Models › Llama-3.1 family

Meta-Llama-3.1-8B-Instruct

unsloth Llama 3.1 Community License out 2 years ago

8.03B parameters, text in, text out, 128K tokens of context. 1 provider serves it.

Verified 2026-10-26 07:27 UTC Rank #530 in LLMs · score 75.5 method v1 Sources 3 Downloads 30d 188k · #253 of 619 tracked

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 file2026-10-26
Do people use it?188kdownloads, 30 days#253 of 619 we track · top 41%+0 likes, downloads −2% this week99 likesHugging Face2026-10-26

Worth reading

Picked by rule from 25 tracked pieces: the lab's own post, the most shared, a field report, the latest.

Most discussed · 437 HN pts
llama.meta.com 2024-07-23 437 HN pts · 269 comments 42 words about the Llama 3.1 family family

25 best of 25 tracked

The 2 picks above, plus these 23. Top is the radar's score: discussion, source authority and the lab's own posts, fading with age.

  1. CodeShow HN: Llama 3.1 70B on a single RTX 3090 via NVMe-to-GPU bypassing the CPUgithub.com · 2026-02-21
  2. Codeg1: Using Llama-3.1 70B on Groq to create o1-like reasoning chainsgithub.com · 2024-09-15
  3. ArticleLlama 3.1 405B now runs at 969 tokens/s on Cerebras Inferencecerebras.ai · 2024-11-19
  4. CodeLlama 3.1 Omni Modelgithub.com · 2024-09-18
  5. CodeShow HN: Tune LLaMa3.1 on Google Cloud TPUsgithub.com · 2024-09-11 · 189 HN pts
  6. CodeLlama 3.1 in Cgithub.com · 2024-07-24 · 212 HN pts
  7. CodeLongwriter – Increase llama3.1 output to 10k wordsgithub.com · 2024-10-07 · 154 HN pts
  8. ArticleHermes 3: The First Fine-Tuned Llama 3.1 405B Modellambdalabs.com · 2024-08-15
  9. DiscussionCerebras launches inference for Llama 3.1; benchmarked at 1846 tokens/s on 8Btwitter.com · 2024-08-27 · 95 HN pts
  10. ArticleLlama 3.1: Our most capable models to dateai.meta.com · 2024-07-23 · 27 HN pts
  11. ArticleWhy Llama 3.1 is Importanttimkellogg.me · 2024-07-23 · 56 HN pts
  12. ArticleNvidia presents Llama-Mesh: Generating 3D Mesh with Llama 3.1 8Bresearch.nvidia.com · 2024-11-17 · 20 HN pts
  13. ArticleMeta Llama 3.1 405Bopenrouter.ai · 2024-07-23
  14. ArticleCoding with Llama 3.1, New DeepSeek Coder and Mistral Largeaider.chat · 2024-07-25 · 32 HN pts
  15. ArticleLlama-3.1 supports tool calls via promptingbraintrust.dev · 2024-07-26
  16. ArticleMeta releases an open-weights GPT-4-level AI model, Llama 3.1 405Barstechnica.com · 2024-07-23
  17. ArticleShow HN: Run Llama 3.1 8B in the browserapp.wiz.chat · 2024-07-28
  18. VideoRunning the latest Llama 3.1 8B on Raspberry Pi [video]youtube.com · 2024-07-30
  19. ArticleShow HN: Finetune Llama-3.1 2x faster in a Colabcolab.research.google.com · 2024-07-23
  20. ArticleBenchmarking Llama 3.1 405B on 8x AMD MI300X GPUsdstack.ai · 2024-10-09
  21. DiscussionReflection-Llama-3.1-70B is Llama-3 with LoRAold.reddit.com · 2024-09-08
  22. ArticleNvidia's new Llama-3.1 Nemotron Ultra outperforms DeepSeek R1 at half the sizeventurebeat.com · 2025-04-11
  23. ArticleChat with Meta Llama 3.1 405Bllama3.replicate.dev · 2024-07-23

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 26

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; heavily run locally (80 quantized builds); a big base for builders (2,345 fine-tunes, adapters and merges).

  • As a service1Featherless
  • On own hardware80quantized builds
  • Built on2,3451,765 fine-tunes · 541 adapters · 39 merges
  • In apps47Hugging Face Spaces

Top Spaces running it: John6666/joy-caption-pre-alpha-mod ♥ 65 · rahul7star/ai-toolkit ♥ 10 · MegaTronX/joy-caption-pre-alpha-mod ♥ 5 · lucyknada/hf-model-get-chat-template ♥ 4

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 (2024-07-23), amber triangles are 10 dated articles (each links to it), grey ticks are repo commits.

AugSepOctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2025-02-15: 1 repo commit2025-02-02: 1 repo commit2024-11-22: 1 repo commit2024-09-03: 3 repo commits2024-08-20: 3 repo commits2024-08-16: 3 repo commits2024-08-15: 3 repo commits2024-08-13: 3 repo commits2024-08-09: 3 repo commits2024-08-08: 3 repo commits2024-08-07: 6 repo commitsLlama 3.1 · 2024-07-23Meta's Llama 3.1 can recall 42 percent of the first Harry Potter book · 2025-06-15Show HN: Tune LLaMa3.1 on Google Cloud TPUs · 2024-09-11Llama 3.1 in C · 2024-07-24Longwriter – Increase llama3.1 output to 10k words · 2024-10-07Cerebras launches inference for Llama 3.1; benchmarked at 1846 tokens/s on 8B · 2024-08-27Llama 3.1: Our most capable models to date · 2024-07-23Why Llama 3.1 is Important · 2024-07-23Nvidia presents Llama-Mesh: Generating 3D Mesh with Llama 3.1 8B · 2024-11-17Coding with Llama 3.1, New DeepSeek Coder and Mistral Large · 2024-07-25Weights 2024-07-23 · 2024-07-23Weights 2024-07-23now · 1 provider
AugSepOctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2025-02-15: 1 repo commit2025-02-02: 1 repo commit2024-11-22: 1 repo commit2024-09-03: 3 repo commits2024-08-20: 3 repo commits2024-08-16: 3 repo commits2024-08-15: 3 repo commits2024-08-13: 3 repo commits2024-08-09: 3 repo commits2024-08-08: 3 repo commits2024-08-07: 6 repo commitsLlama 3.1 · 2024-07-23Meta's Llama 3.1 can recall 42 percent of the first Harry Potter book · 2025-06-15Show HN: Tune LLaMa3.1 on Google Cloud TPUs · 2024-09-11Llama 3.1 in C · 2024-07-24Longwriter – Increase llama3.1 output to 10k words · 2024-10-07Cerebras launches inference for Llama 3.1; benchmarked at 1846 tokens/s on 8B · 2024-08-27Llama 3.1: Our most capable models to date · 2024-07-23Why Llama 3.1 is Important · 2024-07-23Nvidia presents Llama-Mesh: Generating 3D Mesh with Llama 3.1 8B · 2024-11-17Coding with Llama 3.1, New DeepSeek Coder and Mistral Large · 2024-07-25Weights 2024-07-23 · 2024-07-23Weights 2024-07-23now · 1 provider

What people built on it

2,425 derivatives on the Hub. Which build to run, by runtime: the most downloaded in each class.

2,425 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.

80 quantized (Hugging Face model tree)1,765 fine-tunes (Hugging Face model tree)39 merges (Hugging Face model tree)541 adapters (Hugging Face model tree)80 quantized1,765 fine-tunes39 merges541 adapters
80 quantized (Hugging Face model tree)1,765 fine-tunes (Hugging Face model tree)39 merges (Hugging Face model tree)541 adapters (Hugging Face model tree)80 quantized1,765 fine-tunes39 merges541 adapters

All variants →

Reference

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

Use-case evidence

4 use cases

What it is good at 4 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

20 fields

Listed in LLMs

Facts

Pipeline tagtext-generation
Librarytransformers
ArchitecturesLlamaForCausalLM
Model typellama
Dtypebfloat16
Params by dtypeBF16: 8,030,261,248
Size bandM
MoEno
Context length131,072 (config.json max_position_embeddings)
Languagesen
LicenseLlama 3.1 Community License (llama3.1)
Hub snapshot2026-10-26

Servability

vLLM · SGLang

Servability

vLLM: supported · LlamaForCausalLM · 4b1c04e76fe9ac3ca8b7e541dd423e7d5f38dc60SGLang: supported · LlamaForCausalLM · 60d941293e3af27a12c6eb64e2c3e2e1a17f100f

vLLM registry (4b1c04e76fe9ac3ca8b7e541dd423e7d5f38dc60) · SGLang registry (60d941293e3af27a12c6eb64e2c3e2e1a17f100f) · 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 Meta-Llama-3.1-8B-Instruct: 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

40 variants

Lineage

Fine-tuned from meta-llama/Llama-3.1-8B-Instruct Family: unsloth/Llama-3.1 2,425 derivatives on the Hub

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

quantized: 80adapter: 541finetune: 1,765merge: 39

Top variants (40 shown, ranked by downloads)

Relation
40 rows
Variant Relation Quant Params Band License Author Likes Downloads
injoy/Meta-Llama-3.1-8B-Instruct-gguf-f16 quantized gguf — — apache-2.0 injoy 0 17.2k
qiaw99/Llama3.1-8B-Instruct-OpenbookQA-DPO-C-G-sequential adapter — — — — qiaw99 0 13.9k
qiaw99/Llama3.1-8B-Instruct-OpenbookQA-SFT-D adapter — — — — qiaw99 0 12.6k
Leejy0-0/ko-Meta-Llama-3.1-8B-Instruct finetune — 8.03B M apache-2.0 Leejy0-0 0 12.6k
aleegis10/8ed9fe91-c2b5-42ca-8efb-927b4c8fbf45 adapter — — — llama3.1 aleegis10 0 11.1k
qiaw99/Llama3.1-8B-Instruct-OpenbookQA-DPO-C adapter — — — — qiaw99 0 10.7k
prxy5606/98345738-30aa-41c4-bf69-2392a1ce4d0a adapter — — — llama3.1 prxy5606 0 10.6k
qiaw99/Llama3.1-8B-Instruct-OpenbookQA-DPO-para-new adapter — — — — qiaw99 0 9.7k
qiaw99/Llama3.1-8B-Instruct-OpenbookQA-DPO-G-v1 adapter — — — — qiaw99 0 9.3k
prxy5604/7a4e7415-b287-4864-abf4-6ec01099dad8 adapter — — — llama3.1 prxy5604 0 8.5k
juiceb0xc0de/bella-bartender-8b-llama3.1 finetune — 8.03B M llama3.1 juiceb0xc0de 4 8.3k
qiaw99/Llama3.1-8B-Instruct-OpenbookQA-DPO-D adapter — — — — qiaw99 0 8.5k
prxy5607/28d72712-34c7-4d67-8e6e-8eb45aef7e8e adapter — — — llama3.1 prxy5607 0 8.2k
minhtrannnn/284018e7-8496-44b3-b055-1c0111682219 adapter — — — llama3.1 minhtrannnn 0 7.9k
Espresso-AI/search-llm adapter — — — — Espresso-AI 0 7.8k
NoCanGo/WaifuGPT quantized GGUF — — apache-2.0 NoCanGo 1 7.7k
qiaw99/Llama3.1-8B-Instruct-OpenbookQA-SFT-DPO-G adapter — — — — qiaw99 0 7.6k
robiulawaldev/da92a142-8a96-438e-80b3-13cf5e027f66 adapter — — — llama3.1 robiulawaldev 0 7.4k
qiaw99/Llama3.1-8B-Instruct-OpenbookQA-SFT-C adapter — — — — qiaw99 0 7.4k
nhung02/7be752c0-2426-4896-9c97-c044f98d6009 adapter — — — llama3.1 nhung02 0 7.2k
qiaw99/Llama3.1-8B-Instruct-OpenbookQA-DPO-G adapter — — — — qiaw99 0 6.3k
trangtrannnnn/1df0fada-0940-4316-92fb-19ce43f97548 adapter — — — llama3.1 trangtrannnnn 0 6.3k
qiaw99/Llama3.1-8B-Instruct-OpenbookQA-DPO-G-new adapter — — — — qiaw99 0 6.3k
lhong4759/ac11856d-78c8-4956-9dd4-f2022250559f adapter — — — llama3.1 lhong4759 0 6.1k
qiaw99/Llama3.1-8B-Instruct-OpenbookQA-SFT-G adapter — — — — qiaw99 0 6.1k
tuanna08go/e22e436b-c113-489d-bde5-64f85e908839 adapter — — — llama3.1 tuanna08go 0 6k
datlaaaaaaa/1d9b7de9-1129-4a81-b47c-7fee12fac1e2 adapter — — — llama3.1 datlaaaaaaa 0 5.9k
ncbateman/65eaec89-ddb3-4b65-866f-c621f95eea55 adapter — — — llama3.1 ncbateman 0 5.8k
mrHungddddh/568391c6-613d-42b3-b9e0-bb9cb673e152 adapter — — — llama3.1 mrHungddddh 0 5.8k
qiaw99/Llama3.1-8B-Instruct-OpenbookQA-SFT-DPO-F adapter — — — — qiaw99 0 5.7k
datlaaaaaaa/cf707148-8a14-4b17-af50-c0c419a06bb2 adapter — — — llama3.1 datlaaaaaaa 0 5.7k
qiaw99/Llama3.1-8B-Instruct-OpenbookQA-SFT-F adapter — — — — qiaw99 0 5.6k
prxy5607/f59b404a-1d76-4c38-98b7-5a73c0ecea6e adapter — — — llama3.1 prxy5607 0 5.6k
qiaw99/Llama3.1-8B-Instruct-OpenbookQA-SFT-DPO-C adapter — — — — qiaw99 0 5.5k
estrogen/L3.1-8b-Ink-ep1-adpt adapter — — — — estrogen 0 5.3k
tripathiarpan20/tuning-9a1e2037-9d80-4b5e-8374-fc6ddc0609a8 adapter — — — llama3.1 tripathiarpan20 0 5.2k
ncbateman/fc2ba2fb-1ff0-4e66-b0bb-667bfdfd0d59 adapter — — — llama3.1 ncbateman 0 5.2k
qiaw99/Llama3.1-8B-Instruct-ARC-challenge-DPO-G adapter — — — — qiaw99 0 5.1k
hongngo/612beea2-1e23-46e9-b772-5d201f773304 adapter — — — llama3.1 hongngo 0 5.1k
duyphu/4ecd8066-f334-4600-a146-3ec7b56f98be adapter — — — llama3.1 duyphu 0 5k

Repository changelog

30 commits

Repository changelog 30 commits

DateCommitSHA
2025-02-15 Add files using upload-large-folder tool a285619
2025-02-02 Add files using upload-large-folder tool 28e14b5
2024-11-22 Update README.md da09a33
2024-09-03 Upload tokenizer 4a5a8d9
2024-09-03 Upload config 62b4abd
2024-09-03 Upload config e23cc57
2024-08-20 Upload tokenizer 6dfabbc
2024-08-20 Upload config 38d94f7
2024-08-20 Upload config 1119532
2024-08-16 Upload tokenizer 4c9aa50
2024-08-16 Upload config 6298b94
2024-08-16 Upload config 3f6ff05
2024-08-15 Upload tokenizer a58182b
2024-08-15 Upload config 39d4065
2024-08-15 Upload config 06476c0
2024-08-13 Upload tokenizer 76db79b
2024-08-13 Upload config c984e4c
2024-08-13 Upload config 1964578
2024-08-09 Upload tokenizer 04ebeec
2024-08-09 Upload config b1e3fae
2024-08-09 Upload config 4c6f03f
2024-08-08 Upload tokenizer f073dd6
2024-08-08 Upload config 20b4ce3
2024-08-08 Upload config 4b2f37b
2024-08-07 Upload tokenizer 1959b3d
2024-08-07 Upload config 59a397a
2024-08-07 Upload config ec0724a
2024-08-07 Upload tokenizer 315fc37
2024-08-07 Upload config b91f11a
2024-08-07 Upload config a5483c8

All providers

1 provider · 1 endpoint

Where to run 1 providers · 1 endpoints

Hosted endpoints observed for Meta-Llama-3.1-8B-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.

ProviderModel refContextQuant$/M in$/M outtok/sTTFTToolsStatusObserved
Featherless
hf
unsloth/Meta-Llama-3.1-8B-Instruct — — — — — — — live 2026-10-26

Articles and coverage

25 pieces

Ranked by source signals (HN, Lobsters, authority domains, official posts) and recency.

Analysis9

llama.meta.com2024-07-23HN front pageabout the Llama 3.1 familyHN 437 pts · 269 comments42 words
understandingai.org2025-06-15HN front pageabout the Llama 3.1 familyHN 191 pts · 305 comments
github.com2024-09-11authorityHN front pageabout the Llama 3.1 familyHN 189 pts · 52 comments869 words
github.com2024-07-24authorityHN front pageabout the Llama 3.1 familyHN 212 pts · 36 comments5,858 words
github.com2024-10-07authorityHN front pageabout the Llama 3.1 familyHN 154 pts · 29 comments6,696 words
ai.meta.com2024-07-23authorityabout the Llama 3.1 familyHN 27 pts · 3 comments2,136 words
timkellogg.me2024-07-23about the Llama 3.1 familyHN 56 pts · 23 comments
research.nvidia.com2024-11-17authorityHN 20 pts · 1 comments
aider.chat2024-07-25about the Llama 3.1 familyHN 32 pts · 7 comments

Community1

twitter.com2024-08-27about the Llama 3.1 familyHN 95 pts · 42 comments
All coverage tracked for this model (25) — append-only, nothing is ever removed
TitleSourcePublishedFirst seenSignals
Show HN: Llama 3.1 70B on a single RTX 3090 via NVMe-to-GPU bypassing the CPUgithub.com2026-02-212026-10-07hn
Meta's Llama 3.1 can recall 42 percent of the first Harry Potter bookunderstandingai.org2025-06-152026-10-07hn
Nvidia's new Llama-3.1 Nemotron Ultra outperforms DeepSeek R1 at half the sizeventurebeat.com2025-04-112026-10-07hn
Llama 3.1 405B now runs at 969 tokens/s on Cerebras Inferencecerebras.ai2024-11-192026-10-07hn
Nvidia presents Llama-Mesh: Generating 3D Mesh with Llama 3.1 8Bresearch.nvidia.com2024-11-172026-10-07hn
Benchmarking Llama 3.1 405B on 8x AMD MI300X GPUsdstack.ai2024-10-092026-10-07hn
Longwriter – Increase llama3.1 output to 10k wordsgithub.com2024-10-072026-10-07hn
Llama 3.1 Omni Modelgithub.com2024-09-182026-10-07hn
g1: Using Llama-3.1 70B on Groq to create o1-like reasoning chainsgithub.com2024-09-152026-10-07hn
Show HN: Tune LLaMa3.1 on Google Cloud TPUsgithub.com2024-09-112026-10-07hn
Reflection-Llama-3.1-70B is Llama-3 with LoRAold.reddit.com2024-09-082026-10-07hn
Cerebras launches inference for Llama 3.1; benchmarked at 1846 tokens/s on 8Btwitter.com2024-08-272026-10-07hn
Hermes 3: The First Fine-Tuned Llama 3.1 405B Modellambdalabs.com2024-08-152026-10-07hn
Running the latest Llama 3.1 8B on Raspberry Pi [video]youtube.com2024-07-302026-10-07hn
Show HN: Run Llama 3.1 8B in the browserapp.wiz.chat2024-07-282026-10-07hn
Llama-3.1 supports tool calls via promptingbraintrust.dev2024-07-262026-10-07hn
Coding with Llama 3.1, New DeepSeek Coder and Mistral Largeaider.chat2024-07-252026-10-07hn
Llama 3.1 in Cgithub.com2024-07-242026-10-07hn
Why Llama 3.1 is Importanttimkellogg.me2024-07-232026-10-07hn
Show HN: Finetune Llama-3.1 2x faster in a Colabcolab.research.google.com2024-07-232026-10-07hn
Meta releases an open-weights GPT-4-level AI model, Llama 3.1 405Barstechnica.com2024-07-232026-10-07hn
Meta Llama 3.1 405Bopenrouter.ai2024-07-232026-10-07hn
Chat with Meta Llama 3.1 405Bllama3.replicate.dev2024-07-232026-10-07hn
Llama 3.1: Our most capable models to dateai.meta.com2024-07-232026-10-07hn
Llama 3.1llama.meta.com2024-07-232026-10-07hn

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Sources

3 sources

Sources

Hub snapshot: 2026-10-26 · HF API: 2026-10-26 07:21 UTC · Providers: 2026-10-26 07:26 UTC · Articles: 2026-10-26 07:27 UTC · Summary: 2026-10-07 15:11 UTC · Last verified 2026-10-26 07:27 UTC

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