.2 Visionnapkins.dev2024-09-252026-10-07hn
Llama 3.2 1B and 3B on-device modelstwitter.com2024-09-252026-10-07hn
Llama 3.2: Lightweight models for edge devicestwitter.com2024-09-252026-10-07hn
Llama 3.2 Releasegithub.com2024-09-252026-10-07hn
Llama 3.2: Revolutionizing edge AI and vision with open, customizable modelsai.meta.com official2024-09-252026-10-07hn
Download Llama 3.2 1B, 3B, 11B, 90Bllama.com official2024-09-252026-10-07hn
Llama 3.2 released: Multimodal, 1B to 90B sizesllama.com official2024-09-252026-10-07hn
Llama 3.2 1B — what it needs and what runs it · AITrackerbluetechgreen.com2024-09-252026-10-07exa

Papers

2 papers

Papers 2

arXiv links found in the model card and its tags. "Peer-reviewed" is shown only with evidence: a published venue in OpenAlex (measured) or the authors' own journal reference on arXiv (reported).

Similar models

3 models

Similar models

Sources

3 sources

Sources

Hub snapshot: 2026-10-25 · HF API: 2026-10-24 21:33 UTC · Providers: 2026-10-24 21:44 UTC · Articles: 2026-10-24 21:45 UTC · Summary: 2026-10-07 15:00 UTC · Last verified 2026-10-25

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