Nemotron 3 Nano
Hacker ApprovedRanked 39 of 72 language models by recommenders
Fast open-weight model people find good at tool calling and code reading. Critics say it feels weak on real work.
Fast open-weight model people find good at tool calling and code reading. Critics say it feels weak on real work.
23 people gave an opinion
- recommend it
- 18
- criticize it
- 5
- approval share
- 78%
Recommended in 6 of 13 months
- November 2025: not recommended
- December 2025: recommended
- January 2026: recommended
- February 2026: recommended
- March 2026: recommended
- April 2026: recommended
- May 2026: not recommended
- June 2026: not recommended
- July 2026: recommended
- August 2026: not recommended
- September 2026: not recommended
- October 2026: not recommended
- November 2026: not recommended (month in progress)
Why it carries the badge
- 18 people recommend itNeeds 10 or more, met.
- 3.6 recommenders for every criticNeeds 2 to 1 or better, met.
- Recommended in 6 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
Fast responses on local hardware
“I have spent about five hours this week experimenting with Nemotron 3 nano for both tool use and code analysis: it is excellent! and fast!”
Comment from 18 Dec 2025 in “Gemini 3 Flash: Frontier intelligence built for speed” “It's extremely fast on good hardware, quite smart, and can support up to 1m context with reasonable accuracy”
Comment from 17 Dec 2025 in “Gemini 3 Flash: Frontier intelligence built for speed” “It is fast and passed all of my personal tool use tests, and did a good job analyzing code.”
Comment from 16 Dec 2025 in “Nvidia Nemotron 3 Family of Models” - Comment from 17 Dec 2025 in “Nvidia Nemotron 3 Family of Models”
Good tool calling and tool use
“I have spent about five hours this week experimenting with Nemotron 3 nano for both tool use and code analysis: it is excellent! and fast!”
Comment from 18 Dec 2025 in “Gemini 3 Flash: Frontier intelligence built for speed” “It is fast and passed all of my personal tool use tests, and did a good job analyzing code.”
Comment from 16 Dec 2025 in “Nvidia Nemotron 3 Family of Models” “It is very good with tool calling and works great with Roo Code for local development.”
Comment from 31 Jan 2026 in “The $100B Megadeal Between OpenAI and Nvidia Is on Ice” Good at understanding code
“I have spent about five hours this week experimenting with Nemotron 3 nano for both tool use and code analysis: it is excellent! and fast!”
Comment from 18 Dec 2025 in “Gemini 3 Flash: Frontier intelligence built for speed” “It is fast and passed all of my personal tool use tests, and did a good job analyzing code.”
Comment from 16 Dec 2025 in “Nvidia Nemotron 3 Family of Models” “It actually works quite well for general code comprehension across the whole codebase”
Comment from 2 Jan 2026 in “Dell's version of the DGX Spark fixes pain points” Runs in about 18GB RAM
“running it on my M4 @ 90tps, takes 18GB of RAM.”
Comment from 17 Dec 2025 in “Nvidia Nemotron 3 Family of Models” “~18Gb for Nemotron Nano 30b”
Comment from 11 Jan 2026 in “Building Voice Agents with Nvidia Open Models”
What people warn about
Each mark is one comment
Did not impress on real work
“I was not impressed with the latency or the recommended LLM’s quality.”
Comment from 25 Jan 2026 in “Building Voice Agents with Nvidia Open Models” “it doesn't really show for the kind of work I throw at it”
Comment from 19 Jan 2026 in “GLM-4.7-Flash” “There was basically no time period for it to shine.”
Comment from 31 Jan 2026 in “The $100B Megadeal Between OpenAI and Nvidia Is on Ice”
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 |
| Nemotron 3 NanoThis page | 18 | 5 | 78% | 6 | — | Approved |
What people said
25 of the 27 comments that mention it, newest first. Each links to the original comment.
“I think these vanilla models are capable enough to add real value”
“NVIDIA-Nemotron-3-Nano-4B which is the best 4B model I've found”
“intelligence dense Nemotron 3 Nano 30B and Nemotron Cascade 2 30B models”
“Qwen3-next, Qwen3.5, and Nemotron 3 Nano are all great examples.”
“its tool use was seriously lacking”
“My locally running nemotron-3-nano quantized to Q4_K_M gets this right.”
“for Qwen3-Coder-next, Qwen3-30B-A3B, Nemotron-3-Nano, GLM-4.7-Flash etc.”
“Seems to underperform GLM 4.7 Flash though (according to benchmarks)”
“is just about as capable if not better”
“There was basically no time period for it to shine.”
“It is very good with tool calling and works great with Roo Code for local development.”
“I was not impressed with the latency or the recommended LLM’s quality.”
“nemotron-3-nano:30b ( good general purpose)”
“it doesn't really show for the kind of work I throw at it”
“Qwen3-Next and Nemotron 3 Nano are solid players in their respective local weight classes”
“~18Gb for Nemotron Nano 30b”
“It actually works quite well for general code comprehension across the whole codebase”
“That's been one of the biggest wow moments I had with LLMs so far.”
“I have spent about five hours this week experimenting with Nemotron 3 nano for both tool use and code analysis: it is excellent! and fast!”
“It's extremely fast on good hardware, quite smart, and can support up to 1m context with reasonable accuracy”
“it doesn't even fit on a RTX 5090”
“running it on my M4 @ 90tps, takes 18GB of RAM.”
“It is fast and passed all of my personal tool use tests, and did a good job analyzing code.”
“I love how detailed and transparent the data set statistics are on the huggingface pages”
“this looks like it has great potential for cost-effectiveness”
Counts come from 1,795,640 Hacker News comments, November 2025 to November 2026. How we count. Report a mistake.