Models › phi-1 family

microsoft MIT out 3 years ago

1.42B parameters, text in, text out, 2K tokens of context. 1 provider serves it.

Verified 2026-10-25 Rank #590 in LLMs · score 74.3 method v1 Sources 3 Downloads 30d 20.8k · #453 of 619 tracked

Can I run it?0.9GB at INT4Estimatefits a 16 GB cardmethod
Can I use it?MITPermissivelicence file2026-10-24
Do people use it?20.8kdownloads, 30 days#453 of 619 we track · below the median+2 likes, downloads −11% this week227 likesHugging Face2026-10-24

Worth reading

Picked by rule from 2 tracked pieces: the lab's own post, the most shared, a field report, the latest.

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; 8 quantized builds for local use.

  • As a service1Featherless
  • On own hardware8quantized builds
  • Built on143 fine-tunes · 10 adapters · 1 merges
  • In apps35Hugging Face Spaces

Top Spaces running it: LanguageBind/MoE-LLaVA ♥ 154 · Yeyito/llm_contamination_detector ♥ 27 · mPLUG/TinyChart-3B ♥ 17 · showlab/Show-o ♥ 17

Will it fit?

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

Fits a 16 GB card at INT4

About 0.9 GB at INT4, 1.7 GB at FP8, 3.4 GB at BF16: weights only, so leave room for the KV cache.

16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 0.9 GB of weights (estimate; KV cache and activations extra)INT40.9 GBFP8: about 1.7 GB of weights (estimate; KV cache and activations extra)FP81.7 GBBF16: about 3.4 GB of weights (estimate; KV cache and activations extra)BF163.4 GB
16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 0.9 GB of weights (estimate; KV cache and activations extra)INT40.9 GBFP8: about 1.7 GB of weights (estimate; KV cache and activations extra)FP81.7 GBBF16: about 3.4 GB of weights (estimate; KV cache and activations extra)BF163.4 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.

2 dated articles and 30 repo commits so far

Teal is the weights (2023-09-10), amber triangles are 2 dated articles (each links to it), grey ticks are repo commits.

JulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2025-11-24: 2 repo commits2024-04-29: 1 repo commit2024-04-23: 4 repo commits2024-04-17: 2 repo commits2024-02-06: 1 repo commit2024-01-24: 1 repo commit2024-01-22: 4 repo commits2024-01-16: 3 repo commits2024-01-12: 2 repo commits2024-01-11: 1 repo commit2024-01-10: 1 repo commit2024-01-09: 2 repo commits2024-01-08: 2 repo commits2024-01-05: 4 repo commitsPhi-1, a Compact Language Model, Outpaces GPT in Efficient Code Generation · 2023-06-22Ask HN: Is Microsoft's Phi-1 model available for testing somewhere? · 2023-06-27Weights 2023-09-10 · 2023-09-10Weights 2023-09-10now · 1 provider
JulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2025-11-24: 2 repo commits2024-04-29: 1 repo commit2024-04-23: 4 repo commits2024-04-17: 2 repo commits2024-02-06: 1 repo commit2024-01-24: 1 repo commit2024-01-22: 4 repo commits2024-01-16: 3 repo commits2024-01-12: 2 repo commits2024-01-11: 1 repo commit2024-01-10: 1 repo commit2024-01-09: 2 repo commits2024-01-08: 2 repo commits2024-01-05: 4 repo commitsPhi-1, a Compact Language Model, Outpaces GPT in Efficient Code Generation · 2023-06-22Ask HN: Is Microsoft's Phi-1 model available for testing somewhere? · 2023-06-27Weights 2023-09-10 · 2023-09-10Weights 2023-09-10now · 1 provider

What people built on it

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

22 derivatives on the Hub, led by 10 adapters

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

8 quantized (Hugging Face model tree)3 fine-tunes (Hugging Face model tree)1 merge (Hugging Face model tree)10 adapters (Hugging Face model tree)8 quantized3 fine-tunes1 merge10 adapters
8 quantized (Hugging Face model tree)3 fine-tunes (Hugging Face model tree)1 merge (Hugging Face model tree)10 adapters (Hugging Face model tree)8 quantized3 fine-tunes1 merge10 adapters

All variants →

Reference

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

What the card says

1 cited sentence

Summary generated, cited

Phi-1 is a 1.42B parameter Transformer model designed for basic Python coding.[1][2]

  1. parameters human
  2. “The language model Phi-1 is a Transformer”

Generated 2026-10-07 15:14 UTC by parasail-gemma-4-26b-a4b-it; each numeral points at the fact it rests on. Not a verdict.

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

22 fields

Listed in LLMs

Facts

Pipeline tagtext-generation
Librarytransformers
ArchitecturesPhiForCausalLM
Model typephi
Dtypefloat32
Params by dtypeF16: 1,418,270,720
Size bandS
MoEno
Context length2,048 (config.json max_position_embeddings)
Languagesen
PapersarXiv:2306.11644
LicenseMIT (mit)
Hub snapshot2026-10-25

Servability

vLLM · SGLang

Servability

vLLM: supported · PhiForCausalLM · 7050ef881ff0835f6890a47db1859a24c65481d6SGLang: supported · PhiForCausalLM · 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-1: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)3.4 GB · Edge (<4 GB)
FP8 (1 byte/param)1.7 GB · Edge (<4 GB)
INT4 (0.5 bytes/param)0.9 GB · Edge (<4 GB)

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

All variants

22 variants

Lineage

Original model Family: microsoft/phi-1 22 derivatives on the Hub

quantized: 8merge: 1finetune: 3adapter: 10

Top variants (22 shown, ranked by downloads)

Relation
Quant
22 rows
Variant Relation Quant Params Band License Author Likes Downloads
mradermacher/phi-1-i1-GGUF quantized GGUF — — mit mradermacher 0 3.6k
mradermacher/phi-1-GGUF quantized GGUF — — mit mradermacher 1 2.3k
professorf/phi-1-gguf quantized gguf — — mit professorf 1 1.7k
itlwas/phi-1-Q4_K_M-GGUF quantized GGUF — — mit itlwas 0 353
leliuga/phi-1-bnb-4bit quantized -bnb 1.46B S mit leliuga 0 280
Phudish/Test_Tam_2 merge — 1.53B S — Phudish 0 273
Merhabalad/phi-1-Q3_K_M-GGUF quantized GGUF — — mit Merhabalad 0 270
MatteoKhan/phi-1-1.5-merged finetune — 1.42B S mit MatteoKhan 0 161
Mayank-sharma108/phi-1-Q4_K_M-GGUF quantized GGUF — — mit Mayank-sharma108 0 135
Judiht/ludwigfinetuned_phi-1_testcase_generator_20k adapter — — — — Judiht 0 116
TheOSExplorer/phi-1-Q2_K-GGUF quantized Q2_K — — mit TheOSExplorer 0 114
kyryl-opens-ml/phi-1-duckdb-text-to-sql adapter — — — mit kyryl-opens-ml 0 40
rk68/phi-1-finetuned-aqua-rat-2k adapter — — — mit rk68 0 39
AKASH2393/phi1-lora-bilingual-ft adapter — — — — AKASH2393 0 39
rk68/phi-1-finetuned-aqua-rat-teacher-2k adapter — — — mit rk68 0 36
Judiht/finetuned_phi-1_testcase_generator_20k_v2 adapter — — — — Judiht 0 21
Judiht/finetuned_phi-1_testcase_generator_20k-lora adapter — — — — Judiht 0 19
Judiht/finetuned_phi-1_testcase_generator-lora adapter — — — — Judiht 0 15
Judiht/ludwigfinetuned_phi-1_testcase_generator_1k adapter — — — — Judiht 0 15
raghu60/phi1-lora-finetuned adapter — — — — raghu60 0 12
IyedLahiani/HTML_CSS_CodeGenerator finetune — — — — IyedLahiani 0 0
iravikr/phi1-numpy-pandas-qlora finetune — — — apache-2.0 iravikr 0 0

Repository changelog

30 commits

Repository changelog 30 commits

DateCommitSHA
2025-11-24 Update README.md (#15) d4c0adc
2025-11-24 Upload data_summary_card.md (#14) c542f61
2024-04-29 fix(config): Removes auto_map since it is not used anymore. b9ac0e6
2024-04-23 Update README.md cb3004d
2024-04-23 Delete modeling_phi.py 8399ff6
2024-04-23 Delete configuration_phi.py 8c83568
2024-04-23 Update README.md 92f2355
2024-04-17 Delete pytorch_model.bin 0c849e4
2024-04-17 Adding `safetensors` variant of this model (#9) b336aa7
2024-02-06 Update LICENSE a1a5931
2024-01-24 Update README.md ac0061a
2024-01-22 Update README.md ffff260
2024-01-22 Update README.md 2aef707
2024-01-22 Update README.md 64cc1d8
2024-01-22 Update config.json 0d846e0
2024-01-16 Update modeling_phi.py 944a013
2024-01-16 Update README.md fb32aac
2024-01-16 Update README.md 07d9363
2024-01-12 Update modeling_phi.py 03b9f69
2024-01-12 Update modeling_phi.py 54bed1a
2024-01-11 Update modeling_phi.py 50bb267
2024-01-10 Upload modeling_phi.py 2cfa65f
2024-01-09 Delete Research License.docx 957a783
2024-01-09 Upload 5 files 1cb0668
2024-01-08 Update config.json 3e53f58
2024-01-08 Update modeling_phi.py e575241
2024-01-05 Update modeling_phi.py 4e6ed66
2024-01-05 Update configuration_phi.py fbf395a
2024-01-05 fix(root): Fixes relative paths. b908838
2024-01-05 chore(root): Updates files to internal transformers implementation. 8a2c68b

All providers

1 provider · 1 endpoint

Where to run 1 providers · 1 endpoints

Hosted endpoints observed for phi-1, 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-1 — — — — — — — live 2026-10-25

Articles and coverage

2 pieces

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

Analysis1

mpost.io2023-06-22HN 1 pts · 0 comments

Community1

news.ycombinator.com2023-06-27HN 1 pts · 0 comments71 words

Papers

1 paper

Papers 1

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).

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3 models

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Sources

3 sources

Sources

Hub snapshot: 2026-10-25 · HF API: 2026-10-24 21:42 UTC · Providers: 2026-10-24 21:44 UTC · Articles: 2026-10-24 21:46 UTC · Summary: 2026-10-07 15:14 UTC · Last verified 2026-10-25

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