Llama-3.2-1B-Instruct

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 #25 in LLMs · score 116.9 method v1 Sources 4 Downloads 30d 3.7M · #40 of 619 tracked

Changed this week: 4 new quantized builds on the Hub (431 in all).2026-10-24

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?3.7Mdownloads, 30 days#40 of 619 we track · top 6%+34 likes, downloads −32% this week1,885 likesHugging Face2026-10-24

Worth reading

Picked by rule from 34 tracked pieces: the lab's own post, the most shared, a field report, the latest.

The lab's own post

Download Llama 3.2 1B, 3B, 11B, 90B

llama.com 2024-09-25 7 HN pts 42 words

Most discussed · 579 HN pts

Show HN: Llama 3.2 Interpretability with Sparse Autoencoders

The project trained a Sparse Autoencoder on 6.5 Billion activations from Llama 3.2-3B layer 23 over 10 epochs.

github.com 2024-11-21 579 HN pts · 99 comments 5.8k words about the Llama 3.2 family family

Latest · 4 months ago

Show HN: MinLlama – Llama 3.2 inference in ~100 lines of NumPy

A minimal implementation of Llama 3.2 Instruct inference runs in ~100 lines of pure Numpy code.

github.com 2026-06-23 2 HN pts 196 words about the Llama 3.2 family family

25 best of 34 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.

ArticleLlama 3.2: Revolutionizing edge AI and vision with open, customizable modelsai.meta.com · 2024-09-25 · 924 HN pts · official
ArticleLlama 3.2 released: Multimodal, 1B to 90B sizesllama.com · 2024-09-25 · 89 HN pts · official
ArticleI Self-Hosted Llama 3.2 with Coolify on My Home Servergeek.sg · 2024-10-16 · 221 HN pts
ArticleOllama 0.4 is released with support for Meta's Llama 3.2 Vision models locallyollama.com · 2024-11-06 · 182 HN pts
ArticleLlama can now see and run on your device – welcome Llama 3.2huggingface.co · 2024-09-25 · 26 HN pts
ArticleShow HN: Fine-tuned Llama 3.2 3B to match 70B models for local transcriptsbilawal.net · 2025-09-01
ArticleShow HN: Llama 3.2 3B and Keiro Research achieves 85% on SimpleQAkeirolabs.cloud · 2026-03-07
ArticleVerbatim AI – on-device transcription (Whisper) + summaries (Llama 3.2)apps.apple.com · 2026-04-21 · 2 HN pts
CodeLlama 3.2 Releasegithub.com · 2024-09-25 · 12 HN pts
ArticleLoad Llama-3.2 WebGPU in the browser from a local foldersimonwillison.net · 2025-09-09
ArticleRWKV-7 beats Llama 3.2 with 3x fewer training tokens and formally exceeds TC^0ai.gopubby.com · 2026-02-23
CodePydanticAI using Ollama (llama3.2) running locallygithub.com · 2024-12-06
CodeShow HN: Recall – open-source local file organizer using Llama 3.2 and Ollamagithub.com · 2025-12-10
CodeImplementing the Llama 3.2 1B and 3B Architectures from Scratchgithub.com · 2024-10-05
CodeShow HN: MLX.zig – Llama 3.2 in Ziggithub.com · 2025-03-14
ArticleOpen Source wireframe to app powered by Llama 3.2 Visionnapkins.dev · 2024-09-25
ArticleShow HN: Finetune Llama 3.2 Vision in a Colabcolab.research.google.com · 2024-11-21
DiscussionLlama 3.2: Lightweight models for edge devicestwitter.com · 2024-09-25
DiscussionLlama 3.2 1B and 3B on-device modelstwitter.com · 2024-09-25
ArticleRun Llama 3.2 3B on your phoneapps.apple.com · 2025-01-18
ArticleLLama3.2-vision as almost perfect OCR?demo.doctractor.com · 2024-11-18
ArticleMeta: Llama 3.2 1B Instruct - AI Model Details & Benchmarksbenchable.ai · undated

Show all 22

Where to run it

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

#	Cheapest 2	In /1M	Out /1M	Context	Quant	Seen
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 (431 quantized builds); a big base for builders (2,542 fine-tunes, adapters and merges).

As a service2Cloudflare, Featherless
On own hardware431quantized builds
Built on2,5421,844 fine-tunes · 683 adapters · 15 merges
In apps100+Hugging Face Spaces

Top Spaces running it: HuggingFaceH4/blogpost-scaling-test-time-compute ♥ 602 · allenai/reward-bench ♥ 438 · cvachet/pdf-chatbot ♥ 382 · baconnier/prompt-plus-plus ♥ 246

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.

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

The story so far

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

Most coverage came in the first two weeks

Teal is the weights (2024-09-18), amber triangles are 10 dated articles (each links to it).

What people built on it

2,973 derivatives on the Hub. Which build to run, by runtime: the most downloaded in each class.

2,973 derivatives on the Hub, most of them fine-tunes

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

GGUF MaziyarPanahi/Llama-3.2-1B-Instruct-GGUF for llama.cpp, Ollama, LM Studio 12.2M downloads FP8 RedHatAI/Llama-3.2-1B-Instruct-FP8-dynamic for vLLM, SGLang 13.9M downloads

All variants →

Reference

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

Use-case evidence

2 use cases

What it is good at 2 use cases

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

Llama-3.2-1B-Instruct has 1.24B parameters. (safetensors metadata, observed 2026-10-24)
Context length is 60,000 tokens (59K). (provider listing, observed 2026-10-24)
License: Llama 3.2 Community License (friction: attribution). As 3.1; EU multimodal restriction in the text. (license file, observed 2026-10-24)
Created 2024-09-18, last modified 2024-10-24. (HF API, observed 2026-10-24)
Access is gated on Hugging Face (manual). (HF API, observed 2026-10-24)

Pipeline tag	text-generation
Library	transformers
Architectures	LlamaForCausalLM
Model type	llama
Params by dtype	BF16: 1,235,814,400
Size band	S
MoE	no
Context length	60,000 (provider listing)
Gated	manual
Papers	arXiv:2204.05149, arXiv:2405.16406
License	Llama 3.2 Community License (llama3.2)
Hub snapshot	2026-10-25

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-Instruct: 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 2,973 derivatives on the Hub

quantized: 431finetune: 1,844adapter: 683merge: 15

Top variants (40 shown, ranked by downloads)

Variant	Relation	Quant	Params	Band	License	Author	Likes	Downloads
RedHatAI/Llama-3.2-1B-Instruct-FP8-dynamic	quantized	-FP8	1.50B	S	llama3.2	RedHatAI	4	13.9M
MaziyarPanahi/Llama-3.2-1B-Instruct-GGUF	quantized	GGUF	—	—	—	MaziyarPanahi	18	12.2M
hugging-quants/Llama-3.2-1B-Instruct-Q8_0-GGUF	quantized	Q8_0	—	—	—	hugging-quants	50	7.1M
RedHatAI/Llama-3.2-1B-Instruct-FP8	quantized	-FP8	1.50B	S	llama3.2	RedHatAI	4	6.7M
unsloth/Llama-3.2-1B-Instruct-GGUF	quantized	GGUF	—	—	llama3.2	unsloth	80	3M
bartowski/Llama-3.2-1B-Instruct-GGUF	quantized	GGUF	—	—	llama3.2	bartowski	184	2.9M
mlc-ai/Llama-3.2-1B-Instruct-q4f16_1-MLC	quantized	—	—	—	—	mlc-ai	7	2.4M
unsloth/Llama-3.2-1B-Instruct-unsloth-bnb-4bit	quantized	-bnb	1.26B	S	llama3.2	unsloth	4	1.5M
unsloth/Llama-3.2-1B-Instruct-bnb-4bit	quantized	-bnb	1.27B	S	llama3.2	unsloth	23	1.2M
hugging-quants/Llama-3.2-1B-Instruct-Q4_K_M-GGUF	quantized	GGUF	—	—	—	hugging-quants	36	1M
RedHatAI/Llama-3.2-1B-Instruct-quantized.w8a8	quantized	-quant	1.50B	S	llama3.2	RedHatAI	8	496.8k
lmstudio-community/Llama-3.2-1B-Instruct-GGUF	quantized	GGUF	—	—	llama3.2	lmstudio-community	49	291.6k
mlc-ai/Llama-3.2-1B-Instruct-q4f32_1-MLC	quantized	—	—	—	—	mlc-ai	1	281.1k
Skywork/Skywork-Reward-V2-Llama-3.2-1B	finetune	—	1.24B	S	llama3.2	Skywork	9	246.8k
SanctumAI/Llama-3.2-1B-Instruct-GGUF	quantized	GGUF	—	—	llama3.2	SanctumAI	3	183.7k
HKUSTAudio/Llasa-1B	finetune	—	1.37B	S	cc-by-nc-4.0	HKUSTAudio	103	156k
Vikhrmodels/Vikhr-Llama-3.2-1B-Instruct	finetune	—	1.24B	S	llama3.2	Vikhrmodels	46	135.1k
HKUSTAudio/Llasa-1B-Multilingual	finetune	—	1.77B	S	cc-by-nc-4.0	HKUSTAudio	44	97.4k
argilla/Llama-3.2-1B-Instruct-APIGen-FC-v0.1	finetune	—	1.24B	S	apache-2.0	argilla	1	93.5k
manycore-research/SpatialLM-Llama-1B	finetune	—	1.25B	S	llama3.2	manycore-research	1k	38k
cazzz307/Abliterated-Llama-3.2-1B-Instruct	finetune	—	1.24B	S	llama3.2	cazzz307	2	87k
inference-optimization/Llama-3.2-0.5B-Instruct	finetune	—	506M	S	mit	inference-optimization	1	82.6k
abaryan/CyberXP_Agent_Llama_3.2_1B	finetune	—	1.24B	S	mit	abaryan	3	80.9k
argilla-warehouse/Llama-3.2-1B-Instruct-v2-FC	finetune	—	1.24B	S	—	argilla-warehouse	0	73.5k
amd/Llama-3.2-1B-Instruct-FP8-KV	quantized	-FP8	1.24B	S	llama3.2	amd	1	67.3k
THGLab/Llama-3.2-1B-Instruct-LinkLlama-Cap50	finetune	—	1.24B	S	llama3.2	THGLab	0	55.4k
puettmann/LlaMaestra-3.2-1B-Translation	finetune	—	1.24B	S	llama3.2	puettmann	3	42k
NAM00/context_tuned_patient_matching_Llama-3.2-1B-Instruct	finetune	—	1.24B	S	llama3.2	NAM00	0	40.9k
mlc-ai/Llama-3.2-1B-Instruct-q4f16_0-MLC	quantized	—	—	—	—	mlc-ai	4	40.1k
onnx-community/Llama-3.2-1B-Instruct-ONNX	quantized	—	—	—	llama3.2	onnx-community	31	37.3k
uzlm/alloma-1B-Instruct	finetune	—	1.24B	S	llama3.2	uzlm	6	34.5k
prithivMLmods/Llama-SmolTalk-3.2-1B-Instruct	finetune	—	1.24B	S	creativeml-openrail-m	prithivMLmods	3	31.4k
ngxson/MiniThinky-v2-1B-Llama-3.2	quantized	—	1.24B	S	—	ngxson	43	26.8k
legraphista/Llama-3.2-1B-Instruct-IMat-GGUF	quantized	GGUF	—	—	llama3.2	legraphista	1	28.5k
NakJun/Llama-3.2-1B-Instruct-korQuAD-v1	finetune	—	1.24B	S	llama3.2	NakJun	8	28.1k
ContactDoctor/Bio-Medical-Llama-3-2-1B-CoT-012025	finetune	—	1.24B	S	other	ContactDoctor	38	19.5k
second-state/Llama-3.2-1B-Instruct-GGUF	quantized	GGUF	—	—	llama3.2	second-state	0	19.8k
FastFlowLM/Llama-3.2-1B-NPU2	finetune	—	—	—	llama3	FastFlowLM	1	18.1k
phamhai/Llama-3.2-1B-Instruct-Frog	finetune	—	1.24B	S	llama3.2	phamhai	5	17.9k
manycore-research/SpatialLM1.1-Llama-1B	finetune	—	1.35B	S	llama3.2	manycore-research	20	16k

Repository changelog

1 change

changed in the last 7 daysOther: 2026-10-24all changes

All providers

2 providers · 2 endpoints

Where to run 2 providers · 2 endpoints

Hosted endpoints observed for Llama-3.2-1B-Instruct, 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.

Provider	Model ref	Context	Quant	$/M in	$/M out	tok/s	TTFT	Tools	Status	Observed
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-Instruct	—	—	—	—	—	—	—	live	2026-10-25

Articles and coverage

34 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

Llama 3.2: Revolutionizing edge AI and vision with open, customizable models

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 3.2 released: Multimodal, 1B to 90B sizes

llama.com2024-09-25officialauthorityabout the Llama 3.2 familyHN 89 pts · 19 comments42 words

Download Llama 3.2 1B, 3B, 11B, 90B

llama.com2024-09-25officialauthorityHN 7 pts · 0 comments42 words

Analysis7

Show HN: Llama 3.2 Interpretability with Sparse Autoencoders

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

I Self-Hosted Llama 3.2 with Coolify on My Home Server

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.

Show HN: MinLlama – Llama 3.2 inference in ~100 lines of NumPy

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 0.4 is released with support for Meta's Llama 3.2 Vision models locally

ollama.com2024-11-06HN front pageabout the Llama 3.2 familyHN 182 pts · 25 comments202 words

Llama can now see and run on your device – welcome Llama 3.2

huggingface.co2024-09-25authorityabout the Llama 3.2 familyHN 26 pts · 1 comments3,434 words

Verbatim AI – on-device transcription (Whisper) + summaries (Llama 3.2)

apps.apple.com2026-04-21about the Llama 3.2 familyHN 2 pts · 1 comments

Llama 3.2 Release

github.com2024-09-25authorityabout the Llama 3.2 familyHN 12 pts · 0 comments

All coverage tracked for this model (34) — append-only, nothing is ever removed

Title	Source	Published	First seen	Signals
Meta: Llama 3.2 1B Instruct - AI Model Details & Benchmarks	benchable.ai	—	2026-10-07	exa
Llama-3.2-1B (Meta) Benchmarks, Context Window, Architecture & API Pricing (2026) \| TheModelverse \| TheModelverse	themodelverse.in	—	2026-10-07	exa
Llama 3.2 1B Instruct — Hardware Requirements & Compatibility \| llmrun	llmrun.dev	—	2026-10-07	exa
Llama 3.2 1B Instruct by meta-llama	llm.extractum.io	—	2026-10-07	exa
Llama-3.2-1B \| NVIDIA NeMo AutoModel	docs.nvidia.com	—	2026-10-07	exa
Meta: Llama 3.2 1B Instruct Review (2026) — Pricing, Speed & Verdict \| UseRightAI	userightai.com	—	2026-10-07	exa
Show HN: MinLlama – Llama 3.2 inference in ~100 lines of NumPy	github.com	2026-06-23	2026-10-07	hn
Verbatim AI – on-device transcription (Whisper) + summaries (Llama 3.2)	apps.apple.com	2026-04-21	2026-10-07	hn
Show HN: Llama 3.2 3B and Keiro Research achieves 85% on SimpleQA	keirolabs.cloud	2026-03-07	2026-10-07	hn
RWKV-7 beats Llama 3.2 with 3x fewer training tokens and formally exceeds TC^0	ai.gopubby.com	2026-02-23	2026-10-07	hn
Llama-3.2-1B-Instruct: A Compact, Multilingual and Efficient Open Language Model - Vanita.ai	vanitaai.com	2026-02-08	2026-10-07	exa
Show HN: Recall – open-source local file organizer using Llama 3.2 and Ollama	github.com	2025-12-10	2026-10-07	hn
Load Llama-3.2 WebGPU in the browser from a local folder	simonwillison.net	2025-09-09	2026-10-07	hn
Show HN: Fine-tuned Llama 3.2 3B to match 70B models for local transcripts	bilawal.net	2025-09-01	2026-10-07	hn
Meta: Llama 3.2 1B Instruct by Meta AI - AI Model Details \| LLMIndex \| LLMIndex	llmindex.net	2025-06-03	2026-10-07	exa
Show HN: MLX.zig – Llama 3.2 in Zig	github.com	2025-03-14	2026-10-07	hn
Run Llama 3.2 3B on your phone	apps.apple.com	2025-01-18	2026-10-07	hn
I built this robot and gave it a llama3.2 brain	twitter.com	2025-01-14	2026-10-07	hn
PydanticAI using Ollama (llama3.2) running locally	github.com	2024-12-06	2026-10-07	hn
Show HN: Llama 3.2 Interpretability with Sparse Autoencoders	github.com	2024-11-21	2026-10-07	hn
Show HN: Finetune Llama 3.2 Vision in a Colab	colab.research.google.com	2024-11-21	2026-10-07	hn
LLama3.2-vision as almost perfect OCR?	demo.doctractor.com	2024-11-18	2026-10-07	hn
Ollama 0.4 is released with support for Meta's Llama 3.2 Vision models locally	ollama.com	2024-11-06	2026-10-07	hn
I Self-Hosted Llama 3.2 with Coolify on My Home Server	geek.sg	2024-10-16	2026-10-07	hn
Implementing the Llama 3.2 1B and 3B Architectures from Scratch	github.com	2024-10-05	2026-10-07	hn
Llama can now see and run on your device – welcome Llama 3.2	huggingface.co	2024-09-25	2026-10-07	hn
Open Source wireframe to app powered by Llama 3.2 Vision	napkins.dev	2024-09-25	2026-10-07	hn
Llama 3.2 1B and 3B on-device models	twitter.com	2024-09-25	2026-10-07	hn
Llama 3.2: Lightweight models for edge devices	twitter.com	2024-09-25	2026-10-07	hn
Llama 3.2 Release	github.com	2024-09-25	2026-10-07	hn
Llama 3.2: Revolutionizing edge AI and vision with open, customizable models	ai.meta.com official	2024-09-25	2026-10-07	hn
Download Llama 3.2 1B, 3B, 11B, 90B	llama.com official	2024-09-25	2026-10-07	hn
Llama 3.2 released: Multimodal, 1B to 90B sizes	llama.com official	2024-09-25	2026-10-07	hn
Llama 3.2 1B Instruct – 128k context, open weights \| LLM Reference	llmreference.com	2024-09-25	2026-10-07	exa

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).

The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink cited in card

David Patterson, Joseph Gonzalez, Urs Hölzle +7 · 2022-04-11 · PDF · HF paper page (13 upvotes)
SpinQuant: LLM quantization with learned rotations cited in card

Zechun Liu, Changsheng Zhao, Igor Fedorov +6 · 2024-05-26 · PDF · HF paper page (3 upvotes)

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Sources

4 sources

Sources

Hub snapshot: 2026-10-25 · HF API: 2026-10-24 21:31 UTC · Providers: 2026-10-24 21:44 UTC · Articles: 2026-10-24 21:45 UTC · Summary: 2026-10-07 14:59 UTC · Last verified 2026-10-25

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