One person, 300k "A vs B" pages: how BenchLM catches search for every new model, weekly
What it is A site that aggregates public benchmark scores from each lab, ranks LLMs, and auto-generates a comparison page for every pair of models.
Why it took off In 2026, new models ship every week, and searches like "A vs B" and "which is best at coding" keep climbing. It uses templates to build about 300k comparison pages with real data. Niche pairings have a ready-made page only because of it, and its transparent methodology makes people and AI willing to cite it.
BHow you could follow it Stop building LLM leaderboards. Carry the template (many entities × pairwise comparisons × honest handling of missing data) over to a category where entities keep multiplying and nobody has filled the space yet, such as AI coding tools, generative APIs, or GPU cloud pricing. Get traffic from search and AI citations, then add an API and ads once traffic builds.
Global rank 129k · 90 days ago 393k
BenchLM (benchlm.ai) is an LLM leaderboard built by one person. It doesn't run evals itself. It pulls together each lab's public scores, pairs up 1,000 models two by two, and generates a comparison page for each pair, about 300k pages in total. Its global rank rose 3x in 90 days, and its founder self-reports 1.11M pageviews in September. The play has already been dissected and labeled "copyable," so the real question is which category to apply it to, not whether to build yet another LLM leaderboard.
One search
On Nov 6, I searched "gpt-6 vs claude opus 5.5" in Brave. The first result was DataCamp's long-form article. The second was benchlm.ai/compare/claude-opus-5-5-vs-gpt-6-astra, ahead of Artificial Analysis, MindStudio, and Tom's Guide. DataCamp's piece was written by an editor. Nobody wrote the BenchLM page. The template generated it: a summary at the top, then a price table and category scores, then a verdict for "coding," "agents," and "long documents."
I tried a pair nobody searches for: moshi-7b-vs-ultravox-v0-7, two niche voice models. The page still exists, and it's refreshingly honest: "There is no shared benchmark between these two models in public data, so we can't judge which is better." Every row is marked "insufficient evidence." Almost nobody will read this page, but across 300k pages there are enough obscure pairings that they add up to real traffic.
What it is and who made it
An indie developer named Glevd (on X as @glevd, self-described as Guillaume; I couldn't find other background) launched it in August 2025. The about page is blunt: "BenchLM does not run private evaluations." Data comes from model cards, launch announcements, public leaderboards, and papers. It computes an overall score with its own algorithm called BenchAlign (now at v5.8, with weights and calibration method published), ranks 212 models, and covers 1,016 models and 758 benchmarks. Each ranking is tagged "Supported" (enough evidence) or "Estimated." Benchmarks that are already saturated, like SWE-bench Verified, are displayed but not scored.
How much it grew
| Timeline | Global ranking (Tranco) | Pageviews it self-reports (GA4) | Pages on the site |
|---|---|---|---|
| End of July | About 450k people | About 509k a week in 4 | About 73k (howtodistribute, July stats) |
| August | 390k people | 791,237 (August 1–28) | — |
| September | 240k people | 1,115,214 (September 1–28, up 40.9% month over month) | — |
| Early November | 129k people (11-05) | — | About 309k (sitemap, November) |
In Chrome's real-user data (CrUX), its global tier went from the top 1M in June to the top 500k by September 7. Australia, Canada, Turkey, and Vietnam have already entered the top 100k locally. Its rank has kept climbing over the last 7 days (133k to 129k), with no sign of a ceiling yet.
The pageview figure is self-reported on its advertising page, /advertise, which is aimed at recruiting advertisers, so treat it as a rough number. Notably, page count and traffic grew together: over 3 to 4 months, pages went from just over 70k to just over 300k, and pageviews went from 500k to 1.1M.
Where users come from: almost all search
- Pairwise comparison pages are the main driver. Pairing 1,000 models two by two gives about 500k combinations in theory, and it has built about 300k of them. Each time a new model launches, the template adds several hundred new pages automatically, without anyone writing a word.
- Other entry points pick up more search terms. There are 1,017 model pages, 764 benchmark pages, 77 use-case pages under /best/ (coding, long context, Chinese models, local deployment, and more), and over 14 /alternatives/ pages targeting searches like "Artificial Analysis alternative" and "llm-stats alternative." Page titles update to the current month automatically, e.g. "LLM Leaderboard — November 2026." In early November, it ranked #5 on Brave for "llm leaderboard" and #5 for "best llm for coding 2026."
- It works to get AI and other sites to cite it. It has an llms.txt, structured data on its pages, and a repeatable citation asset, the "BenchLM Token Price Index." People on Reddit already quote its price index and rankings verbatim. The awesome-llm-bench repo on GitHub syncs its top 10 daily and calls it "the most honest, most frequently updated aggregator."
- Embeds bring in backlinks. /embed generates a leaderboard iframe with a "by BenchLM.ai" link built in. Data downloads are under a CC BY-NC license that requires attribution with a link back. How many backlinks this actually brings in is unverified.
- The newsletter keeps people. Its Beehiiv subscriber count was 25 in October at 6,100 thousand people, and 3,439 at the end of August.
- What I couldn't find: Almost no one has mentioned it on X in the last 120 days. There's no launch record on Product Hunt or Hacker News, and no sign of paid promotion. howtodistribute's breakdown concludes it rests on a single channel.
Why now
Over 2026, the labs have released new versions almost every week: GPT-6.x, Claude 5.x, Gemini 4, Kimi K3. Each release adds a new batch of "X vs Y" and "which is best at coding" searches, and these queries have a short shelf life, too fast for editors to keep up. BenchLM's template is built for this demand: the more entities there are, the more pages there are, and the faster entities update, the further human-written competitors fall behind.
Page count alone isn't enough. In 2026, Google cracked down hard on thin content, and BenchLM survived because every page carries real scores, prices, and sources. Where data is missing, it writes "Not measured" instead of inventing a conclusion. Its public methodology and labeling of evidence strength built a reputation for honesty, which is why people and AI are willing to cite it.
Where the money comes from
The site lists these, but how much they actually earn is unknown:
- Data API: 250 free calls per month, Pro at $49/month, Research at $249/month. The page says "700+ users" without saying whether that means signups or paying customers. There's also MCP access and commercial licensing.
- Ad sales: site placements, newsletter placements, and "publishing packages" with articles. The advertising page says "booking December placements."
- Affiliate: the site includes a disclosure statement.
It isn't listed on revenue-disclosure platforms like TrustMRR, so revenue isn't public. Based on 1.1M monthly pageviews and one person running it, ads plus API probably cover a solo operator's living, but the exact figure can only be estimated and is not visible from outside.
Who's competing
This category is crowded. The top players have their own data, and BenchLM doesn't.
| Competitors | Rank (Tranco, 11-05) | How it differs from BenchLM |
|---|---|---|
| LMArena(arena.ai) | 6,798 | Blind user voting from a funded team; BenchLM uses it as one data source |
| Artificial Analysis | 18,624 (90 days ago, 40,649) | Runs its own evals and measures speed and pricing; the industry's de facto standard |
| OpenRouter Rankings | 3,850 (the whole openrouter.ai domain) | Ranks by real API call volume, not scores |
| llm-stats.com | 126,685 (90 days ago, 158,671) | The closest play. Its rank is now almost identical to BenchLM's, but it rose only about 1.25x in 90 days, and it has far fewer pages |
| Leaderboard pages from Vellum and onyx.app | 157k / 142k (whole domain) | SaaS companies using leaderboards as content marketing; narrow coverage |
| benchleader, benchmarklist, theaggregate, whatllm | None in the top 1M | Copycat sites that appeared in 2026 |
A breakdown already exists: howtodistribute.com published "How BenchLM got its users" in July, labeled "COPYABLE: you can start next Monday, no budget, no audience, no one's approval needed." Four or five copycat sites have followed, and none have taken off yet.
If it were you
B. The play is worth learning, but don't build another LLM leaderboard. The top of this market has its own eval data, BenchLM already built 300k pages first, and the play has been publicly dissected, with copycats going nowhere. What's worth taking is the method: many entities × pairwise comparisons × honest templates, applied to a category where new entities keep appearing and people keep arguing, but nobody has filled the space yet.
- Who it's for: someone who can write a scraper, build a static site, and can wait 6 to 12 months before it compounds. Best if you already know a category and where to pull data, and the data is tedious enough that others won't bother (that tedium is your moat).
- Who it's not for: anyone who needs income within three months; anyone with no data source they can re-scrape on a schedule, planning to fill pages with AI-written content (2026-year thin content gets whole sites demoted); anyone who wants to build LLM benchmarks head-on against BenchLM and Artificial Analysis.
- How to do it: list your entities first, compute n×(n−1)/2, and only build comparison pages if the ceiling clears several thousand. Candidate areas: AI coding tools and agents, voice/image/video generation API pricing and quality, GPU cloud price quotes, mobile plans or broadband in one country, a category of SaaS. The template must render a full page even for the coldest pair, with "No data yet" where data is missing. Add /best/{use-case}, /alternatives/{competitor}, and a calculator or two. Nonexistent URLs must return a real 404; BenchLM gets this wrong (howtodistribute notes it returns 200 for made-up URLs).
- How to get traffic: search first, with sitemap and structured data set up before launch. Build a citable index (e.g. a "X price index"), ship an llms.txt, and go after AI search citations. Embeddable widgets with attribution terms earn backlinks. Put a newsletter signup on every page from day one. Open the API and sell ads only once traffic passes a few hundred thousand views a month.
- When to start: there's no hard deadline, but it gets harder the longer you wait. Pick a category that appeared this year and whose entity count is still growing every month, and move before SaaS content-marketing pages fill it. Ideally live before Q1 2027, with long-tail clicks by mid-year.
- What it looks like when you've misread the signal: ① BenchLM's Tranco rank drops back past 300k at the start of 2027, or its /advertise page stops updating traffic numbers: Google is cracking down on programmatic comparison pages, and this play is on the decline; ② Less than a tenth of your indexed pages get clicks 3 months after launch: the category you picked doesn't have enough "A vs B" searches; ③ Google or the major AI search tools start showing model comparison tables right on the results page: aggregator sites in the middle get skipped.
A last note for anyone building products: when a category has so many "things" that no one can write them all by hand, and they change every week, first count how many pairs there are, then check who has already built how many pages.
Research notes: competitor table, acquisition evidence, full research report
- Competitors
Name Where Launched Scale How it differs from this one LMArena / arena.ai Web 2023 arena.ai Tranco 6,798 User blind-vote Elo, run by a funded team; BenchLM treats it as one data source Artificial Analysis Web 2024 Tranco 18,624, CrUX global top 50k Runs its own evals, and tests speed and price too; BenchLM mirrors its index and built alternatives pages to capture its traffic OpenRouter Rankings Big-company features 2023 openrouter.ai Tranco 3,850 Ranks by real API usage, not benchmark scores Epoch AI Benchmarking Hub Web 2024 Tranco 43,550 Research lab, runs its own evals llm-stats.com Web 2024 Tranco 126,685 (90 days ago 158,671) Closest in strategy, but fewer pages and weaker methodology; up only about 1.25x in 90 days Vellum LLM Leaderboard Web 2023 vellum.ai Tranco 156,975 SaaS companies use the leaderboard as a lead magnet; narrow coverage onyx.app LLM leaderboard Web 2025-26 onyx.app Tranco 142,391 A SaaS content-marketing page, competing for the same best-for keywords on Brave Search; no large-scale pairwise comparison pages LiveBench Open source 2024 Tranco 322,937 Makes its own contamination-proof questions; a single benchmark only - Where users come from
- Verified Programmatic SEO (pairwise comparison pages, model pages, benchmark pages, best pages, alternatives pages): the sitemap has about 309,481 URLs, of which about 300k are /compare/ (about 73k as of July); self-reported 58.3K Google clicks over 28 days in July; on Brave, "llm leaderboard" ranks #5 and "gpt-6 vs claude opus 5.5" ranks #2
- Verified Competitor-capture pages: over 14 pages exist, including /alternatives/artificialanalysis, /alternatives/llm-stats, /alternatives/lmarena
- Verified Going after AI citations / GEO: has llms.txt and Dataset JSON-LD, and publishes citable BenchLM Stats and a Token Price Index; people quote it verbatim on Reddit; parse.gl has a dedicated page and Baidu Baike has an entry
- Inferred Embeds traded for backlinks: the /embed iframe carries an attribution link, and the data is under CC BY-NC, which requires attribution; actual backlink volume unverified
- Verified Organic community citations: r/ClaudeAI, r/GithubCopilot and others post it as evidence; awesome-llm-bench syncs its Top 10 from it daily
- Verified Newsletter retention: Beehiiv subscribers 6,100+ (2026-10-25), up more than 77% since late August
- Inferred X / HN / PH / paid acquisition: none found: x-radar shows 0 posts, and our PH, HN and ad libraries have nothing on it; howtodistribute also says it can't see any paid spend
BenchLM (benchlm.ai): how it works
Channel: web (C2; it doesn't appear in any of our other databases). Research date 2026-11-07.
One line
BenchLM is an LLM benchmark aggregator launched in August 2025 by indie developer Glevd (X account @glevd, who goes by Guillaume). It doesn't run evals itself. It collects scores from model cards, public leaderboards and papers, and uses its own BenchAlign (now v5.8) to compute an overall score and rank 212 models, covering 1016 models and 758 benchmarks. It works mainly through programmatic SEO: pairing "Model A vs Model B" in every combination, it generated about 300k comparison pages in one go, then added model pages, benchmark pages, /best/ and /alternatives/ pages to catch a long tail of searches. 2026 has had a very dense run of model releases, and searches like "X vs Y" and "best LLM for coding" keep rising. It caught that wave.
1. Data: how big it is and how fast it's growing
- Tranco (traffic DB, rank_day): 2026-07-30 was ranked 449,242; 08-06 was 393,003,09-03; 242,159,10-01 was 189,549,11-05; 129,426 ... Over 90 days it rose about ×3.0 and hasn't peaked (in the last 7 days it climbed from 132,766 to 129,426).
- CrUX (traffic library crux_domain): the global tier 2026-06 is the top 1M; 07 to September it's the top 500k; 2026-09 AU, CA, and TR climbed into the top 100k, and VN had already reached the top 100k in August; JP went from the top 1M to the top 500k; US, GB, DE, and FR went from the top 1M to the top 500k as of May.
- Traffic it reports itself (https://benchlm.ai/advertise, its ad sales page):
- GA4 logged 1,115,214 views from 2026-09-01 to 09-28, versus 791,237 the same period last month, +40.9% month over month;
- model pages got at least 122,266 views and comparison pages at least 90,311;
- Beehiiv subscribers 6,100+ (2026-10-25), up more than 77% from 3,439 at the end of August.
- Earlier self-reported numbers (howtodistribute.com/benchlm quoting the /advertise page at the time): 4K views in the 2026-07-25 weeks to 509.4; 58.3K Google clicks in the 28 days to 2026-07-06.
- Page scale: We counted its sitemap on 2026-11-07. Across 32 shards there are about 309,481 URLs, including roughly 300k /compare/ head-to-head pages, plus 1017 model pages, 764 benchmark pages, 240 vendor pages, 77 best-of pages and 103 blog posts. howtodistribute's count from around July was 73,149 URLs (72,019 of them compare pages). So the page count grew about 4x over 3 to 4 months, and traffic climbed alongside it.
- Where the traffic is: web only. We found no app and no Chrome extension.
2. Competitors (doing the same thing)
All Tranco ranks come from the traffic DB 2026-11-05; the figure in parentheses is the rank 90 days ago.
| Product | Form | Launched | Scale | How it differs from BenchLM |
|---|---|---|---|---|
| LMArena / arena.ai | Web | 2023(Chatbot Arena) | arena.ai 6,798(13,220);lmarena.ai 65,148 | User blind votes and its own Elo, from a funded team; BenchLM treats it as one data source |
| Artificial Analysis | Web | 2024 | 18,624 (40,649), CrUX global top 50k | Runs its own evals, and tests speed and price too; it's the industry reference. BenchLM mirrors its Intelligence Index and built a dedicated /alternatives/artificialanalysis page to capture its traffic |
| OpenRouter Rankings | Web (big-vendor-grade features) | 2023 | openrouter.ai 3,850 | Ranks by real API usage, not benchmark scores |
| Epoch AI Benchmarking Hub | Web | 2024 | 43,550 | Research lab, runs its own evals |
| Scale Labs leaderboard | Web | 2024 | scale.com 27,236 | Private expert evals (SEAL); BenchLM mirrors some of its boards |
| llm-stats.com | Web | 2024 | 126,685 (158,671), CrUX global top 500k | Closest rival: also an aggregator plus comparison pages, with nearly the same rank as BenchLM now, but only up about 1.25x in 90 days. BenchLM has /alternatives/llm-stats to capture its traffic |
| Vellum LLM Leaderboard | Web (SaaS content marketing) | 2023 | vellum.ai 156,975 | SaaS companies use the leaderboard as a lead magnet; narrow coverage |
| onyx.app/llm-leaderboard | Web (SaaS content marketing) | 2025–26 | onyx.app 142,391 | Also running "best LLM for X" SEO pages, competing with BenchLM for the same keywords on Brave Search |
| LiveBench | Web / open source | 2024 | 322,937(571,926) | Builds its own contamination-proof questions, academic background |
| HF Open LLM Leaderboard, Aider, SWE-bench, tbench and other single-task boards | Open source / web | 2023–25 | aider.chat 88,818;swebench.com 147,456 | Each covers one benchmark; BenchLM aggregates them |
| whatllm.org, benchleader.com, benchmarklist.com, theaggregate.ai | Web | 2026 | The last three aren't in Tranco's top 1M | Copycat aggregators; see section 5 |
Bottom line: this space is crowded. The leaders (Arena, Artificial Analysis) have teams and their own evaluation data. BenchLM has no data of its own; its play is aggregation plus page count.
3. Growth tactics (where users come from)
- Programmatic SEO (confirmed, the main engine): about 300k /compare/{a}-vs-{b} pages, each with a verdict, a price table and per-category scores, with "Not measured" written honestly where data is missing. There are also 1017 model pages, 764 benchmark pages, /best/{use-case} pages (coding, long-context, chinese-models, local-llm...), 14+ /alternatives/{competitor} pages (artificialanalysis, llm-stats, lmarena, chatgpt, claude, openclaw...), plus calculators under /tools/.
- Evidence: sitemap counts; howtodistribute's breakdown concludes that this one channel carries the site, with no paid spend visible; on Brave Search it ranks #5 for "llm leaderboard", #2 for "gpt-6 vs claude opus 5.5", and #5 for "best llm for coding 2026" (2026-11-07 checked).
- The self-reported page data fits too: model pages and comparison pages account for most of the views.
- Page titles automatically carry the current month every month, e.g. "LLM Leaderboard & AI Model Benchmarks — November 2026", to capture timely "2026 / this month" queries.
- Grabbing AI citations / GEO (confirmed): has llms.txt; pages carry Dataset JSON-LD; 2026-07 launched BenchLM Stats, built specifically as "citable data points", e.g. the "BenchLM Token Price Index". Reddit users already quote the data verbatim (an r/AskReddit thread cites the Token Price Index; r/hermesagent cites its ranking of MiniMax M2.7); parse.gl has a dedicated page, "What AI says about BenchLM"; even the English edition of Baidu Baike has an entry for it.
- Embed widget for backlinks (mechanism confirmed, how many backlinks it brings unverified): /embed generates an iframe leaderboard with a built-in "LLM benchmark leaderboard by BenchLM.ai" anchor-text backlink below it. Data downloads are under CC BY-NC, which requires attribution and a link back.
- Organic mentions in communities (confirmed, sporadic): comments in r/ClaudeAI, r/GithubCopilot and r/elasticsearch have people posting benchlm.ai as evidence; GitHub has leoncuhk/awesome-llm-bench, which syncs the Top 10 daily from benchlm.ai and calls it "the most honest, most frequently updated aggregator"; tomrochette.com and lossless.group also list it.
- Email newsletter to retain people (confirmed): Beehiiv, 6,100+ subscribers, up 77% over two months, used to turn one-time search visitors into repeat readers.
- X, HN, PH cold start: no evidence found. x-radar searched "benchlm" over the last 120 days and found 0 posts; our PH and HN databases don't have it either (C2). Founder @glevd's X bio reads "Building @BenchLM_AI", but I haven't seen any big-account repost that caused a spike.
- Paid acquisition: none found. It's C2; it isn't in the ad libraries, and howtodistribute also says "No paid distribution visible".
4. Why it took off
- Demand is rising: over the past 2026 years, model labs have shipped new versions almost every week (GPT-6.x, Claude 5.x, Gemini 4, Kimi K3...), and searches like "A vs B" and "which is best for coding" have grown with them. Each new model automatically adds N new comparison pages from its template, with no one writing them.
- Page count is the moat: with 1000 models, pairwise combinations come to about 500k pairs, and it has already built about 300k pages. Rivals like llm-stats and Vellum have one or two orders of magnitude fewer pages, so for obscure pairings BenchLM is the only one with a ready-made page.
- Long-tail pages have real substance: every page carries real scores, prices, and sources, and missing data is marked "Not measured" rather than filled in. That keeps them indexable in the 2026 era, when thin content gets demoted.
- Methodology as the brand: BenchAlign publishes its version number, weights and calibration method; every ranking is tagged Supported or Estimated; saturated or contaminated benchmarks like SWE-bench Verified are shown but not scored. This earns it a reputation as an "honest aggregator" (awesome-llm-bench's words), and it's why AI search and Reddit are willing to cite it.
- One person, very low cost: the data is all public, pages are generated from templates, and hosting is static or cached.
- Monetization in several layers: data API (Free 250 calls / Pro $49 / Research $249 per month; the page says "700+ users", which doesn't clarify whether that's sign-ups or paying customers), MCP, commercial licensing, on-site and newsletter ad sales (/advertise, already booking December ads), and affiliate disclosures.
5. Differentiation, and whether it's really why it grew
- Differentiation: (1) broader than every aggregator: 1016 models, 758 benchmarks, plus niche boards for voice, Korean, cybersecurity; (2) pairwise comparison pages built out to about 300k; (3) transparent methodology that grades the strength of evidence behind each ranking; (4) a data API and MCP, so developers can plug it straight into their own products or AI tools.
- Is this the cause? Growth mainly comes from (2), that is, page count × SEO templates. (1) is a precondition for (2): the more entities, the more combination pages. (3) keeps those pages from being treated as spam and gets them cited by people and AI, which is what lets SEO last, but it isn't a traffic source in itself. (4) is a way to make money, not a way to grow. For comparison: llm-stats uses a similar playbook but has fewer pages and weaker methodology, and grew only 1.25x over the same period, while BenchLM grew 3x.
6. Does anyone know about it, does anyone copy it
- Visibility: it's spreading in small circles.
- It publicly lists its GA4 pageviews and subscriber count on /advertise to sell ads;
- howtodistribute.com has already published "How BenchLM got its users", breaking down the playbook in detail and tagging it "COPYABLE";
- not listed on TrustMRR (trustmrr.com/startup/benchlm returns 404), revenue not public;
- almost no one discusses it on X (x-radar: 0 posts), and media coverage is limited to one futuretweets comparison article (2026-10-31).
- Copycats: benchleader.com (futuretweets compares it side by side with BenchLM), benchmarklist.com (promoted by someone on r/LLMDevs, claiming "1100+ benchmarks"), theaggregate.ai (has a page that collects BenchLM's rankings), whatllm.org, and onyx.app's llm-leaderboard page. None of these are in Tranco's top 1M (onyx.app ranks as its whole SaaS domain).
7. What others can borrow
- Pick a category people argue about every day where entities keep multiplying (models, tools, APIs, GPUs, phone plans...). Estimate the page ceiling as n×(n-1)/2. Build a comparison template that still looks decent when data is missing, with data sources that can be re-scraped on a schedule. Then add entry points like /best/{use-case}, /alternatives/{competitor}, and calculators.
- Grab AI citations: llms.txt, Dataset JSON-LD, and an index people keep citing (like its Token Price Index).
- Put an embed widget behind an attribution license to earn backlinks.
- Use a newsletter to keep search visitors; once traffic builds, open the API and ad sales as the two revenue lines.
- Risks: all the data is third-party and anyone can copy it; if Google changes its policy on programmatic pages, traffic could drop sharply.
8. Still unclear
- Revenue: unclear. Whether the API's "700+ users" are paying or just registered is unknown, and ad and affiliate income is also unknown.
- The share of its 300k comparison pages actually indexed by Google and getting clicks is unverified. July data shows 58.3K clicks over 28 days, with no later updates.
- 2026-03 site has had 301 redirects (per Wayback records); whether it changed domains or structure is unverified.
- Founder background unverified; all we know is the X handle @glevd (Guillaume).
- How many backlinks the embed widget actually brings is unverified.
Sources
- benchlm.ai/, /about, /data, /advertise, /embed, /llms.txt, /sitemap.xml (2026-11-07 crawl)
- howtodistribute.com/benchlm
- futuretweets.com/benchleader-vs-benchlm-vs-artificial-analys…
- github.com/leoncuhk/awesome-llm-bench
- Reddit: r/ClaudeAI 1rw80mr, r/GithubCopilot 1vsdt44, r/AskReddit 1xh7h7k, r/hermesagent 1tc99yw, r/LLMDevs 1u0lyni
- traffic database (rank_day, crux_domain, rankings as of 2026-11-05)
- Brave Search API (2026-11-07); x-radar (0 posts over the last 120 days)
- Wayback CDX: first snapshot 2025-08-13