# 🇩🇪 Frankfurt Ping & Network Latency (FRA) | AS203314

## 🇩🇪 Frankfurt (FRA)

Frankfurt is Europe's financial center and home to DE-CIX, the world's second-largest Internet Exchange. This PoP anchors Hats Network's dense European fiber ring.

Measurement round: `2026-08-16T04:07:28Z`.

This page provides round-trip time (RTT) latency metrics between the **Frankfurt (FRA)** PoP and every other node on the Hats Network (AS203314) global backbone.

### PoP Highlights

* **Location:** Frankfurt, Germany (Europe)
* **Region:** Europe
* **Role:** Backbone interconnection point for Hats Network (AS203314)
* **Public city reference:** [GeoNames 2925533](https://www.geonames.org/2925533) — 50.11552, 8.68417
* **Coverage:** RTT measurements to 19 other PoPs across 5 continents

### Facility & Interconnection

* **Facility:** FRA1

> Interactive content is available on the canonical HTML page.

### Latency Summary

| Metric                | Value                                                                                                           |
| --------------------- | --------------------------------------------------------------------------------------------------------------- |
| Fastest Route         | [🇩🇪 Frankfurt (FRA) → 🇳🇱 Amsterdam (AMS)](/docs/network/latency/pairs/fra-ams-rtt) (**5.9 ms**) — Ultra-Low |
| Slowest Route         | [🇩🇪 Frankfurt (FRA) → 🇦🇺 Sydney (SYD)](/docs/network/latency/pairs/fra-syd-rtt) (**256 ms**)                |
| Average RTT           | **114.0 ms**                                                                                                    |
| Average Jitter        | **0.95 ms**                                                                                                     |
| Average Packet Loss   | **0.05%**                                                                                                       |
| Best Fiber Efficiency | **81.9%**                                                                                                       |
| Intra-Region Peers    | 6 PoPs in Europe                                                                                                |
| Total Routes          | 19 outbound / 19 inbound (100% coverage)                                                                        |

> Jitter, packet-loss, percentile, and trend fields are estimated comparative indicators. Read the [theoretical fiber latency methodology](/docs/network/latency/theoretical-fiber-latency).

## Geographic & Network Position

Frankfurt sits on Hats Network's **Europe** backbone. Measured round-trip times to its 6 intra-region peers range from **5.9 ms** (Amsterdam (AMS)) to **34.7 ms** (Moscow (MOW)).

Frankfurt is the central switching point of the European fiber ring and home to DE-CIX, one of the world's largest Internet Exchanges.

## Outbound Latency from Frankfurt (FRA)

Round-trip time in milliseconds **from Frankfurt** to all other backbone PoPs, sorted fastest to slowest.

| Destination             | RTT (ms)                                             | Fiber Floor | Efficiency | Jitter  | Loss  | Tier      |
| ----------------------- | ---------------------------------------------------- | ----------- | ---------- | ------- | ----- | --------- |
| 🇳🇱 Amsterdam (AMS)    | **[5.9](/docs/network/latency/pairs/fra-ams-rtt)**   | 3.57 ms     | 60.6%      | 0.12 ms | 0%    | Ultra-Low |
| 🇩🇪 Berlin (BER)       | **[6.1](/docs/network/latency/pairs/fra-ber-rtt)**   | 4.16 ms     | 68.2%      | 0.12 ms | 0%    | Ultra-Low |
| 🇫🇷 Paris (PAR)        | **[7.6](/docs/network/latency/pairs/fra-par-rtt)**   | 4.7 ms      | 61.8%      | 0.12 ms | 0%    | Ultra-Low |
| 🇬🇧 London (LON)       | **[12.9](/docs/network/latency/pairs/fra-lon-rtt)**  | 6.26 ms     | 48.5%      | 0.12 ms | 0%    | Ultra-Low |
| 🇫🇷 Marseille (MRS)    | **[16.4](/docs/network/latency/pairs/fra-mrs-rtt)**  | 7.82 ms     | 47.7%      | 0.19 ms | 0%    | Ultra-Low |
| 🇷🇺 Moscow (MOW)       | **[34.7](/docs/network/latency/pairs/fra-mow-rtt)**  | 19.85 ms    | 57.2%      | 0.25 ms | 0.13% | Excellent |
| 🇺🇸 New York (NYC)     | **[74.4](/docs/network/latency/pairs/fra-nyc-rtt)**  | 60.9 ms     | 81.9%      | 0.73 ms | 0%    | Excellent |
| 🇺🇸 Ashburn (IAD)      | **[80.7](/docs/network/latency/pairs/fra-iad-rtt)**  | 64.3 ms     | 79.7%      | 0.91 ms | 0.04% | Good      |
| 🇺🇸 Miami (MIA)        | **[112](/docs/network/latency/pairs/fra-mia-rtt)**   | 76.17 ms    | 68%        | 1.27 ms | 0.07% | Good      |
| 🇺🇸 Seattle (SEA)      | **[135.2](/docs/network/latency/pairs/fra-sea-rtt)** | 80.34 ms    | 59.4%      | 0.98 ms | 0.16% | Good      |
| 🇺🇸 Los Angeles (LAX)  | **[141.8](/docs/network/latency/pairs/fra-lax-rtt)** | 91.31 ms    | 64.4%      | 1.06 ms | 0%    | Good      |
| 🇸🇬 Singapore (SIN)    | **[151.4](/docs/network/latency/pairs/fra-sin-rtt)** | 100.56 ms   | 66.4%      | 0.7 ms  | 0%    | Fair      |
| 🇭🇰 Hong Kong (HKG)    | **[152](/docs/network/latency/pairs/fra-hkg-rtt)**   | 89.87 ms    | 59.1%      | 1.18 ms | 0%    | Fair      |
| 🇹🇼 Taipei (TPE)       | **[163.8](/docs/network/latency/pairs/fra-tpe-rtt)** | 91.96 ms    | 56.1%      | 1.28 ms | 0.04% | Fair      |
| 🇧🇷 São Paulo (GRU)    | **[181.3](/docs/network/latency/pairs/fra-gru-rtt)** | 96.04 ms    | 53%        | 2.02 ms | 0.04% | Fair      |
| 🇿🇦 Johannesburg (JNB) | **[188.4](/docs/network/latency/pairs/fra-jnb-rtt)** | 84.87 ms    | 45%        | 1.61 ms | 0.1%  | Fair      |
| 🇯🇵 Tokyo (TYO)        | **[194.5](/docs/network/latency/pairs/fra-tyo-rtt)** | 91.61 ms    | 47.1%      | 1.29 ms | 0.12% | Fair      |
| 🇦🇺 Melbourne (MEL)    | **[250.1](/docs/network/latency/pairs/fra-mel-rtt)** | 159.77 ms   | 63.9%      | 2.57 ms | 0%    | High      |
| 🇦🇺 Sydney (SYD)       | **[256](/docs/network/latency/pairs/fra-syd-rtt)**   | 161.37 ms   | 63%        | 1.5 ms  | 0.16% | High      |

## Fastest Routes to Frankfurt (FRA)

The 10 fastest measured routes **to Frankfurt**, ranked by average RTT. Min / max / stdev are computed from the same measurement round (50 ICMP echo probes per route, 100 ms interval); routes without a published per-sample round show the measured average RTT only.

| Rank | Source               | Avg RTT                                                 | Min       | Max       | Stdev   |
| ---- | -------------------- | ------------------------------------------------------- | --------- | --------- | ------- |
| 1    | 🇳🇱 Amsterdam (AMS) | **[5.9 ms](/docs/network/latency/pairs/ams-fra-rtt)**   | 5.67 ms   | 7.15 ms   | 0.23 ms |
| 2    | 🇩🇪 Berlin (BER)    | **[6.1 ms](/docs/network/latency/pairs/ber-fra-rtt)**   | 5.9 ms    | 6.73 ms   | 0.18 ms |
| 3    | 🇫🇷 Paris (PAR)     | **[7.6 ms](/docs/network/latency/pairs/par-fra-rtt)**   | 7.35 ms   | 8.42 ms   | 0.22 ms |
| 4    | 🇬🇧 London (LON)    | **[13.6 ms](/docs/network/latency/pairs/lon-fra-rtt)**  | 13.18 ms  | 15.43 ms  | 0.42 ms |
| 5    | 🇫🇷 Marseille (MRS) | **[16 ms](/docs/network/latency/pairs/mrs-fra-rtt)**    | 15.12 ms  | 18.91 ms  | 0.79 ms |
| 6    | 🇷🇺 Moscow (MOW)    | **[35.9 ms](/docs/network/latency/pairs/mow-fra-rtt)**  | 33.56 ms  | 42.93 ms  | 1.78 ms |
| 7    | 🇺🇸 New York (NYC)  | **[73.9 ms](/docs/network/latency/pairs/nyc-fra-rtt)**  | 71.94 ms  | 81.47 ms  | 1.98 ms |
| 8    | 🇺🇸 Ashburn (IAD)   | **[81.2 ms](/docs/network/latency/pairs/iad-fra-rtt)**  | 79.1 ms   | 86.57 ms  | 1.81 ms |
| 9    | 🇺🇸 Miami (MIA)     | **[112.2 ms](/docs/network/latency/pairs/mia-fra-rtt)** | 108.19 ms | 121.5 ms  | 3.61 ms |
| 10   | 🇺🇸 Seattle (SEA)   | **[133.2 ms](/docs/network/latency/pairs/sea-fra-rtt)** | 130.2 ms  | 141.75 ms | 2.72 ms |

## Inbound Latency to Frankfurt (FRA)

Round-trip time in milliseconds **from all other PoPs to Frankfurt**. Network paths may be asymmetric — inbound and outbound RTT can differ for the same city pair.

| Source                  | RTT (ms)                                             | Fiber Floor | Efficiency | Jitter  | Loss  | Tier      |
| ----------------------- | ---------------------------------------------------- | ----------- | ---------- | ------- | ----- | --------- |
| 🇳🇱 Amsterdam (AMS)    | **[5.9](/docs/network/latency/pairs/ams-fra-rtt)**   | 3.57 ms     | 60.6%      | 0.12 ms | 0.05% | Ultra-Low |
| 🇩🇪 Berlin (BER)       | **[6.1](/docs/network/latency/pairs/ber-fra-rtt)**   | 4.16 ms     | 68.2%      | 0.12 ms | 0%    | Ultra-Low |
| 🇫🇷 Paris (PAR)        | **[7.6](/docs/network/latency/pairs/par-fra-rtt)**   | 4.7 ms      | 61.8%      | 0.12 ms | 0.1%  | Ultra-Low |
| 🇬🇧 London (LON)       | **[13.6](/docs/network/latency/pairs/lon-fra-rtt)**  | 6.26 ms     | 46.1%      | 0.12 ms | 0.03% | Ultra-Low |
| 🇫🇷 Marseille (MRS)    | **[16](/docs/network/latency/pairs/mrs-fra-rtt)**    | 7.82 ms     | 48.9%      | 0.18 ms | 0.15% | Ultra-Low |
| 🇷🇺 Moscow (MOW)       | **[35.9](/docs/network/latency/pairs/mow-fra-rtt)**  | 19.85 ms    | 55.3%      | 0.3 ms  | 0%    | Excellent |
| 🇺🇸 New York (NYC)     | **[73.9](/docs/network/latency/pairs/nyc-fra-rtt)**  | 60.9 ms     | 82.4%      | 0.74 ms | 0.09% | Excellent |
| 🇺🇸 Ashburn (IAD)      | **[81.2](/docs/network/latency/pairs/iad-fra-rtt)**  | 64.3 ms     | 79.2%      | 0.95 ms | 0.1%  | Good      |
| 🇺🇸 Miami (MIA)        | **[112.2](/docs/network/latency/pairs/mia-fra-rtt)** | 76.17 ms    | 67.9%      | 0.83 ms | 0.06% | Good      |
| 🇺🇸 Seattle (SEA)      | **[133.2](/docs/network/latency/pairs/sea-fra-rtt)** | 80.34 ms    | 60.3%      | 0.66 ms | 0.11% | Good      |
| 🇺🇸 Los Angeles (LAX)  | **[142.3](/docs/network/latency/pairs/lax-fra-rtt)** | 91.31 ms    | 64.2%      | 0.71 ms | 0%    | Good      |
| 🇭🇰 Hong Kong (HKG)    | **[150.7](/docs/network/latency/pairs/hkg-fra-rtt)** | 89.87 ms    | 59.6%      | 1.66 ms | 0%    | Fair      |
| 🇸🇬 Singapore (SIN)    | **[151.6](/docs/network/latency/pairs/sin-fra-rtt)** | 100.56 ms   | 66.3%      | 0.77 ms | 0.04% | Fair      |
| 🇹🇼 Taipei (TPE)       | **[166](/docs/network/latency/pairs/tpe-fra-rtt)**   | 91.96 ms    | 55.4%      | 1.67 ms | 0.13% | Fair      |
| 🇿🇦 Johannesburg (JNB) | **[166](/docs/network/latency/pairs/jnb-fra-rtt)**   | 84.87 ms    | 51.1%      | 1.86 ms | 0.11% | Fair      |
| 🇧🇷 São Paulo (GRU)    | **[186.2](/docs/network/latency/pairs/gru-fra-rtt)** | 96.04 ms    | 51.6%      | 2 ms    | 0%    | Fair      |
| 🇯🇵 Tokyo (TYO)        | **[193.2](/docs/network/latency/pairs/tyo-fra-rtt)** | 91.61 ms    | 47.4%      | 2.16 ms | 0%    | Fair      |
| 🇦🇺 Melbourne (MEL)    | **[248.6](/docs/network/latency/pairs/mel-fra-rtt)** | 159.77 ms   | 64.3%      | 2.09 ms | 0.16% | Fair      |
| 🇦🇺 Sydney (SYD)       | **[254.4](/docs/network/latency/pairs/syd-fra-rtt)** | 161.37 ms   | 63.4%      | 2.54 ms | 0%    | High      |

## Europe Peers

Frankfurt is one of 7 Hats Network PoPs in **Europe**. Intra-region routes offer the lowest latency and highest path diversity.

| PoP                                     | Code | Country     | RTT (ms) | Tier      |
| --------------------------------------- | ---- | ----------- | -------- | --------- |
| [🇳🇱 Amsterdam (AMS)](./ams-amsterdam) | AMS  | Netherlands | **5.9**  | Ultra-Low |
| [🇩🇪 Berlin (BER)](./ber-berlin)       | BER  | Germany     | **6.1**  | Ultra-Low |
| [🇬🇧 London (LON)](./lon-london)       | LON  | UK          | **12.9** | Ultra-Low |
| [🇫🇷 Marseille (MRS)](./mrs-marseille) | MRS  | France      | **16.4** | Ultra-Low |
| [🇷🇺 Moscow (MOW)](./mow-moscow)       | MOW  | Russia      | **34.7** | Excellent |
| [🇫🇷 Paris (PAR)](./par-paris)         | PAR  | France      | **7.6**  | Ultra-Low |

## Frequently Asked Questions

**What is the fastest route to Frankfurt?**

The fastest measured route to Frankfurt (FRA) is [Amsterdam (AMS) → Frankfurt (FRA)](/docs/network/latency/pairs/ams-fra-rtt), averaging **5.9 ms** RTT (Ultra-Low).

**What is the fastest route from Frankfurt?**

The fastest measured route from Frankfurt (FRA) is [Frankfurt (FRA) → Amsterdam (AMS)](/docs/network/latency/pairs/fra-ams-rtt), averaging **5.9 ms** RTT (Ultra-Low).

**How well connected is Frankfurt to the Hats Network backbone?**

Frankfurt (FRA) maintains measured routes to all 19 other PoPs across 5 continents. The slowest route, [Frankfurt (FRA) → Sydney (SYD)](/docs/network/latency/pairs/fra-syd-rtt), averages **256 ms** RTT.

## Open Data

Measured latency data for Frankfurt (FRA) is published daily under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) as part of the Hats Network open latency dataset:

* **Per-route files** — every directed route from Frankfurt is published as `fra-<destination>.pings.{csv,json,yaml}` under [`/opendata/latency/latest/pairs/`](/opendata/latency/latest/pairs/) — for example [fra-ams.pings.csv](/opendata/latency/latest/pairs/fra-ams.pings.csv), the 50-probe ICMP echo round for [Frankfurt (FRA) → Amsterdam (AMS)](/docs/network/latency/pairs/fra-ams-rtt).
* **Dataset documentation** — [/opendata/latency/](/opendata/latency/) covers file formats, versioning, checksums, and the aggregated full-matrix releases.

***

*Data auto-generated on August 16, 2026. Explore the [full interactive latency matrix](/docs/network/latency) for side-by-side comparison across all 20 PoPs.*

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## License and attribution

- **Canonical source:** [View the human-readable HTML page](https://hatsnet.io/docs/network/latency/fra-frankfurt).
- **Original documentation:** © Hats Network Inc., licensed under [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/).
- **Public latency data:** © Hats Network Inc., licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
- **Full terms:** [Content and Data License](https://hatsnet.io/docs/legal/content-and-data-license) — includes attribution requirements, third-party material, trademarks, source code and other exclusions.