Fluidstack
기업 솔루션 · 101.4K 월 방문
Fluidstack은 최첨단 AI 모델의 훈련 및 서비스를 위한 고성능 전용 GPU 클러스터를 제공하는 선도적인 AI 클라우드 플랫폼입니다. 수천 개의 GPU를 신속하게 배포하고, 24/7 전문가 지원을 포함한 완전 관리형 서비스를 제공하며, 데이터 전송 비용이 없는 투명한 가격 정책으로 AI 팀이 인프라 문제 없이 확장할 수 있도록 지원합니다.
제품 개요
Fluidstack 제품 개요
Fluidstack은 최첨단 AI 모델의 훈련 및 서비스를 위한 고성능 전용 GPU 클러스터를 제공하는 선도적인 AI 클라우드 플랫폼입니다. 수천 개의 GPU를 신속하게 배포하고, 24/7 전문가 지원을 포함한 완전 관리형 서비스를 제공하며, 데이터 전송 비용이 없는 투명한 가격 정책으로 AI 팀이 인프라 문제 없이 확장할 수 있도록 지원합니다.
Preview
Unsloth 제품 개요
Unsloth는 대규모 언어 모델(LLM)의 파인튜닝을 획기적으로 가속화하기 위해 설계된 고성능 오픈소스 라이브러리입니다. 최대 30배 빠른 훈련 속도와 90% 적은 메모리 사용량을 제공하여 표준 하드웨어에서도 고급 AI 모델 커스터마이징을 가능하게 합니다.
Preview
Detailed feature comparison
| Feature | Fluidstack | Unsloth |
|---|---|---|
| 주요 카테고리 | 기업 솔루션 | 머신러닝 |
| 등록일 | 2025-08-09 | 2025-08-06 |
| 가격 | 유료 | 프리미엄 |
| 공식 사이트 | www.fluidstack.io | unsloth.ai |
| 제품 유형 | 웹사이트 | 웹사이트 |
| Performance data | ||
| 사용자 평점 | 확인되지 않음 | 확인되지 않음 |
| 댓글 | 0 | 0 |
| 월 방문 | 101.4K | 1.1M |
| 월 성장률 | 0.4% | -31.3% |
| 즐겨찾기 | 95 | 89 |
| Details | 상세 보기 | 상세 보기 |
Fluidstack vs Unsloth monthly traffic
Compare Fluidstack and Unsloth by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the Fluidstack vs Unsloth monthly traffic comparison, Fluidstack currently shows 101.4K visits and Unsloth shows 1.1M; Unsloth has about 10.6 times the visible traffic of Fluidstack, an absolute difference of about 976.6K visits. This reflects visible reach, not feature quality or paid users.
Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.
Fluidstack monthly traffic:
Latest traffic
월 방문
101.4K
평균 방문 시간
1:06
방문당 페이지
2.58
이탈률
39.33%
Data updated 2026-06-11
Monthly traffic trend
- 2025/9: 28.9K 월 방문
- 2026/1: 91.6K 월 방문
- 2026/2: 69.4K 월 방문
- 2026/3: 95.5K 월 방문
- 2026/4: 101K 월 방문
- 2026/5: 101.4K 월 방문
주요 지역
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 87.31% | 88.5K |
| 🇬🇧United Kingdom | 6.99% | 7.1K |
| 🇮🇳India | 2.34% | 2.4K |
| 🇨🇦Canada | 1.75% | 1.8K |
| 🇻🇳Vietnam | 1.61% | 1.6K |
트래픽 소스
| Source type | Percentage | Traffic |
|---|---|---|
| 직접 | 77.86% | 79K |
| 리퍼럴 | 16.42% | 16.7K |
| 이메일 | 5.72% | 5.8K |
검색 키워드
fluid stackfluidstackfluidstack careersfluidstack jobsfluidstack technical program manager, deployments
Unsloth monthly traffic:
Latest traffic
월 방문
1.1M
평균 방문 시간
2:08
방문당 페이지
3.04
이탈률
48.11%
Data updated 2026-06-15
Monthly traffic trend
- 2025/9: 426.2K 월 방문
- 2026/1: 574.8K 월 방문
- 2026/2: 698.3K 월 방문
- 2026/3: 1.3M 월 방문
- 2026/4: 1.6M 월 방문
- 2026/5: 1.1M 월 방문
주요 지역
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇨🇳China | 43.4% | 467.8K |
| 🇺🇸United States | 30.21% | 325.7K |
| 🇮🇳India | 11.41% | 123K |
| 🇰🇷Korea, Republic of | 7.88% | 84.9K |
| 🇩🇪Germany | 7.1% | 76.5K |
트래픽 소스
| Source type | Percentage | Traffic |
|---|---|---|
| 직접 | 64.94% | 700K |
| 리퍼럴 | 34.01% | 366.6K |
| 이메일 | 1.05% | 11.3K |
검색 키워드
kimi k2.6qwen3.5unslothunsloth aiunsloth studio
Traffic-based selection guidance: If public market visibility is an important first-pass criterion, investigate Unsloth first. The final choice should still follow taxonomy, use case, and a real trial because higher traffic does not prove broader capabilities or better workflow fit.
Usage comparison
Compare the core capabilities of Fluidstack and Unsloth
Fluidstack Core features
머신러닝
클라우드 컴퓨팅
기업 솔루션
Unsloth Core features
머신러닝
클라우드 컴퓨팅
코드 어시스턴트
Use cases
Fluidstack Use cases
딥러닝
기계 학습
모델 학습
AI 인프라
B200
클라우드 컴퓨팅
기업 AI
GPU 클라우드
H100
고성능 컴퓨팅
추론
Unsloth Use cases
딥러닝
기계 학습
모델 학습
AI 개발자
미세 조정
GPU 최적화
라마
대규모 언어 모델
LoRA
메모리 효율성
미스트랄
오픈 소스
성능
Fluidstack vs Unsloth：In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth Fluidstack vs Unsloth comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. Fluidstack is primarily listed under “기업 솔루션”, while Unsloth is primarily listed under “머신러닝”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Primary category (Fluidstack: 기업 솔루션; Unsloth: 머신러닝); Pricing (Fluidstack: Paid; Unsloth: Freemium); Monthly visits (Fluidstack: 101.4K; Unsloth: 1.1M); Monthly growth (Fluidstack: 0.4%; Unsloth: -31.3%); Favorites (Fluidstack: 95; Unsloth: 89). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the Fluidstack vs Unsloth monthly traffic comparison, Fluidstack currently shows 101.4K visits and Unsloth shows 1.1M; Unsloth has about 10.6 times the visible traffic of Fluidstack, an absolute difference of about 976.6K visits. This reflects visible reach, not feature quality or paid users.
Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.
If public market visibility is an important first-pass criterion, investigate Unsloth first. The final choice should still follow taxonomy, use case, and a real trial because higher traffic does not prove broader capabilities or better workflow fit.
Product positioning, use cases, and roles
Fluidstack and Unsloth currently overlap in shared categories: 머신러닝 및 클라우드 컴퓨팅; shared tags: 딥러닝, 기계 학습 및 모델 학습. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
Fluidstack's unique categories/tags are 기업 솔루션, AI 인프라, B200, 클라우드 컴퓨팅, 기업 AI, GPU 클라우드, H100 및 고성능 컴퓨팅; Unsloth's are 코드 어시스턴트, AI 개발자, 미세 조정, GPU 최적화, 라마, 대규모 언어 모델, LoRA 및 메모리 효율성. These unique fields are the strongest differentiators: validate the product whose recorded scope matches the task instead of following traffic alone.
What ratings, comments, and favorites can tell you
Fluidstack has no verified rating, 0 comments, 95 favorites, and 92 likes；Unsloth has no verified rating, 0 comments, 89 favorites, and 95 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate Fluidstack first
Put Fluidstack on the priority trial list when the task aligns with “기업 솔루션” and especially 기업 솔루션, AI 인프라, B200, 클라우드 컴퓨팅, 기업 AI 및 GPU 클라우드. This follows recorded positioning and does not imply unlisted capabilities are absent.
Fluidstack also currently records: pricing is paid, product type is website, 101.4K verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
When to evaluate Unsloth first
Put Unsloth on the priority trial list when the task aligns with “머신러닝” and especially 코드 어시스턴트, AI 개발자, 미세 조정, GPU 최적화, 라마 및 대규모 언어 모델. This follows recorded positioning and does not imply unlisted capabilities are absent.
Unsloth also currently records: pricing is freemium, product type is website, 1.1M verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
How to validate the recommendation before deciding
The available data describes positioning, public visibility, and community signals, but it cannot prove output quality, speed, integration effort, privacy, or long-term cost in your workflow. Before deciding, run the same representative tasks in Fluidstack and Unsloth, then record completion time, accuracy, manual corrections, and the real paid threshold. A like-for-like trial turns this comparison into a defensible adoption decision.
비교 FAQ
How should I choose between Fluidstack and Unsloth?
Compare positioning, pricing, taxonomy, and traffic maturity, then verify the latest details on each official website.
Where does this comparison data come from?
The factual baseline is derived from product, taxonomy, traffic, and community data. Reviewed editorial conclusions show their source and verification date.
What do unknown fields mean?
Unknown means there is not enough reliable evidence; the page does not fill gaps with assumptions.