
Little Friends: Puppy Island
Big Blue Bubble · Fireshine Games · 2023-06-27
Modes: Single player
Releases: Jun 27, 2023 (Nintendo Switch), Jun 27, 2023 (PC (Microsoft Windows))
Get ready for a pawsome puppy adventure in Little Friends: Puppy Island! Discover exciting locations, dig up hidden treasures, build and expand your holiday resort, and meet plenty of lovable little friends to care for on your very own un-paw-gettable, tropical island adventure!
Health check
- · 44 reviews in the last 8 weeks (~6/week).
- · Review velocity down 43% vs the prior 8 weeks.
- · Top 25% of 26,262 Adventure games in the census by review count.
Review-multiple estimate from 317 total reviews — how this is computed.
Current store prices
| WinGameStore | $3.99 | -90% |
| lowest across shops (ITAD) | $39.99 |
Deal snapshots via CheapShark, refreshed daily.
All-time low: $2.95 at GameBillet (2025-11-22) · bundled 2×via IsThereAnyDeal
12-month high $39.99 · on sale 56 of 95 observed days · $37.04 above the all-time low (census price snapshots)
Review momentum
Price history
Completion
- · 98.4% of players earned Pet The Dog
- · 42.7% of players earned Flower Power
- · 12.5% of players earned River Revealer
Global achievement rates from Steam.
Details
10 supported languages: English, French, Italian, German, Spanish - Spain, Japanese, Korean, Portuguese - Brazil, Simplified Chinese, Traditional Chinese
Console footprint
| Platform | Players tracked | Completion | Trophies/achievements |
|---|---|---|---|
| Steam (Steam) | 284 | 18% | 84 |
| Switch (Nintendo) | 61 | 0% | 0 |
Players tracked by Exophase (achievement/trophy trackers) — a sample of the player base, not total sales.
Player tags
3DDogCuteIndieCasualBuildingColorfulLife SimRelaxingAdventure
Census log
- 2023-06-01First review activity on record (week of 2023-06-01).
- 2025-07-01Biggest review week on record: 22 reviews (week of 2025-07-01).
Computed from census-recorded observations only — dates are observation dates.
Players also track
Dr. Cares - Amy's Pet ClinicAquarium Land
Similarity via IGDB.