Novita AI
Hacker ApprovedShares rank 7 of 14 inference providers by recommenders
People recommend Novita as a cheap, fast, hosted API for open-weight models, with strict data retention and good cache hit rates. Critics say it serves quantized versions and doesn't test its models carefully.
People recommend Novita as a cheap, fast, hosted API for open-weight models, with strict data retention and good cache hit rates. Critics say it serves quantized versions and doesn't test its models carefully.
16 people gave an opinion
- recommend it
- 13
- criticize it
- 3
- approval share
- 81%
Recommended in 8 of 13 months
- November 2025: not recommended
- December 2025: not recommended
- January 2026: recommended
- February 2026: not recommended
- March 2026: recommended
- April 2026: not recommended
- May 2026: recommended
- June 2026: recommended
- July 2026: recommended
- August 2026: recommended
- September 2026: recommended
- October 2026: recommended
- November 2026: not recommended (month in progress)
Why it carries the badge
- 13 people recommend itNeeds 10 or more, met.
- 4.3 recommenders for every criticNeeds 2 to 1 or better, met.
- Recommended in 8 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
Cheap compared to other providers
“They are incredibly price competitive, have strict data retention policies, and in general are quite fast.”
Comment from 30 May 2026 in “Anthropic surpasses OpenAI to become most valuable AI startup” “You can pay the same $10 on Novita or with any other provider.”
Comment from 14 Sep 2026 in “Big AI sets out its terms for regulatory capture” “offer the exact same service for significantly less”
Comment from 15 Oct 2026 in “Things to know when you get cancer”
What people warn about
Each mark is one comment
Serves quantized model versions
“their main gig is serving quantized versions of the model to offer it for cheaper / at better latency”
Comment from 19 Jan 2026 in “GLM-4.7-Flash” Models not carefully tested
“they clearly don't spend much time on actually testing and configuring all of the models they provide”
Comment from 27 Jun 2026 in “The gap between open weights LLMs and closed source LLMs”
Other inference providers people recommend
The four most recommended other inference providers, 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 |
|---|---|---|---|---|---|---|
| Fireworks AI | 67 | 19 | 78% | 11 | — | Approved |
| DeepInfra | 36 | 11 | 77% | 11 | — | Approved |
| Together AI | 20 | 7 | 74% | 9 | — | Approved |
| fal.ai | 19 | 7 | 73% | 8 | — | Approved |
| Novita AIThis page | 13 | 3 | 81% | 8 | — | Approved |
What people said
12 of the 16 comments that mention it, newest first. Each links to the original comment.
“offer the exact same service for significantly less”
“didn't lead to major performance degradation for me”
“You can pay the same $10 on Novita or with any other provider.”
“For truly production use cases, use Novita, Fireworks, Toghether or something of the sort.”
“there are US based provider like Novita, Coreweave... that serve this specific Deepsek model and honor them”
“I find they usually have better cache hit rates than fireworks”
“they clearly don't spend much time on actually testing and configuring all of the models they provide”
“looks like NovitaAI would meet those criteria”
“They are incredibly price competitive, have strict data retention policies, and in general are quite fast.”
“qwen3 8b w/ novita being first place but barely”
“their main gig is serving quantized versions of the model to offer it for cheaper / at better latency”
“On NovitaAI with DS R1 it would cost you $0.7 * 403.2 + $2.5 * 126.7”
Counts come from 1,795,640 Hacker News comments, November 2025 to November 2026. How we count. Report a mistake.