The latency cost of hosting an API in India
Comments on “The latency cost of hosting an API in India”
Claim-checked. Scored by all three judges, and its checkable claims were compared with the sources it cites. How far stories are checked
Latencyradar.com compared daily response times from its Mumbai and San Francisco servers across 20 services, through 20 October 2026. Many API-style services were slower from Mumbai: ChatGPT's API started answering 398 ms later, and crates.io took 1,555 ms against 445 ms. Package registries such as PyPI and jsDelivr showed no gap. The site attributes the delay to CDN edges forwarding requests to distant origins, an explanation it doesn't source. Its advice is to reuse connections, cache, and set timeouts from Mumbai's own numbers. Both test servers sit in data centres.
Why it ranked
No. 13 of 107 with a score of 0.65. The panel rated it highest on new information (0.91) and substantiated (0.84), lowest on significance (0.47). Placed No. 13, No. 23 by score alone: the placement terms moved other stories past it.
- AI judgeJudge 2claude-haiku-5-5
- Measured benchmark of API latency from Mumbai versus San Francisco with clear methodology and caveats; useful for infra and deployment decisions, though a niche measurement with limited broad significance.
- AI judgeJudge 3gpt-5.6-luna
- A measured comparison of Mumbai and San Francisco latency across major APIs and registries, with methodology, causal explanation, tail data, and concrete deployment guidance. It is highly actionable, though geographically focused rather than field-defining.
Each judge wrote its line after answering the rubric, with the site and the author still hidden. Every answer behind this is in the table under Score.
Score
0.65total under rubric v2.3
- Significance0.47
- Reader interest0.71
- Audience breadth0.60
- Practical relevance0.81
- Substantiated0.84
- Technical depth0.75
- New information0.91
- Counts against: Promotional0.08
- Counts against: Overclaim0.16
Each judge’s answer per question (0–1), their mean and spread, and what the question adds to the score (weight × mean).
| Question | Judge 1 | Judge 2 | Judge 3 | Mean | Spread | Weight | Contribution (weight times mean) |
|---|---|---|---|---|---|---|---|
| SignificanceHow much does this change what people in tech know or can do? | 0.55 | 0.30 | 0.55 | 0.47 | 0.25 | +0.24 | +0.112 |
| Reader interestWould a well-informed senior engineer or tech founder want to read this today, and likely pass it on? | 0.68 | 0.60 | 0.86 | 0.71 | 0.26 | +0.26 | +0.185 |
| Audience breadthHow many people who build technology does it concern? | 0.71 | 0.50 | 0.58 | 0.60 | 0.21 | +0.13 | +0.078 |
| Practical relevanceHow useful is it to someone who builds software or tech products? | 0.91 | 0.70 | 0.82 | 0.81 | 0.21 | +0.22 | +0.178 |
| SubstantiatedHow well is it backed? Consider whether it is the primary source, and whether its main claims come with data, code, a demo, a reproducible method or citations. | 0.93 | 0.70 | 0.90 | 0.84 | 0.23 | +0.05 | +0.042 |
| Technical depthHow technically substantive is it? | 0.86 | 0.70 | 0.68 | 0.75 | 0.18 | +0.05 | +0.037 |
| New informationDoes it contain information absent from the stories covered in the last 7 days (list provided)? | 0.90 | 0.85 | 0.98 | 0.91 | 0.13 | +0.05 | +0.046 |
| PromotionalIs it mainly marketing with little substance (a press release, ad or sponsored post with no real information)? A launch post that carries real news is not promotional. | 0.04 | 0.20 | 0.01 | 0.08 | 0.19 | −0.19 | −0.016 |
| OverclaimDo the headline or conclusions claim more than the body supports? | 0.18 | 0.25 | 0.04 | 0.16 | 0.21 | −0.11 | −0.017 |
| Sum of contributions | +0.646 | ||||||
| Claim-check penalty | 0.000 | ||||||
| Total, as published | 0.646 | ||||||
Spread is the highest minus the lowest judge answer. marks a spread above 0.40: the judges disagree, and the story is marked contested.
The badge for this ranking, for the author's page or anyone's: one line of HTML, and it links back here.
<a href="https://rubric.hrih.si/editions/2026-11-03/13/"><img src="https://rubric.hrih.si/badge/2026-11-03/13.svg" alt="Ranked #13 on Rubric, 3 Nov 2026" width="238" height="28"></a>Claim check
Claim check: 4 matches source · 3 no source given · 1 couldn’t check. Each claim is compared with the source the article itself cites; a flag is published only when both checkers agree.
Matches sourceNumber
The ChatGPT API takes 1,326 ms to start answering from Mumbai versus 928 ms from San Francisco, a 398 ms extra wait.
The cited source says the same thing.
The article says “ChatGPT API * +398 ms 1,326 ms 928 ms”
The source says “San Francisco | 928 ms | 1517 ms | 65”
Source cited by the article: latencyradar.com/latency/chatgpt
Couldn’t checkFirst, only or fastest
crates.io has the largest gap between Mumbai (1,555 ms) and San Francisco (445 ms), an extra 1,110 ms.
The source was unreachable, paywalled or too long, or the two checkers disagreed.
The article says “crates.io has the largest gap, and size is the reason”
The source says No passage could be compared.
Source cited by the article: latencyradar.com/latency/crates-io
No source givenNumber
DeepSeek API starts answering 139 ms sooner from Mumbai than from San Francisco, and Mistral just as soon.
The article gives no link or citation for it.
The article says “DeepSeek starts 139 ms sooner there than in San Francisco, and Mistral just as soon”
The source says No source to compare with.
Matches sourceNumber
For Stripe's API from Mumbai, connecting took 63 ms, the secure connection 66 ms and the wait 61 ms, versus 22 to 27 ms per step from San Francisco.
The cited source says the same thing.
The article says “From Mumbai, connecting took 63 ms, the secure connection 66 ms and the wait 61 ms”
The source says “Reaching the server 63 ms Setting up security: most of the time 66 ms Waiting for the server 61 ms”
Source cited by the article: latencyradar.com/latency/stripe-api
Matches sourceNumber
From Mumbai, 5% of requests to Coinbase's exchange API took longer than 809 ms, against 109 ms from San Francisco.
The cited source says the same thing.
The article says “From Mumbai, 5% of requests to Coinbase's exchange API took longer than 809 ms, against 109 ms from San Francisco”
The source says “Mumbai | 225 ms | 809 ms | 65”
Source cited by the article: latencyradar.com/latency/coinbase-exchange
No source givenNumber
For 11 of the 12 slower services, Mumbai reached a server in 2 or 3 ms and set up the secure connection in under 12 ms, as quickly as San Francisco.
The article gives no link or citation for it.
The article says “For 11 of the 12 slower services, Mumbai reached a server in 2 or 3 ms and set up the secure connection in under 12 ms”
The source says No source to compare with.
No source givenCausal conclusion
The nearby server belongs to the service's CDN and passes each request on to the service's own servers, which are closer to San Francisco than Mumbai.
The article gives no link or citation for it.
The article says “It doesn't hold the answer, so it passes each request on to the service's own servers, which are closer to San Francisco than to Mumbai”
The source says No source to compare with.
Matches sourceNumber
PyPI and crates.io both sit behind Fastly, and from Mumbai one took 11 ms and the other 1,555 ms.
The cited source says the same thing.
The article says “PyPI and crates.io both sit behind Fastly, and from Mumbai one took 11 ms and the other 1,555 ms”
The source says “Mumbai | 11 ms | 13 ms | 65”
Source cited by the article: latencyradar.com/latency/pypi
Also covered by
No other coverage was clustered with this story.
Elsewhere
Elsewhere: HN 3 pts, not on front page
Recorded for context only, checked 3 Nov 2026, 05:47 UTC. It played no part in the ranking.