Models › Llama family

Llama-Guard-3-8B

meta-llama Llama 3.1 Community License out 2 years ago

8.03B parameters, text in, text out. 1 provider serves it.

Verified 2026-10-25 Rank #213 in LLMs · score 88.4 method v1 Sources 3 Downloads 30d 27.8k · #432 of 619 tracked

Changed this week: 2 new quantized builds on the Hub (21 in all).2026-10-24

Can I run it?4.8GB at INT4Estimatefits a 16 GB cardmethod
Can I use it?Llama 3.1 Community License'Built with Llama' attribution; >700M MAU clauselicence file2026-10-24
Do people use it?27.8kdownloads, 30 days#432 of 619 we track · below the median+4 likes, downloads −12% this week343 likesHugging Face2026-10-24

Worth reading

Picked by rule from 23 tracked pieces: the lab's own post, the most shared, a field report, the latest.

Most discussed · 1,311 HN pts

Llama.cpp 30B runs with only 6GB of RAM now

llama.cpp introduces a new file format enabling memory mapping for model weights, resulting in loading speeds 10 to 100 times faster.

  • The new format merges multi-file models like LLaMA 13B into a single file to prevent C++ code from reshaping data during loading.
github.com 2023-03-31 1,311 HN pts · 414 comments 989 words about the Llama family family
Latest · 2 years ago

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

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 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.
ai.meta.com 2024-09-25 924 HN pts · 328 comments 2.5k words about the Llama family family

23 best of 23 tracked

The 2 picks above, plus these 21. Top is the radar's score: discussion, source authority and the lab's own posts, fading with age.

  1. ArticleCode Llama, a state-of-the-art large language model for codingai.meta.com · 2023-08-24 · 970 HN pts · official
  2. ArticleMeta Llama 3llama.meta.com · 2024-04-18 · 2,199 HN pts · official
  3. ArticleThe LLama Effect: Leak Sparked a Series of Open Source Alternatives to ChatGPTthesequence.substack.com · 2023-04-09 · 791 HN pts
  4. CodeLlama.cpp: Port of Facebook's LLaMA model in C/C++, with Apple Silicon supportgithub.com · 2023-03-10 · 989 HN pts
  5. CodeGpt4all: A chatbot trained on ~800k GPT-3.5-Turbo Generations based on LLaMagithub.com · 2023-03-28 · 593 HN pts
  6. CodeRun Llama 13B with a 6GB graphics cardgist.github.com · 2023-05-14
  7. CodeLlama2.c: Inference llama 2 in one file of pure Cgithub.com · 2023-07-23 · 707 HN pts
  8. CodeShow HN: I built a free in-browser Llama 3 chatbot powered by WebGPUgithub.com · 2024-05-03 · 547 HN pts
  9. DiscussionFine-tune your own Llama 2 to replace GPT-3.5/4news.ycombinator.com · 2023-09-12 · 955 HN pts
  10. DiscussionMeta AI releases Code Llama 70Btwitter.com · 2024-01-29
  11. ArticleRun Llama 2 uncensored locallyollama.ai · 2023-08-02
  12. ArticleLlama Guard 3 | Model Cards and Prompt formatsllama.com · undated · official
  13. ArticleLlama.ttf: A font which is also an LLMfuglede.github.io · 2024-06-23
  14. ArticleLlama Guard 1 vs 2 vs 3: Models and Taxonomiesaimoderationtools.com · 2026-05-09
  15. ArticleLlama Guard Benchmark Review: Production Limitsaimoderationtools.com · 2026-05-03
  16. ArticleSafety Evaluation on Llama-Guard 3-8B benchmark leaderboard · SOTA2 Researchsota2.com · undated
  17. ArticleLlama Guard 3 8B - AI Model Details & Benchmarksbenchable.ai · undated
  18. ArticleLlama Guard 3 8B By meta-llama: Benchmarks, Features and Detailed Analysis. Insights on Llama Guard 3 8B.llm-explorer.com · undated
  19. ArticleLlama Guard 3 8B — Specs, Pricing & GPU Requirements | InferenceBench | InferenceBenchinferencebench.io · undated
  20. ArticleSection 48.3: Output Guardrails: Llama Guard, NeMo Guardrails, ShieldGemma, Guardrails AIllmbook.icsgen-ai.org · undated
  21. ArticleLlama Guard 3 8B - Model Performance | Evalryevalry.com · 2026-01-28

Where to run it

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

#Cheapest live rowIn /1MOut /1MContextQuantSeen
1 Featherless — — — — Oct 25

All 1 provider →

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 1 API provider; 21 quantized builds for local use.

  • As a service1Featherless
  • On own hardware21quantized builds
  • Built on96 fine-tunes · 3 adapters · 0 merges
  • In apps32Hugging Face Spaces

Top Spaces running it: nvidia/Cosmos3-Action-Viewer ♥ 46 · whitecircle/circle-guard-bench ♥ 32 · tomg-group-umd/DynaGuard ♥ 13 · nbroad/HF-API-monitor ♥ 2

Will it fit?

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

Fits a 16 GB card at INT4

About 4.8 GB at INT4, 9.6 GB at FP8, 19 GB at BF16: weights only, so leave room for the KV cache.

16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 4.8 GB of weights (estimate; KV cache and activations extra)INT44.8 GBFP8: about 9.6 GB of weights (estimate; KV cache and activations extra)FP89.6 GBBF16: about 19 GB of weights (estimate; KV cache and activations extra)BF1619 GB
16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 4.8 GB of weights (estimate; KV cache and activations extra)INT44.8 GBFP8: about 9.6 GB of weights (estimate; KV cache and activations extra)FP89.6 GBBF16: about 19 GB of weights (estimate; KV cache and activations extra)BF1619 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.

Most coverage came in the first two weeks

Teal is the weights (2024-07-22), amber triangles are 10 dated articles (each links to it).

What people built on it

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

30 derivatives on the Hub, most of them quantized

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

21 quantized (Hugging Face model tree)6 fine-tunes (Hugging Face model tree)3 adapters (Hugging Face model tree)21 quantized6 fine-tunes3 adapters
21 quantized (Hugging Face model tree)6 fine-tunes (Hugging Face model tree)3 adapters (Hugging Face model tree)21 quantized6 fine-tunes3 adapters

All variants →

Reference

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

Use-case evidence

3 use cases

What it is good at 3 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

17 fields

Listed in LLMs

Facts

Pipeline tagtext-generation
Librarytransformers
ArchitecturesLlamaForCausalLM
Model typellama
Params by dtypeBF16: 8,030,261,248
Size bandM
MoEno
Gatedmanual
PapersarXiv:2407.21783, arXiv:2312.06674, arXiv:2204.05862, arXiv:2308.01263
LicenseLlama 3.1 Community License (llama3.1)
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-Guard-3-8B: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)19 GB · Single GPU (<24 GB)
FP8 (1 byte/param)9.6 GB · Single GPU (<24 GB)
INT4 (0.5 bytes/param)4.8 GB · Single GPU (<24 GB)

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

All variants

30 variants

Lineage

Fine-tuned from meta-llama/Llama-3.1-8B (same organization) Family: meta-llama/Llama 30 derivatives on the Hub

Base model: meta-llama/Llama-3.1-8B

quantized: 21finetune: 6adapter: 3

Top variants (30 shown, ranked by downloads)

Relation
Quant
30 rows
Variant Relation Quant Params Band License Author Likes Downloads
legraphista/Llama-Guard-3-8B-IMat-GGUF quantized GGUF — — llama3.1 legraphista 5 40.8k
eaddario/Llama-Guard-3-8B-GGUF quantized GGUF — — llama3.1 eaddario 0 20.4k
mradermacher/Llama-Guard-3-8B-i1-GGUF quantized GGUF — — llama3.1 mradermacher 5 18.2k
mradermacher/Llama-Guard-3-8B-GGUF quantized GGUF — — llama3.1 mradermacher 1 15k
VincentGOURBIN/Llama-Guard-3-8B finetune — 8.03B M llama3.1 VincentGOURBIN 0 5.1k
Rakancorle1/ThinkGuard finetune — 8.03B M llama3.1 Rakancorle1 4 3.7k
featherless-ai-quants/meta-llama-Llama-Guard-3-8B-GGUF quantized GGUF — — — featherless-ai-quants 0 2.6k
tensorblock/Llama-Guard-3-8B-GGUF quantized GGUF — — llama3.1 tensorblock 0 2.5k
DevQuasar-8/meta-llama.Llama-Guard-3-8B-GGUF quantized GGUF — — — DevQuasar-8 1 2.3k
MaziyarPanahi/Llama-Guard-3-8B-GGUF quantized GGUF — — — MaziyarPanahi 0 2.1k
Fabio2000/Llama-Guard-3-8B-Q4_K_M-GGUF quantized GGUF — — llama3.1 Fabio2000 0 384
itlwas/Llama-Guard-3-8B-Q4_K_M-GGUF quantized GGUF — — llama3.1 itlwas 0 364
ktoprakucar/Llama-Guard-3-8B-Q8-GPTQ quantized GPTQ — — llama3.1 ktoprakucar 1 283
lauraharyo/Llama-Guard-3-8B-Q4_K_M-GGUF quantized GGUF — — llama3.1 lauraharyo 0 332
venkatsriram/Llama-Guard-3-8B-Q4_K_M-GGUF quantized GGUF — — llama3.1 venkatsriram 1 272
thegenerativegeneration/Llama-Guard-3-8B-Q2_K-GGUF quantized Q2_K — — llama3.1 thegenerativegeneration 0 257
GuardwallAI/Llama-Guard-3-8B-Q4_K_M-GGUF quantized GGUF — — llama3.1 GuardwallAI 0 239
GuardwallAI/Llama-Guard-3-8B-Q8_0-GGUF quantized Q8_0 — — llama3.1 GuardwallAI 0 153
marcusnogueira/llama-guard-3-8b-awq-4bit quantized awq 8.03B M — marcusnogueira 0 141
marcusnogueira/llama-guard-3-8b-gptq-4bit quantized gptq 8.03B M — marcusnogueira 0 136
liao1111/CompanionGuard adapter — — — other liao1111 2 35
marcusnogueira/llama-guard-3-8b-gptq-8bit quantized gptq 8.03B M — marcusnogueira 0 134
tomalamb/Llama-Guard-3-8B-lora-r1-beavertails adapter — — — — tomalamb 0 49
Rakancorle1/laaj_15k_label_only adapter — — — llama3.1 Rakancorle1 0 22
jackysnake/sft_gr-llama_guard_3_8b finetune — 8.03B M other jackysnake 0 20
marcusnogueira/llama-guard-3-8b-llm-int8 quantized int8 8.03B M — marcusnogueira 0 18
marcusnogueira/llama-guard-3-8b-smoothquant-w8a8 quantized -w8a8 8.03B M — marcusnogueira 0 15
jodel/finetune-guard-3 finetune — — — other jodel 0 0
44m0n/llama-guard-3-sensitive-data-0-1 finetune — — — other 44m0n 0 0
saiteki-kai/QA-Llama-Guard-3-8B finetune — — — — saiteki-kai 0 0

Repository changelog

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

All providers

1 provider · 1 endpoint

Where to run 1 providers · 1 endpoints

Hosted endpoints observed for Llama-Guard-3-8B, sorted by input price (USD per million tokens). Each row names its observer and date; prices change daily, so check the source before quoting.

ProviderModel refContextQuant$/M in$/M outtok/sTTFTToolsStatusObserved
Featherless
hf
meta-llama/Llama-Guard-3-8B — — — — — — — live 2026-10-25

Articles and coverage

23 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.com2023-08-24officialauthorityHN front pageabout the Llama familyHN 970 pts · 501 comments1,460 words
Meta released Code Llama, a code-specialized large language model built on Llama 2 that is free for research and commercial use. The family includes four sizes with 7B, 13B, 34B, and 70B parameters, trained on 500B tokens of code data (1T for the 70B model) and supporting up to 100,000 tokens of context. Benchmark testing showed Code Llama 34B scored 53.7% on HumanEval and 56.2% on MBPP, outperforming other open-source solutions.written, reviewed, cited
  • Code Llama - Python is a language-specialized variation of Code Llama, further fine-tuned on 100B tokens of Python code.
ai.meta.com2024-09-25officialauthorityHN front pageabout the Llama 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.meta.com2024-04-18officialHN front pageabout the Llama familyHN 2,199 pts · 923 comments42 words

Analysis5

thesequence.substack.com2023-04-09authorityHN front pageabout the Llama familyHN 791 pts · 504 comments837 words
Meta released Llama in 7B, 13B, 33B, and 65B parameter versions, which were leaked on 4chan and subsequently fine-tuned by researchers into models like Vicuna that match GPT-4 performance. Stanford University released Alpaca, an instruction-following model based on the Llama 7B variant, while UC Berkeley, CMU, Stanford, and UC San Diego open-sourced Vicuna. Additional projects include Koala from Berkeley AI Research, ChatLLama from Nebuly, and ColossalChat from the Colossal-AI project, all leveraging the leaked base model to create open-source conversational agents.written, reviewed, cited
  • Open source LLM alternatives previously lacked the ability to follow human instructions compared to API models.
  • BloombergGPT is a 50 billion LLM fine tuned in financial data based on the BLOOM architecture.
  • The Segment Anything Model was released with the largest computer vision segmentation dataset ever, containing 1-Billion masks.
github.com2023-03-10authorityHN front pageabout the Llama familyHN 989 pts · 284 comments494 words
llama.cpp enables LLM and VLM inference in C/C++ with minimal setup across various hardware. It supports 1.5-bit, 2-bit, 3-bit, 4-bit, 5-bit, 6-bit, and 8-bit integer quantization for faster inference and reduced memory use. Apple silicon is a first-class citizen optimized via ARM NEON, Accelerate and Metal frameworks, while CPU+GPU hybrid inference partially accelerates models larger than the total VRAM capacity.written, reviewed, cited
github.com2023-03-28authorityHN front pageabout the Llama familyHN 593 pts · 301 comments466 words
github.com2023-07-23authorityHN front pageabout the Llama familyHN 707 pts · 165 comments4,774 words
The llama2.c repository offers a 700-line pure C file for training and inferring Llama 2 models, currently supporting fp32 inference for models up to 7B parameters. Work on model quantization is currently ongoing, but the project includes a 110M parameter model trained on the TinyStories dataset.written, reviewed, cited
  • Models larger than 7B are unusably slow because the repo performs float32 inference.
  • The 13B+ model variant fails due to integer flow errors in pointer arithmetic.
github.com2024-05-03authorityHN front pageabout the Llama familyHN 547 pts · 139 comments233 words
Secret-llama is an entirely-in-browser LLM chatbot powered by the webllm inference engine that runs fully private without needing a server. It supports models like Llama 3 and Mistral, ranging in size from 600MB to 4.3GB, requiring WebGPU support. Users can try it directly online, while developers compile the React code using yarn build-and-preview.written, reviewed, cited

Community2

github.com2023-03-31authorityHN front pageabout the Llama familyHN 1,311 pts · 414 comments989 words
llama.cpp introduces a new file format enabling memory mapping for model weights, resulting in loading speeds 10 to 100 times faster. This change allows safely loading models up to 2x larger, supports running many concurrent inference processes, and ensures tensors are aligned properly on a 32-byte boundary. Users who deleted old Meta LLaMA .pth files can use the migrate-ggml-2023-03-30-pr613.py script to convert old ggml files into the new mmap()'able format.written, reviewed, cited
  • The new format merges multi-file models like LLaMA 13B into a single file to prevent C++ code from reshaping data during loading.
news.ycombinator.com2023-09-12HN front pageabout the Llama familyHN 955 pts · 181 comments10,023 words
Fine-tuning open-source Llama 2 models can replace GPT-3.5 and GPT-4 for specific tasks, with a fine-tuned Llama 7B matching GPT-4 labels 95% of the time on a test set. While fine-tuning requires 1000+ examples and is less flexible than prompting, a fine-tuned Llama 7B is 50x cheaper than GPT-3.5 per token, costing just $19 to classify 2M recipes versus $23k for GPT-4.written, reviewed, cited
All coverage tracked for this model (23) — append-only, nothing is ever removed
TitleSourcePublishedFirst seenSignals
Llama Guard 3 | Model Cards and Prompt formatsllama.com official—2026-10-07exa
Safety Evaluation on Llama-Guard 3-8B benchmark leaderboard · SOTA2 Researchsota2.com—2026-10-07exa
Llama Guard 3 8B - AI Model Details & Benchmarksbenchable.ai—2026-10-07exa
Llama Guard 3 8B By meta-llama: Benchmarks, Features and Detailed Analysis. Insights on Llama Guard 3 8B.llm-explorer.com—2026-10-07exa
Llama Guard 3 8B — Specs, Pricing & GPU Requirements | InferenceBench | InferenceBenchinferencebench.io—2026-10-07exa
Section 48.3: Output Guardrails: Llama Guard, NeMo Guardrails, ShieldGemma, Guardrails AIllmbook.icsgen-ai.org—2026-10-07exa
Llama Guard 1 vs 2 vs 3: Models and Taxonomiesaimoderationtools.com2026-05-092026-10-07exa
Llama Guard Benchmark Review: Production Limitsaimoderationtools.com2026-05-032026-10-07exa
Llama Guard 3 8B - Model Performance | Evalryevalry.com2026-01-282026-10-07exa
Llama 3.2: Revolutionizing edge AI and vision with open, customizable modelsai.meta.com official2024-09-252026-10-07hn
Llama.ttf: A font which is also an LLMfuglede.github.io2024-06-232026-10-07hn
Show HN: I built a free in-browser Llama 3 chatbot powered by WebGPUgithub.com2024-05-032026-10-07hn
Meta Llama 3llama.meta.com official2024-04-182026-10-07hn
Meta AI releases Code Llama 70Btwitter.com2024-01-292026-10-07hn
Fine-tune your own Llama 2 to replace GPT-3.5/4news.ycombinator.com2023-09-122026-10-07hn
Code Llama, a state-of-the-art large language model for codingai.meta.com official2023-08-242026-10-07hn
Run Llama 2 uncensored locallyollama.ai2023-08-022026-10-07hn
Llama2.c: Inference llama 2 in one file of pure Cgithub.com2023-07-232026-10-07hn
Run Llama 13B with a 6GB graphics cardgist.github.com2023-05-142026-10-07hn
The LLama Effect: Leak Sparked a Series of Open Source Alternatives to ChatGPTthesequence.substack.com2023-04-092026-10-07hn
Llama.cpp 30B runs with only 6GB of RAM nowgithub.com2023-03-312026-10-07hn
Gpt4all: A chatbot trained on ~800k GPT-3.5-Turbo Generations based on LLaMagithub.com2023-03-282026-10-07hn
Llama.cpp: Port of Facebook's LLaMA model in C/C++, with Apple Silicon supportgithub.com2023-03-102026-10-07hn

Papers

4 papers

Papers 4

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

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Sources

3 sources

Sources

Hub snapshot: 2026-10-25 · HF API: 2026-10-24 21:35 UTC · Providers: 2026-10-24 21:44 UTC · Articles: 2026-10-24 21:45 UTC · Summary: 2026-10-07 15:03 UTC · Last verified 2026-10-25

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