Qwen2.5-14B
Hacker ApprovedShares rank 44 of 72 language models by recommenders
People recommend it for running locally on long data processing and pattern analysis, and it stays usable on modest hardware. The most common caveat is that it struggles with large projects.
People recommend it for running locally on long data processing and pattern analysis, and it stays usable on modest hardware. The most common caveat is that it struggles with large projects.
14 people gave an opinion
- recommend it
- 11
- criticize it
- 3
- approval share
- 79%
Recommended in 9 of 13 months
- November 2025: recommended
- December 2025: recommended
- January 2026: not recommended
- February 2026: recommended
- March 2026: recommended
- April 2026: recommended
- May 2026: not recommended
- June 2026: recommended
- July 2026: not recommended
- August 2026: recommended
- September 2026: recommended
- October 2026: recommended
- November 2026: not recommended (month in progress)
Why it carries the badge
- 11 people recommend itNeeds 10 or more, met.
- 3.7 recommenders for every criticNeeds 2 to 1 or better, met.
- Recommended in 9 of 13 monthsNeeds 4 or more, 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
Good for long-running local data work
“AnythingLLM + qwen2.5:14b is what I use — good for pattern recognition across metrics you wouldn't think to look for manually.”
Comment from 20 Mar 2026 in “Garmin data archive – local, offline, Ollama-ready” “Which is actually good enough for the long term data processing I make it spend all day doing.”
Comment from 13 Mar 2026 in “Can I Run AI locally?” Fast and low on RAM
“fast, reliable, low ram specs and most of the times fine on cpu”
Comment from 27 Feb 2026 in “Show HN: I built a local AI-powered Ouija board with a fine-tuned 3B model” “qwen2.5-14b runs a lot faster on my mini”
Comment from 17 Sep 2026 in “Reverse-engineered Jev-like model” Small sizes still give good results
“I use smaller models (qwen2.5:1.5b) with keyboard shortcuts and speech to text”
Comment from 10 Feb 2026 in “Eight More Months of Agents” “I liked the results even using the small Qwen2.5-0.5B model”
Comment from 14 Jun 2026 in “Show HN: RAIF – an experimental structured I/O format for LLMs” “qwen2.5:7b handles it fine”
Comment from 25 Aug 2026 in “Show HN: Voicecard – a CLI that resolves contradictions in rambling voice notes”
What people warn about
Each mark is one comment
Struggles with large projects
“I struggled with Qwens2.5-14b trying to do large projects”
Comment from 30 Jun 2026 in “Qwen 3.6 27B is the sweet spot for local development”
Other language models people recommend
The four most recommended other language models, 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.
| Product | Recommend | Criticize | Approval | Months | Owned | Badge |
|---|---|---|---|---|---|---|
| Claude Opus | 3,331 | 2,746 | 55% | 13 | 4 mo156 owners | — |
| OpenAI GPT | 1,205 | 987 | 55% | 13 | 6 mo47 owners | — |
| Claude Sonnet | 854 | 586 | 59% | 13 | 6 mo46 owners | — |
| DeepSeek V4 Flash | 828 | 223 | 79% | 8 | 1 mo24 owners | Approved |
| Qwen2.5-14BThis page | 11 | 3 | 79% | 9 | — | Approved |
What people said
13 of the 16 comments that mention it, newest first. Each links to the original comment.
“it was good for the purpose of answering people and keeping the dialog”
“qwen2.5-14b runs a lot faster on my mini”
“qwen2.5:7b handles it fine”
“I struggled with Qwens2.5-14b trying to do large projects”
“I liked the results even using the small Qwen2.5-0.5B model”
“AnythingLLM + qwen2.5:14b is what I use — good for pattern recognition across metrics you wouldn't think to look for manually.”
“Which is actually good enough for the long term data processing I make it spend all day doing.”
“fast, reliable, low ram specs and most of the times fine on cpu”
“Qwen2.5-14B on CPU as a slow fallback”
“1.5B models are not very bright which doesn't give me much hope for what they could "claw" or accomplish.”
“I use smaller models (qwen2.5:1.5b) with keyboard shortcuts and speech to text”
“modern local models are basically on par with cloud ones”
“it looks like it can create instant feedback loop”
Counts come from 1,795,640 Hacker News comments, November 2025 to November 2026. How we count. Report a mistake.