Models › Janus family

deepseek-ai MIT (deepseek) out 21 months ago

Several kinds of input and output.

Verified 2026-10-25 Rank #375 in LLMs · score 80.3 method v1 Sources 3 Downloads 30d 2.8k · #569 of 619 tracked

Changed this week: 1 new quantized build on the Hub (7 in all).2026-10-24

Can I use it?MIT (deepseek)Permissivelicence file2026-10-24
Do people use it?2.8kdownloads, 30 days#569 of 619 we track · below the median+6 likes, downloads −3% this week506 likesHugging Face2026-10-24

Worth reading

Picked by rule from 6 tracked pieces: the lab's own post, the most shared, a field report, the latest.

Latest · 24 days ago

Show HN: Janus – Go binary that runs GGUF models via Vulkan on AMD/Intel/Nvidia

Janus is a single Go binary that runs .gguf models on your machine and exposes an OpenAI-compatible API.

  • The build script pins llama.cpp to version b11146 because internal struct layouts match that specific tag.
  • On Windows, Go cannot overwrite a running executable, requiring the process to be stopped in Task Manager before rebuilding.
github.com 2026-10-01 106 HN pts · 19 comments 774 words about the Janus family family

6 best of 6 tracked

The 3 picks above, plus these 3. Top is the radar's score: discussion, source authority and the lab's own posts, fading with age.

  1. CodeJanus: Decoupling visual encoding for multimodal understanding and generationgithub.com · 2024-10-20 · 36 HN pts
  2. ArticleProject Janus: Now Open Sourcetechcommunity.microsoft.com · 2025-03-26 · 4 HN pts
  3. ArticleShow HN: DeepSeek Janus Pro 7B APIeachlabs.ai · 2025-01-28 · 6 HN pts

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.

No API provider serves it, so its downloads are people running it themselves: 7 quantized builds and 11 Spaces.

  • As a service0no API provider listed
  • On own hardware7quantized builds
  • Built on128 fine-tunes · 4 adapters · 0 merges
  • In apps11Hugging Face Spaces

Top Spaces running it: afrideva/Janus-Pro-1b ♥ 21

The story so far

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

Coverage peaked at launch and is still arriving

Teal is the weights (2025-01-26), amber triangles are 6 dated articles (each links to it), grey ticks are repo commits.

What people built on it

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

19 derivatives on the Hub, led by 8 fine-tunes

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

7 quantized (Hugging Face model tree)8 fine-tunes (Hugging Face model tree)4 adapters (Hugging Face model tree)7 quantized8 fine-tunes4 adapters
7 quantized (Hugging Face model tree)8 fine-tunes (Hugging Face model tree)4 adapters (Hugging Face model tree)7 quantized8 fine-tunes4 adapters

All variants →

Reference

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

What the card says

1 cited sentence

Summary generated, cited

The framework unifies multimodal understanding and generation by decoupling visual encoding into separate pathways.[1]

  1. “unifies multimodal understanding and generation”

Generated 2026-10-07 15:10 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

15 fields

Listed in LLMs

Facts

Pipeline tagany-to-any
Librarytransformers
ArchitecturesMultiModalityCausalLM
Model typemulti_modality
Dtypebfloat16
MoEno
PapersarXiv:2501.17811
LicenseMIT (deepseek) (mit)
Hub snapshot2026-10-25

Servability

vLLM · SGLang

Servability

vLLM: not in registry · 7050ef881ff0835f6890a47db1859a24c65481d6SGLang: not in registry · 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.

All variants

19 variants

Lineage

Original model Family: deepseek-ai/Janus 19 derivatives on the Hub

quantized: 7finetune: 8adapter: 4

Top variants (19 shown, ranked by downloads)

Relation
Quant
Size
19 rows
Variant Relation Quant Params Band License Author Likes Downloads
onnx-community/Janus-Pro-1B-ONNX quantized — — — mit onnx-community 51 65.2k
wnma3mz/Janus-Pro-1B-4bit quantized -4bit 2.09B M mit wnma3mz 4 1.6k
kiel2/Kiel-2-Omni finetune — 2.09B M mit kiel2 1 1.6k
kiel2/Kiel-2.1-Omni finetune — 2.09B M — kiel2 1 1.5k
wnma3mz/Janus-Pro-1B finetune — 2.09B M mit wnma3mz 0 438
AXERA-TECH/Janus-Pro-1B quantized — — — mit AXERA-TECH 2 292
wnma3mz/Janus-Pro-1B-LM-4bit quantized -4bit 1.65B S mit wnma3mz 0 273
wnma3mz/Janus-Pro-1B-LM finetune — 1.65B S mit wnma3mz 3 120
RKNNAI/RK182X-VLM-Janus-Pro-1B quantized GGUF — — other RKNNAI 0 147
zeromodels/janus_pro_1b finetune — — — mit zeromodels 0 139
zghhui/Janus-Pro-1B-GCPO-Geneval finetune — 2.09B M — zghhui 0 88
LemOneLabs/Janus-Pro-1B-ONNX quantized — — — mit LemOneLabs 0 57
zghhui/Janus-Pro-1B-GCPO-HPS finetune — 2.09B M — zghhui 0 49
Branis333/Janus_Grade adapter — — — — Branis333 0 49
zghhui/Janus-Pro-7B-GCPO-Geneval finetune — 7.42B M — zghhui 0 36
Branis333/Janus_grade_final adapter — — — — Branis333 0 35
gauravparajuli/deepseekJanusPro1bms-swift123 adapter — — — — gauravparajuli 0 30
gauravparajuli/Janus-Pro-1B-Kvasir-LoRA_test adapter — — — — gauravparajuli 0 23
SkyContact/Janus-Pro-1B-GGUF quantized GGUF — — mit SkyContact 0 0

Repository changelog

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

Repository changelog 5 commits

DateCommitSHA
2025-02-01 Update README.md 960ab33
2025-01-27 Update README.md 8db7a90
2025-01-27 update README 8da01df
2025-01-27 upload ckpt ffcf344
2025-01-26 initial commit e47d37d

Articles and coverage

6 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.

Official1

techcommunity.microsoft.com2025-03-26authorityabout the Janus familyHN 4 pts · 1 comments8,243 words
Microsoft open-sourced Project Janus on Feb 27, 2025, to optimize O-RAN networks with dynamic service models and real-time telemetry. The release includes the jbpf library and jrt-controller, enabling control at microsecond time scales and access to fine-grained L1 telemetry. Previously announced at MWC 2024, the framework supports anomaly detection, interference mitigation, and fast vRAN power savings.written, reviewed, cited
  • Project Janus enables adding new functionality to operational RAN deployments without causing service disruption.
  • The framework allows developers to exert control over RAN behavior at microsecond time scales.
  • Project Janus allows real-time dynamic access to L1 telemetry, letting the telemetry type be controlled based on future AI use cases.

Analysis4

github.com2026-10-01authorityHN front pageabout the Janus familyHN 106 pts · 19 comments774 words
Janus is a single Go binary that runs .gguf models on your machine and exposes an OpenAI-compatible API. It requires Go 1.25+ and supports local inference via Vulkan or CPU fallback without requiring Python, Docker, or Ollama. The build script pins llama.cpp b11146, and the server listens on port 8990 under an MIT license.written, reviewed, cited
  • The build script pins llama.cpp to version b11146 because internal struct layouts match that specific tag.
  • On Windows, Go cannot overwrite a running executable, requiring the process to be stopped in Task Manager before rebuilding.
  • The first reply often takes 10–60 seconds because the model is loading into VRAM during startup.
github.com2025-01-27authorityHN front pageabout the Janus familyHN 912 pts · 674 comments
github.com2024-10-20authorityabout the Janus familyHN 36 pts · 3 comments2,112 words
DeepSeek released Janus-Pro on January 27, 2025, as an advanced version of Janus that improves multimodal understanding and visual generation. The model incorporates optimized training strategies, expanded training data, and scaling to larger model sizes to achieve significant advancements. JanusFlow, released on November 13, 2024, introduces a minimalist architecture integrating autoregressive language models with rectified flow for image generation. All models support a sequence length of 4096 and are available on Hugging Face.written, reviewed, cited
  • A tokenizer configuration bug previously prevented classifier-free guidance from functioning properly, degrading visual generation quality.
  • The generation pipeline requires setting a classifier-free guidance weight of 5 to achieve the intended image synthesis results.
  • Engineers must set the image token count per image to 576 and the image size to 384 pixels during the generation process.
eachlabs.ai2025-01-28about the Janus familyHN 6 pts · 2 comments

Community1

old.reddit.com2025-01-28HN front pageHN 214 pts · 22 comments

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).

Similar models

3 models

Similar models

Sources

3 sources

Sources

Hub snapshot: 2026-10-25 · HF API: 2026-10-24 21:39 UTC · Providers: 2026-10-24 21:44 UTC · Articles: 2026-10-24 21:46 UTC · Summary: 2026-10-07 15:10 UTC · Last verified 2026-10-25

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