17th Aug 2026, 05:57 PM
Rao's Homemade Bucatini Pasta, 16 oz
Price may vary by location, shipping cost, and availability.
23% Off
$3.08
$3.99
Highest: $3.99
Average: $3.36
Lowest: $2.87
Price History Graph
Offer Price Prices
Lowest: -
Average: -
Highest: -
Price History Information
You can check the price history of Rao's Homemade Bucatini Pasta, 16 oz here. This product's current Price in USA is $3.08. The average and highest prices are $3.36 and $3.99 respectively.
| Lowest Ever Price | $2.87 |
|---|---|
| 11th Aug 2026 | |
| Average Price | $3.36 |
| Based on 30 days price tracking | |
| Highest Price | $3.99 |
| 23rd Jul 2026 | |
Price History of All Variants of Raos Homemade Bucatini Pasta 16 oz
Current Price in USA
| Price | $3.08 |
|---|---|
| MRP | $3.99 |
| Savings | $0.91 |
| Discount | 22.80% |
Recent Price Drops on Rao's Homemade Bucatini Pasta, 16 oz
Price Drop 10th Aug 2026
$3.10 → $2.87
7.42% drop
Price Drop 1st Aug 2026
$3.99 → $3.10
22.31% drop
Product Information
Details
| Product Name | Rao's Homemade Bucatini Pasta, 16 oz |
|---|---|
| Store Product Code | B0CRSSQWBC |
| Store Name | amazon.com |
| Rating | 9.4 / 10 |
| Category | Pasta |
Features
- Raos Homemade Bucatini is a long, tubular pasta with a perfect al dente texture and a delicious flavor that speaks for itself
- Bucatini pasta has a hole running through the center and pairs well with traditional Italian recipes like Carbonara and oil-based sauces
- Traditionally bronze die cut pasta that's dried slow and low
- Non-GMO Project Verified and made with just 2 ingredients: house-milled semolina flour and water
- Over 120 years in the making, Raos Homemade sets the standard for restaurantquality from the comfort of your home
Images
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Rating and Reviews
9.4 Based on 263 reviews
Raos Homemade Bucatini Pasta 16 oz has 9.4 rating out of 10. This average rating is consist of 263 individual ratings. You can rate this product at product review page.
* Predictions is created on based of past prices and trends, it does not guarantee that it will happen. These are just prediction for theoretical information only.