Models › Phi-3 family

Phi-3-mini-4k-instruct

microsoft MIT out 3 years ago

3.82B parameters, text in, text out, 4K tokens of context. 1 provider serves it.

Verified 2026-10-25 Rank #139 in LLMs · score 93.8 method v1 Sources 3 Downloads 30d 340.8k · #206 of 619 tracked

Changed this week: 2 new quantized builds on the Hub (183 in all).2026-10-24

Can I use it?MITPermissivelicence file2026-10-24
Do people use it?340.8kdownloads, 30 days#206 of 619 we track · top 33%+4 likes, downloads −7% this week1,479 likesHugging Face2026-10-24

Worth reading

Picked by rule from 27 tracked pieces: the lab's own post, the most shared, a field report, the latest.

Most discussed · 411 HN pts

Phi-3 Technical Report

Phi-3 models achieve high performance rivaling Mixtral 8x7B by training on a scaled-up dataset of heavily filtered publicly available web data and synthetic data.

arxiv.org 2024-04-23 411 HN pts · 130 comments 463 words about the Phi 3 family family
Latest · 22 months ago

Exploring Microsoft's Phi-3-Mini and its integration with tool like Ollama

Microsoft's Phi-3-Mini is a 3.8 billion-parameter language model designed for efficiency on devices with limited resources like notebooks and smartphones.

  • Organizations needing full-scale enterprise solutions should consider deploying phi-3.5-mini on Azure for production-grade stability.
  • Pieces CLI can access your pastebin to store code snippets generated by the local phi-3-mini model.
pieces.app 2024-12-26 84 HN pts · 31 comments 1.2k words about the Phi 3 family family

25 best of 27 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. CodeOllama v0.1.33 with Llama 3, Phi 3, and Qwen 110Bgithub.com · 2024-04-28 · 192 HN pts
  2. CodeMicrosoft Phi-3 Cookbookgithub.com · 2024-05-21 · 152 HN pts
  3. PaperPhi-3 Technical Report: A Highly Capable Language Model Locally on Your Phonearxiv.org · undated
  4. ArticlePhi-3: Redefining what's possible with SLMsazure.microsoft.com · 2024-04-23 · 16 HN pts · official
  5. ArticlePhi-3-Mediumazure.microsoft.com · 2024-05-21 · 6 HN pts · official
  6. ArticlePhi-3 Technical a Highly Capable Language Model Locally on Your Phonehuggingface.co · 2024-04-23 · 7 HN pts
  7. DiscussionMicrosoft Updated Phi-3twitter.com · 2024-07-02 · 35 HN pts
  8. ArticleTiny but mighty: The Phi-3 small language models with big potentialnews.microsoft.com · 2024-04-23 · 6 HN pts · official
  9. ArticleBuilding Intelligent Applications with Local RAG in .NET and Phi-3techcommunity.microsoft.com · 2024-07-02 · official
  10. ArticleMicrosoft launches Phi-3, its smallest AI model yettheverge.com · 2024-04-23
  11. ArticleThe latest major open LLM releases: Mixtral, Llama 3, Phi-3, and OpenELMmagazine.sebastianraschka.com · 2024-05-12
  12. ArticleLocal iOS/macOS phi-3-mini-4k-instructapps.apple.com · 2024-05-14
  13. ArticleMicrosoft releases powerful new Phi-3.5 models, beating Google, OpenAI and moreventurebeat.com · 2024-08-21
  14. PaperPhi-3 Technical Report: A Highly Capable Language Model Locally on Your Phonearxiv.org · 2024-08-30
  15. CodeShow HN: Phi-3-MLX – Language and Vision Models for Apple Silicongithub.com · 2024-07-19
  16. ArticlePhi-3-vision in 50 lines of C# with ONNX Runtime GenAInietras.com · 2024-06-05
  17. ArticleAfter Llama3 here we have Phi-3: Small Language Models beating LLMsdidyouknowbg8.wordpress.com · 2024-04-23
  18. ArticlePhi-3-mini-4k-instruct | Model Catalog | Microsoft Foundryai.azure.us · undated
  19. ArticlePhi 3 Mini 4K Instruct by microsoft — VRAM 7.7GB, 4K context | LLM Explorerllm-explorer.com · undated
  20. ArticlePhi 3 Mini 4K Instruct Benchmarks, Pricing & Specs — Vector Wirevectorwire.ai · undated
  21. ArticlePhi 3 Mini 4K Instruct by microsoftllm.extractum.io · undated
  22. ArticlePhi-3 Technical Report: A Highly Capable Language Model Locally on Your Phonesaikatkumardey.com · undated
  23. Articlephi-3-mini: The 3.8B Powerhouse Reshaping LLM Performance on Your Phonehackernoon.com · undated

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; heavily run locally (183 quantized builds); a big base for builders (2,006 fine-tunes, adapters and merges).

  • As a service1Featherless
  • On own hardware183quantized builds
  • Built on2,0061,124 fine-tunes · 869 adapters · 13 merges
  • In apps100+Hugging Face Spaces

Top Spaces running it: ginipick/FLUXllama ♥ 561 · KingNish/JARVIS ♥ 292 · Nymbo/Serverless-TextGen-Hub ♥ 44 · MBZUAI/LLaMA-3-V ♥ 33

Will it fit?

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

Fits a 16 GB card at INT4

About 2.3 GB at INT4, 4.6 GB at FP8, 9.2 GB at BF16: weights only, so leave room for the KV cache.

16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 2.3 GB of weights (estimate; KV cache and activations extra)INT42.3 GBFP8: about 4.6 GB of weights (estimate; KV cache and activations extra)FP84.6 GBBF16: about 9.2 GB of weights (estimate; KV cache and activations extra)BF169.2 GB
16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 2.3 GB of weights (estimate; KV cache and activations extra)INT42.3 GBFP8: about 4.6 GB of weights (estimate; KV cache and activations extra)FP84.6 GBBF16: about 9.2 GB of weights (estimate; KV cache and activations extra)BF169.2 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 (2024-04-22), amber triangles are 9 dated articles (each links to it), grey ticks are repo commits.

MayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2025-12-10: 2 repo commits2024-09-20: 1 repo commit2024-08-20: 1 repo commit2024-07-01: 2 repo commits2024-06-11: 1 repo commit2024-05-31: 1 repo commit2024-05-22: 1 repo commit2024-05-21: 1 repo commit2024-05-20: 1 repo commit2024-05-16: 1 repo commit2024-05-03: 1 repo commit2024-05-02: 2 repo commits2024-04-29: 2 repo commits2024-04-28: 2 repo commits2024-04-26: 3 repo commits2024-04-25: 1 repo commit2024-04-22: 2 repo commitsPhi-3 Technical Report · 2024-04-23Ollama v0.1.33 with Llama 3, Phi 3, and Qwen 110B · 2024-04-28Microsoft Phi-3 Cookbook · 2024-05-21Exploring Microsoft's Phi-3-Mini and its integration with tool like Ollama · 2024-12-26Phi-3: Redefining what's possible with SLMs · 2024-04-23Phi-3-Medium · 2024-05-21Phi-3 Technical a Highly Capable Language Model Locally on Your Phone · 2024-04-23Microsoft Updated Phi-3 · 2024-07-02Tiny but mighty: The Phi-3 small language models with big potential · 2024-04-23Weights 2024-04-22 · 2024-04-22Weights 2024-04-22now · 1 provider
MayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2025-12-10: 2 repo commits2024-09-20: 1 repo commit2024-08-20: 1 repo commit2024-07-01: 2 repo commits2024-06-11: 1 repo commit2024-05-31: 1 repo commit2024-05-22: 1 repo commit2024-05-21: 1 repo commit2024-05-20: 1 repo commit2024-05-16: 1 repo commit2024-05-03: 1 repo commit2024-05-02: 2 repo commits2024-04-29: 2 repo commits2024-04-28: 2 repo commits2024-04-26: 3 repo commits2024-04-25: 1 repo commit2024-04-22: 2 repo commitsPhi-3 Technical Report · 2024-04-23Ollama v0.1.33 with Llama 3, Phi 3, and Qwen 110B · 2024-04-28Microsoft Phi-3 Cookbook · 2024-05-21Exploring Microsoft's Phi-3-Mini and its integration with tool like Ollama · 2024-12-26Phi-3: Redefining what's possible with SLMs · 2024-04-23Phi-3-Medium · 2024-05-21Phi-3 Technical a Highly Capable Language Model Locally on Your Phone · 2024-04-23Microsoft Updated Phi-3 · 2024-07-02Tiny but mighty: The Phi-3 small language models with big potential · 2024-04-23Weights 2024-04-22 · 2024-04-22Weights 2024-04-22now · 1 provider

What people built on it

2,189 derivatives on the Hub. Which build to run, by runtime: the most downloaded in each class.

2,189 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.

183 quantized (Hugging Face model tree)1,124 fine-tunes (Hugging Face model tree)13 merges (Hugging Face model tree)869 adapters (Hugging Face model tree)183 quantized1,124 fine-tunes13 merges869 adapters
183 quantized (Hugging Face model tree)1,124 fine-tunes (Hugging Face model tree)13 merges (Hugging Face model tree)869 adapters (Hugging Face model tree)183 quantized1,124 fine-tunes13 merges869 adapters

All variants →

Reference

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

Benchmarks

8 rows

Benchmarks 8 rows

measured third-party leaderboard rowauthor-reported number from the model card or eval files (8)No confidence intervals unless the source gave them; settings differ between rows, so compare within a benchmark, not across. Date = the benchmark's own date when it gives one, else when we read it.
BenchmarkValueSetting / notesReported byDate
author-reported Average36.7June 2024 Updatemodel author2026-10-07
author-reported GPQA Diamond · Reason through hard problems30.6June 2024 Updatemodel author2026-10-07
author-reported Instruction Extra Hard6June 2024 Updatemodel author2026-10-07
author-reported Instruction Hard5.1June 2024 Updatemodel author2026-10-07
author-reported Instructions Challenge42.3June 2024 Updatemodel author2026-10-07
author-reported JSON Structure Output52.3June 2024 Updatemodel author2026-10-07
author-reported MMLU · Reason through hard problems70.9June 2024 Updatemodel author2026-10-07
author-reported XML Structure Output49.8June 2024 Updatemodel author2026-10-07

What the card says

1 cited sentence

Summary generated, cited

The model is released under an MIT license and supports a 4K context length.[1][2]

  1. license
  2. “Mini version in two variants [4K]”

Generated 2026-10-07 15:02 UTC by parasail-gemma-4-26b-a4b-it; each numeral points at the fact it rests on. Not a verdict.

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

21 fields

Listed in LLMs

Facts

Pipeline tagtext-generation
Librarytransformers
ArchitecturesPhi3ForCausalLM
Model typephi3
Dtypebfloat16
Params by dtypeBF16: 3,821,079,552
Size bandM
MoEno
Context length4,096 (config.json max_position_embeddings)
Languagesen, fr
LicenseMIT (mit)
Hub snapshot2026-10-25

Servability

vLLM · SGLang

Servability

vLLM: supported · Phi3ForCausalLM · 7050ef881ff0835f6890a47db1859a24c65481d6SGLang: supported · Phi3ForCausalLM · 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 Phi-3-mini-4k-instruct: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)9.2 GB · Single GPU (<24 GB)
FP8 (1 byte/param)4.6 GB · Single GPU (<24 GB)
INT4 (0.5 bytes/param)2.3 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: microsoft/Phi-3 2,189 derivatives on the Hub

quantized: 183finetune: 1,124adapter: 869merge: 13

Top variants (40 shown, ranked by downloads)

Relation
Quant
40 rows
Variant Relation Quant Params Band License Author Likes Downloads
solidrust/Phi-3-mini-4k-instruct-AWQ quantized AWQ 3.82B M — solidrust 0 645.5k
mlc-ai/Phi-3-mini-4k-instruct-q4f16_1-MLC quantized — — — — mlc-ai 1 209.6k
bartowski/Phi-3.1-mini-4k-instruct-GGUF quantized GGUF — — mit bartowski 45 163.4k
mozilla-ai/Phi-3-mini-4k-instruct-llamafile finetune — — — apache-2.0 mozilla-ai 16 108.2k
e-palmisano/Phi3-ITA-mini-4K-instruct finetune — 3.82B M mit e-palmisano 1 96.1k
lmstudio-community/Phi-3.1-mini-4k-instruct-GGUF quantized GGUF — — mit lmstudio-community 24 76.6k
OpenVINO/Phi-3-mini-4k-instruct-int4-ov quantized int4 — — mit OpenVINO 4 72.9k
numind/NuExtract finetune — 3.82B M mit numind 236 43.6k
qwp4w3hyb/Phi-3-mini-4k-instruct-iMat-GGUF quantized GGUF — — mit qwp4w3hyb 1 40.8k
second-state/Phi-3-mini-4k-instruct-GGUF quantized GGUF — — mit second-state 5 40.1k
gaianet/Phi-3-mini-4k-instruct-GGUF quantized GGUF — — mit gaianet 1 36.4k
legraphista/Phi-3-mini-4k-instruct-update2024_07_03-IMat-GGUF quantized GGUF — — mit legraphista 0 32.9k
ycheng1024/task-20-microsoft-Phi-3-mini-4k-instruct adapter — — — — ycheng1024 0 32.9k
bartowski/Phi-3-mini-4k-instruct-v0.3-GGUF quantized GGUF — — mit bartowski 5 25.5k
MaziyarPanahi/calme-2.3-phi3-4b finetune — 3.82B M mit MaziyarPanahi 9 23.9k
brittlewis12/Phi-3-mini-4k-instruct-GGUF quantized GGUF — — mit brittlewis12 2 22.1k
legraphista/Phi-3-mini-4k-instruct-IMat-GGUF quantized GGUF — — mit legraphista 0 21.9k
ContinuousAT/Phi-CAT adapter — — — — ContinuousAT 0 20.3k
backyardai/Phi-3-mini-4k-instruct-GGUF quantized GGUF — — mit backyardai 0 16.7k
ab-ai/PII-Model-Phi3-Mini finetune — 3.82B M mit ab-ai 10 14.1k
QuantFactory/NuExtract-GGUF quantized GGUF — — mit QuantFactory 4 9.5k
flockgo/task-1-microsoft-Phi-3-mini-4k-instruct adapter — — — — flockgo 0 8.8k
DreamGallery/task-5-microsoft-Phi-3-mini-4k-instruct adapter — — — — DreamGallery 0 8.3k
lucifer-ms/task-3-microsoft-Phi-3-mini-4k-instruct adapter — — — — lucifer-ms 0 8.3k
DreamGallery/task-1-microsoft-Phi-3-mini-4k-instruct adapter — — — — DreamGallery 0 7.5k
KrithikV/MedMobile finetune — 3.82B M mit KrithikV 8 6.9k
mlc-ai/Phi-3-mini-4k-instruct-q4f32_1-MLC quantized — — — — mlc-ai 0 7.3k
matrixportalx/Phi-3-mini-4k-instruct-Q4_K_M-GGUF quantized GGUF — — mit matrixportalx 4 6.3k
moelanoby/phi-3-M3-coder finetune — 3.82B M — moelanoby 48 4k
sam-fd/task-13-microsoft-Phi-3-mini-4k-instruct adapter — 3.82B M — sam-fd 0 6.2k
DreamGallery/task-6-microsoft-Phi-3-mini-4k-instruct adapter — — — — DreamGallery 0 6k
latiao1999/task-5-microsoft-Phi-3-mini-4k-instruct adapter — — — — latiao1999 0 6k
QuantFactory/phi-3-portuguese-tom-cat-4k-instruct-GGUF quantized GGUF — — apache-2.0 QuantFactory 2 5.8k
Phora68/bible-study-phi3-mini quantized GGUF 3.82B M mit Phora68 3 5.4k
ishanmane/phi3-rewriter-sft adapter — — — — ishanmane 0 5.5k
misterJB/arkadas-field-717hz finetune — 3.82B M — misterJB 0 5.5k
srrthk/task-13-microsoft-Phi-3-mini-4k-instruct adapter — — — — srrthk 0 4.9k
leliuga/Phi-3-mini-4k-instruct-bnb-4bit quantized -bnb 3.93B M other leliuga 6 4.5k
QuantFactory/calme-2.3-phi3-4b-GGUF quantized GGUF — — mit QuantFactory 0 4.5k
edumunozsala/phi-3-mini-QLoRA adapter — — — mit edumunozsala 0 4.2k

Repository changelog

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

Repository changelog 25 commits

DateCommitSHA
2025-12-10 Update README.md (#109) f39ac1d
2025-12-10 Upload data_summary_card.md (#108) 87e6c1e
2024-09-20 Update README.md (#96) 0a67737
2024-08-20 Update README.md 5a516f8
2024-07-01 Minor updates on README c1358f8
2024-07-01 Update model (#77) 4f818b1
2024-06-11 Add attention_bias to make TGI work (#64) ff07dc0
2024-05-31 Add link to Phi-3 vision ONNX models d269012
2024-05-22 Update sample_finetune.py (#65) 5fa3419
2024-05-21 Update README 19f7775
2024-05-20 Update README.md d6b5c7b
2024-05-16 Fix typo (#58) 8f5f3a0
2024-05-03 fix(README): Adds temperature=0.7 to prevent Inference API from going off the chart. 920b6cf
2024-05-02 fix(tokenizer): Also updates tokenizer.json to prevent any mismatch. 653ee82
2024-05-02 fix(tokenizer_config): Adjusts `rstrip` of special tokens. (#53) 4eea1a7
2024-04-29 Update README.md 2921602
2024-04-29 fix(root): Replaces system by user to improve generation experience. 300945e
2024-04-28 Update docstrings 291e9e3
2024-04-28 Update docstring in sample_finetune.py 13565ec
2024-04-26 Update README.md cc80d6c
2024-04-26 Update sample_finetune.py (#42) 6a07688
2024-04-26 chore(readme): Adds a proper chat example to widget. 4b6011c
2024-04-25 fix(readme): Adds information about placeholder tokens. 3c0c9df
2024-04-22 chore(root): Initial files upload. 65be4e0
2024-04-22 initial commit c91d28f

All providers

1 provider · 1 endpoint

Where to run 1 providers · 1 endpoints

Hosted endpoints observed for Phi-3-mini-4k-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
microsoft/Phi-3-mini-4k-instruct — — — — — — — live 2026-10-25

Articles and coverage

27 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

azure.microsoft.com2024-04-23officialauthorityabout the Phi 3 familyHN 16 pts · 1 comments1,074 words
Microsoft introduces Phi-3, a family of open small language models including the upcoming Phi-3-small (7B) and Phi-3-medium (14B). Phi-3-mini is a 3.8B parameter model available on Azure AI Studio, Hugging Face, and Ollama with a context window of up to 128K tokens. The models have lower capacity to retain facts on factual knowledge benchmarks due to their smaller size.written, reviewed, cited
  • Phi-3-mini can be used on-device, especially when further optimized with ONNX Runtime for cross-platform availability.
azure.microsoft.com2024-05-21officialauthorityabout the Phi 3 familyHN 6 pts · 1 comments1,243 words
news.microsoft.com2024-04-23officialauthorityabout the Phi 3 familyHN 6 pts · 0 comments

Analysis6

arxiv.org2024-04-23authorityHN front pageabout the Phi 3 familyHN 411 pts · 130 comments463 words
Phi-3 models achieve high performance rivaling Mixtral 8x7B by training on a scaled-up dataset of heavily filtered publicly available web data and synthetic data. This approach enables deployment locally on your phone despite small parameter counts like the 3.8 billion in phi-3-mini. The phi-3.5-MoE variant reaches 78% on MMLU with 6.6 billion active parameters, while phi-3.5-Vision handles multi-image prompts.written, reviewed, cited
github.com2024-04-28authorityHN front pageabout the Phi 3 familyHN 192 pts · 64 comments38 words
github.com2024-05-21authorityHN front pageabout the Phi 3 familyHN 152 pts · 57 comments978 words
Microsoft released the Phi family of open-source small language models, which are the most capable and cost-effective SLMs available. The repository includes 50+ language translations that significantly increase download size, requiring sparse checkout to clone without them. Specific samples include Phi-4-Reasoning-Vision-15B for reasoning-vision tasks, and the models support deployment on cloud or edge devices. Developers should integrate Azure AI Content Safety to detect harmful user-generated and AI-generated content in applications.written, reviewed, cited
  • Developers can use sparse checkout commands to clone the repository without downloading the translation files.
  • The project contains specific samples for Phi-4-Mini-Flash-Reasoning-Instruct for math demonstrations.
pieces.app2024-12-26about the Phi 3 familyHN 84 pts · 31 comments1,213 words
Microsoft's Phi-3-Mini is a 3.8 billion-parameter language model designed for efficiency on devices with limited resources like notebooks and smartphones. It excels in reasoning and coding tasks, offering performance comparable to larger models such as GPT-3.5 while requiring less computational power. Variants like phi-3-mini-128k-instruct support extensive context windows, though the model currently lacks context window overflow handling and may reply with gibberish until a future ONNX release fixes the issue.written, reviewed, cited
  • Organizations needing full-scale enterprise solutions should consider deploying phi-3.5-mini on Azure for production-grade stability.
  • Pieces CLI can access your pastebin to store code snippets generated by the local phi-3-mini model.
arxiv.orgauthorityabout the Phi 3 family7,302 words
Microsoft introduces phi-3-mini, a 3.8 billion parameter language model trained on 3.3 trillion tokens that rivals larger models like Mixtral 8x7B and GPT-3.5. The phi-3.5 series expands this with a 16 x 3.8B MoE model featuring 6.6 billion active parameters and a 4.2 billion parameter vision model. Quantized phi-3-mini runs at more than 12 tokens per second on an iPhone 14 with an A16 Bionic chip.written, reviewed, cited
  • The phi-3-small model switches to GEGLU activation and uses Maximal Update Parametrization to tune hyperparameters.
  • The phi-3.5-MoE model employs top2 routing among 16 expert networks to activate only 2 experts per token.
  • Training phi-3-medium on 4.8T tokens yields less benchmark improvement from 7B to 14B than from 3.8B to 7B.
huggingface.co2024-04-23authorityabout the Phi 3 familyHN 7 pts · 7 comments1,073 words

Community1

twitter.com2024-07-02about the Phi 3 familyHN 35 pts · 15 comments
All coverage tracked for this model (27) — append-only, nothing is ever removed
TitleSourcePublishedFirst seenSignals
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phonearxiv.org—2026-10-07exa
Phi-3-mini-4k-instruct | Model Catalog | Microsoft Foundryai.azure.us—2026-10-07exa
Phi 3 Mini 4K Instruct by microsoft — VRAM 7.7GB, 4K context | LLM Explorerllm-explorer.com—2026-10-07exa
Phi 3 Mini 4K Instruct Benchmarks, Pricing & Specs — Vector Wirevectorwire.ai—2026-10-07exa
Phi 3 Mini 4K Instruct by microsoftllm.extractum.io—2026-10-07exa
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phonesaikatkumardey.com—2026-10-07exa
phi-3-mini: The 3.8B Powerhouse Reshaping LLM Performance on Your Phonehackernoon.com—2026-10-07exa
Exploring Microsoft's Phi-3-Mini and its integration with tool like Ollamapieces.app2024-12-262026-10-07hn
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phonearxiv.org2024-08-302026-10-07exa
Microsoft releases powerful new Phi-3.5 models, beating Google, OpenAI and moreventurebeat.com2024-08-212026-10-07hn
Show HN: Phi-3-MLX – Language and Vision Models for Apple Silicongithub.com2024-07-192026-10-07hn
Building Intelligent Applications with Local RAG in .NET and Phi-3techcommunity.microsoft.com official2024-07-022026-10-07hn
Microsoft Updated Phi-3twitter.com2024-07-022026-10-07hn
Phi-3-vision in 50 lines of C# with ONNX Runtime GenAInietras.com2024-06-052026-10-07hn
Train Phi-3 Visionwandb.ai2024-06-012026-10-07hn
Microsoft Phi-3 Cookbookgithub.com2024-05-212026-10-07hn
Phi-3-Mediumazure.microsoft.com official2024-05-212026-10-07hn
Local iOS/macOS phi-3-mini-4k-instructapps.apple.com2024-05-142026-10-07hn
The latest major open LLM releases: Mixtral, Llama 3, Phi-3, and OpenELMmagazine.sebastianraschka.com2024-05-122026-10-07hn
Tiny LLM Reviews: Phi 3 3.8bkyle.works2024-04-302026-10-07exa
Ollama v0.1.33 with Llama 3, Phi 3, and Qwen 110Bgithub.com2024-04-282026-10-07hn
After Llama3 here we have Phi-3: Small Language Models beating LLMsdidyouknowbg8.wordpress.com2024-04-232026-10-07hn
Phi-3: Redefining what's possible with SLMsazure.microsoft.com official2024-04-232026-10-07hn
Tiny but mighty: The Phi-3 small language models with big potentialnews.microsoft.com official2024-04-232026-10-07hn
Phi-3 Technical a Highly Capable Language Model Locally on Your Phonehuggingface.co2024-04-232026-10-07hn
Microsoft launches Phi-3, its smallest AI model yettheverge.com2024-04-232026-10-07hn
Phi-3 Technical Reportarxiv.org2024-04-232026-10-07hn

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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 15:02 UTC · Last verified 2026-10-25

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