Hacker ApprovedDepartments

Locally AI by LM Studio

Shares rank 23 of 27 local LLM runners by recommenders

Free, uncluttered iPhone app with a wide range of local AI models and a link to desktop LM Studio. Some models are hidden in settings.

Free, uncluttered iPhone app with a wide range of local AI models and a link to desktop LM Studio. Some models are hidden in settings.

6 people gave an opinion

recommend it
5
criticize it
1
approval share
83%
Each figure is one person. RecommendsCriticizes

Recommended in 2 of 13 months

  1. November 2025: not recommended
  2. December 2025: not recommended
  3. January 2026: not recommended
  4. February 2026: not recommended
  5. March 2026: not recommended
  6. April 2026: recommended
  7. May 2026: not recommended
  8. June 2026: not recommended
  9. July 2026: not recommended
  10. August 2026: not recommended
  11. September 2026: not recommended
  12. October 2026: recommended
  13. November 2026: not recommended (month in progress)

Why it doesn’t carry the badge

  • 5 people recommend itNeeds 10 or more, not met.
  • 5 recommenders for every criticNeeds 2 to 1 or better, met.
  • Recommended in 2 of 13 monthsNeeds 4 or more, not met.

The same three rules apply to every product, and the badge can’t be bought. How the badge works

What people say about it

The reasons people give, with the number of comments that give each one. Open a reason to read what they said.

Why people recommend it

Each mark is one comment

  • Wide range of models

    “It's free, not annoying, and has a bunch of model options.”

    Comment from 17 Oct 2026 in “Qwen3.8-27B on the iPhone 18 Neural Engine at 15–70 tok/s (1.5 bpw)”

    “it’s really good and has a wide range of models”

    Comment from 6 Apr 2026 in “Gemma 4 on iPhone”
  • Free and not annoying

    “It's free, not annoying, and has a bunch of model options.”

    Comment from 17 Oct 2026 in “Qwen3.8-27B on the iPhone 18 Neural Engine at 15–70 tok/s (1.5 bpw)”
  • Links to desktop LM Studio

    “can link to the desktop LM Studio app which is cool”

    Comment from 17 Oct 2026 in “Qwen3.8-27B on the iPhone 18 Neural Engine at 15–70 tok/s (1.5 bpw)”

What people warn about

Each mark is one comment

  • Some models hidden in settings

    “the bonsai model doesn't present in the list. You have to get it via settings.”

    Comment from 1 Apr 2026 in “Show HN: 1-Bit Bonsai, the First Commercially Viable 1-Bit LLMs”
  • Refuses some requests

    “it would refuse to do so, at least from Locally AI”

    Comment from 17 Oct 2026 in “Qwen3.8-27B on the iPhone 18 Neural Engine at 15–70 tok/s (1.5 bpw)”

Other local LLM runners people recommend

The four most recommended other local LLM runners, with the same counts for each, so you can compare like for like. The tick on each bar marks the 2 to 1 line the badge needs.

Locally AI by LM Studio compared with 4 alternatives
ProductRecommendCriticizeApprovalMonthsOwnedBadge
llama.cpp47110981%131 yr4 ownersApproved
Ollama35024759%121.5 yrs8 owners—
LM Studio2177475%123 yrs4 ownersApproved
DS4 by antirez1092084%71 mo3 ownersApproved
Locally AI by LM StudioThis page5183%2——
See all 27 local LLM runners, ranked

What people said

5 of the 7 comments that mention it, newest first. Each links to the original comment.

“it would refuse to do so, at least from Locally AI”

CriticizesComment from 17 Oct 2026 in “Qwen3.8-27B on the iPhone 18 Neural Engine at 15–70 tok/s (1.5 bpw)”

“can link to the desktop LM Studio app which is cool”

RecommendsComment from 17 Oct 2026 in “Qwen3.8-27B on the iPhone 18 Neural Engine at 15–70 tok/s (1.5 bpw)”

“It's free, not annoying, and has a bunch of model options.”

RecommendsComment from 17 Oct 2026 in “Qwen3.8-27B on the iPhone 18 Neural Engine at 15–70 tok/s (1.5 bpw)”

“it’s really good and has a wide range of models”

RecommendsComment from 6 Apr 2026 in “Gemma 4 on iPhone”

“the bonsai model doesn't present in the list. You have to get it via settings.”

MixedComment from 1 Apr 2026 in “Show HN: 1-Bit Bonsai, the First Commercially Viable 1-Bit LLMs”

Counts come from 1,795,640 Hacker News comments, November 2025 to November 2026. How we count. Report a mistake.