AI models for every need
BiasChecker doesn't rely on a single AI. You choose from more than ten models from the major AI providers — and because every model is trained on different data and carries its own slant, that choice is part of the analysis, not just a setting.
In our own testing the same article can read as clearly biased to one model and balanced to another, and the split often tracks where a model was built. So run a piece through more than one: where they agree is a strong signal, where they diverge shows you each model's own perspective. Pick by the depth a piece deserves and how many analyses your plan allows.
The line-up evolves as better models ship — 10+ models from the major AI providers, and the cards below always show the current roster
How model cost works
Your plan gives you a monthly allowance of tokens — that's the exact meter. Every check draws down the actual tokens read and written, multiplied by the model's rate: a 1× model costs the raw token count, a 3× model three times that, a 10× model ten times. Longer articles cost a little more, since there's more text to read. To keep it easy to picture, we translate that allowance into analyses — one analysis ≈ one article checked for one type on a 1× model — but those counts are approximate; the precise draw-down is always tokens × the multiplier.
* Using 1× models. Higher-multiplier models use proportionally more — e.g. a 3× model gives ~200 checks/month on Lite.
Need more? Credit packs top up any plan from $15 for ~500 analyses (2.5M tokens). And on subscription plans, articles the community has already analysed are free — they don't count against your allowance. Compare plans →
Match the model to the analysis
Not every analysis needs the same model. The question to ask: does this lens mostly read the text, or does it need to know the world? Click a tier to filter the models below.
Everything the cards say is based on our own internal testing: in July 2026 we ran every model through the same articles on the same analyses, and each card's speed band, character sketch and trade-off comes from how it actually behaved in that run.
DeepSeek V3.2
DeepSeek
Tuned and benchmarked mainly on Chinese and English; other major languages still work, they're just not the focus.
The bargain overachiever: remarkable recall for the lowest-cost tier — at its best pulling apart shaky reasoning, and it digs up more omissions and context than most pricier models.
The most eager flagger in our testing: it always finds something to say, and occasionally reports a gap the article itself already covers — worth a second look before you rely on a specific omission.
Learn more about DeepSeek V3.2GLM 4.7
Zhipu AI
Tuned and benchmarked mainly on Chinese and English; other major languages still work, they're just not the focus.
A steady all-rounder that quotes its evidence well — our dependable, near-instant 1× everyday pick. Expect the tersest write-ups of any model: short, plain, and to the point.
GPT-5.6 Luna
OpenAI
Strong across dozens of languages; OpenAI benchmarks 14, including Arabic, Chinese, French, German, Hindi, Japanese, Korean and Spanish.
The calm hand of OpenAI's newest generation, now at an everyday price: in our July testing it was among the most even-handed readers of press releases and corporate announcements in the whole line-up (its own OpenAI siblings included), with disciplined legal judgement and fuller, well-hedged write-ups than its price suggests.
The flip side of that calm hand: it can under-call a genuinely one-sided advocacy piece, its moral lens occasionally flags the events a story reports rather than the writing, and its fuller write-ups make it one of the slower picks on tough articles.
Learn more about GPT-5.6 LunaDeepSeek V4 Pro
DeepSeek
Tuned and benchmarked mainly on Chinese and English; other major languages still work, they're just not the focus.
The V4 flagship: the family's trademark thoroughness with more polish than V3.2 — it surfaces more omissions and background gaps per article than most pricier models, in tidy, well-structured write-ups.
Like its V3.2 sibling it is an eager flagger: expect the occasional gap reported that the article itself already covers — worth a second look before relying on a specific omission.
Learn more about DeepSeek V4 ProGemini 3 Flash
Google documents the Gemini family across 100+ languages.
Google's fast-value pick: quick turnarounds, calm on routine and promotional content, and one of the sharpest models at catching a clickbait headline that doesn't match its story.
Two things to double-check: it occasionally pins the wrong date on a story's timeline, and it can overstate legal risk when a piece describes questionable behaviour without naming a specific actor.
Google's safety filter can refuse articles with violent or graphic themes.
Learn more about Gemini 3 FlashGPT-5.4 Minidefault
OpenAI
Strong across dozens of languages; OpenAI benchmarks 14, including Arabic, Chinese, French, German, Hindi, Japanese, Korean and Spanish.
Our default: it matches the flagships' depth of findings at a fraction of the price, in clear, well-organised write-ups that tie every point to a quote from the text — and its legal readings showed some of the best judgement in our July testing.
It reads polished PR and marketing copy as more slanted than most models do — a fairly harmless corporate announcement can come back rated a notch higher than a general reader would put it.
Learn more about GPT-5.4 MiniGrok 4.3
xAI
Handles other major languages, but xAI publishes little on its multilingual quality.
Built for speed: it sticks close to the facts in a lean, just-the-evidence style, exercises real restraint on benign and promotional content, and comes back fast.
Speed over depth — its lean style surfaces fewer findings than the deeper models, and its rewrites condense heavily, so reach for a 6× or 10× flagship when you want the most thorough read.
Learn more about Grok 4.3Kimi K2.5
Moonshot
Tuned and benchmarked mainly on Chinese and English; other major languages still work, they're just not the focus.
Our best all-round value pick in testing: accurate and level-headed, restrained on routine stories, the sharpest of any model at catching persuasion tactics where the spin runs thick — and it writes the funniest roasts.
The least predictable run to run in our testing — re-analysing the same article can come back a notch hotter or cooler than the first read, and its speed swings more with provider load than its peers.
Learn more about Kimi K2.5Claude Haiku 4.5
Anthropic
Strong across dozens of languages; Anthropic benchmarks 14, including Arabic, Chinese, French, German, Hindi, Japanese, Korean and Spanish.
Anthropic's careful eye at a mid price — and the fastest model in our latest 50-article run. It writes the fullest explanation per finding of any model, with an ethics-first sensibility that suits sensitive, moral questions.
The most cautious in the line-up: it declines to force a joke or a historical parallel more readily than any other model, and on borderline articles it is the likeliest to conclude there is nothing to flag.
Learn more about Claude Haiku 4.5GLM 5.2
Zhipu AI
Tuned and benchmarked mainly on Chinese and English; other major languages still work, they're just not the focus.
The fastest model in the line-up by a wide margin — verdicts land in seconds, in short, plain, to-the-point write-ups, with findings in line with the rest of the roster in our August testing.
Its neutral rewrites occasionally come back shorter than the original deserves; the app catches these and offers a retry rather than serving a cut-down version.
Learn more about GLM 5.2Gemini 2.5 Pro
Google documents the Gemini family across 100+ languages.
The evaluator — strongest on methodology and data claims, arguing its conclusions rather than piling up quotes, and the most meticulous with dates and timelines in our July testing.
The slowest model in our testing, and it takes serious subjects seriously — sometimes too much so: when a piece merely reports war or risky behaviour, it can flag the events themselves rather than the writing.
Google's safety filter can refuse articles with violent or graphic themes.
Learn more about Gemini 2.5 ProGemini 3.5 Flash
Google documents the Gemini family across 100+ languages.
The sprint champion of our July testing: the fastest model we measured — analyses typically back in a few seconds — with complete, level-headed output that stays calm on routine content while still catching bait-and-switch headlines and unsupported claims.
Occasionally pins the wrong date on a story's timeline, and can overstate legal risk when a piece describes questionable behaviour without naming a specific actor.
Google's safety filter can refuse articles with violent or graphic themes.
Learn more about Gemini 3.5 FlashGPT-5.1
OpenAI
Strong across dozens of languages; OpenAI benchmarks 14, including Arabic, Chinese, French, German, Hindi, Japanese, Korean and Spanish.
The maximalist: by a wide margin the most thorough model we tested — most findings, most verbatim quotes, fullest write-up on every lens (it surfaced roughly three times the omissions of its peers in our July testing), and the most faithful rewrites.
Its thoroughness cuts both ways: long omission lists can shade into repetition on short articles, and it rates promotional and institutional copy as more biased than most models do.
Learn more about GPT-5.1GPT-5.6 Terra
OpenAI
Strong across dozens of languages; OpenAI benchmarks 14, including Arabic, Chinese, French, German, Hindi, Japanese, Korean and Spanish.
OpenAI's newest generation at flagship strength, and the most even-handed reader in its family in our July testing: it sizes up promotional and institutional copy for what it is and leans once rather than crying foul, while still making the catches that matter, from a bait-and-switch headline to a buried safety claim, in clear quote-anchored write-ups.
It errs towards restraint: it can wave a science-shaped claim through as "not a science article", occasionally concludes none where most models read medium, and its rewrites condense a lean news piece towards a summary. The same caution reaches the Roast: it sometimes declines to write comedy about articles centred on real people under personal pressure (pieces other models roast without issue), so expect the occasional polite pass on that one lens.
Learn more about GPT-5.6 TerraClaude Sonnet 4.6
Anthropic
Strong across dozens of languages; Anthropic benchmarks 14, including Arabic, Chinese, French, German, Hindi, Japanese, Korean and Spanish.
The genre-spotter with the driest wit: first to call a press release a press release, and the most balanced voice on charged topics. In our latest 50-article run it dug up the most omissions and wrote the fullest analyses of any model.
Speed bands are indicative, not guaranteed — actual time varies with article length, time of day, and the current load on the AI providers we use. Very long articles take longer; every model handles articles up to 150,000 characters (roughly 25,000 words). In our max-length tests, models across the price range held full analysis depth at length — engagement with content near the very end of a long read varied by model rather than by price tier.
See the difference: same article, different models
We analysed the same article with twelve different models across all thirteen analysis types. On the seven types it supports, the Consensus panel adds a thirteenth card: three models from different makers, cross-checked and synthesised into one result. Notice how models can reach different conclusions — and how each brings a unique perspective.
Example article
The Hidden Dehydration Epidemic
A fictional wellness advertorial we wrote as demonstration material — every company, product, study, and person in it is invented. It reads the way persuasive health marketing actually reads, so each analysis lens has something real to find. Read the full piece via the source link.
BiasChecker.ai demonstration article (fictional)Surfaces the meaning beneath the words — what the author really wants you to think.
The article profiles Lumivita, a wellness company claiming that millions suffer from undiagnosed cellular dehydration. It contrasts the company's assertions and a proprietary study with the skepticism of doctors and regulatory adjustments to its marketing language.
- •Founder Maarten de Wit claims standard hydration advice is outdated and ineffective.
- •A cited study reports users gained 34% more energy within three weeks.
- •Regulators forced changes to product descriptions after a dialogue.
- •The company operates a coaching program that certifies trainers to sell the protocol.
Steered to see
View Lumivita as a necessary health innovation that is unfairly dismissed by a resistant establishment.
Played down
Regulators required changes to product descriptions, contradicting the narrative that the science is settled and only bureaucracy lags behind.
Technique
The text pairs alarming health claims with testimonials while framing medical skepticism as predictable resistance and regulatory action as minor paperwork.
Evidence
The text reframes regulatory intervention as a trivial administrative delay rather than a check on validity.
The article casts doubt on medical skepticism by implying a conspiracy motive from competitors.
The text uses emotional pressure to make the product feel like a moral obligation for parents.
The article presents a wellness company's claim that a 'hidden dehydration epidemic' exists at the cellular level, causing fatigue and other issues that mainstream medicine overlooks. It promotes the company's CelluDrink product line as a superior solution, citing a company study and testimonials from trainers and a parent. It notes regulatory pushback but frames it as a minor obstacle to innovation.
- •The company's founder claims hydration advice is 'stuck in the 1950s' and that drinking plain water can be harmful.
- •A personal trainer is quoted saying thirst means performance has already dropped by 20%, promoting constant sipping of the product.
- •The article mentions regulators forced the company to change product descriptions, but this is called 'routine dialogue' and 'growing pains'.
- •The company claims its formula was developed with European labs and that journals are 'slow to catch up'.
- •A mother says she gives the product to her school-age children to help them concentrate.
Steered to see
Accept that a hidden health crisis exists and that buying this company's products is a necessary, scientifically-backed solution.
Played down
Regulators intervened to force changes to the company's product descriptions, indicating its claims were problematic.
Technique
The article frames the company's claims as urgent, revolutionary truth opposed by a dismissive establishment, using testimonials and selective science to build credibility.
Evidence
The text uses a false dilemma to create urgency and steer readers toward the company's solution.
The article frames skepticism as evidence of establishment bias, not as a reason for caution, to bolster the company's outsider credibility.
The text buries a significant regulatory red flag by using the company's mild language and immediately countering it with the founder's 'growing pains' framing.
The piece is a promotional profile of Lumivita and its CelluDrink hydration products. It presents cellular dehydration as an overlooked problem and pairs that claim with testimonials, selected study results, and business growth. It also notes that regulators required changes to some product descriptions.
- •"wins over executives, athletes and worried parents"
- •"people using CelluDrink reported 34% more energy within three weeks"
- •"Plain water... can dilute the electrolytes your muscles run on"
- •"Regulators... Lumivita agreed last year to change some of its product descriptions"
- •"the waiting list for its coaching programme... is months long"
Steered to see
Treat CelluDrink as a credible fix for hidden dehydration and see delay as the risky choice.
Played down
It briefly notes regulators made Lumivita change some product descriptions, then moves back to the sales pitch.
Technique
It leans on alarming health claims, upbeat quotes, anecdotal users, and growth cues, while giving the regulatory caveat only a brief mention.
Evidence
The headline casts the issue as urgent and widespread before any support is shown.
The text frames the choice as stark and pushes urgency over skepticism.
The article uses demand and expansion to make the product seem validated.
Lumivita, an Amsterdam wellness company, promotes its CelluDrink hydration products by claiming mainstream medicine underestimates cellular dehydration. The article presents testimonials from athletes, trainers, and parents alongside company claims of scientific backing, while noting regulatory pushback and medical skepticism.
- •Company founder claims 'Big Beverage' conspires to keep people drinking plain water
- •Regulators forced product description changes after 'routine dialogue'
- •Coaching programme certifies trainers to sell protocol to their own clients
- •Study cited is unpublished, with researcher only 'shortlisted' for prizes per company claim
- •Mother quotes guilt-inducing framing: 'What kind of parent watches their child struggle... and does nothing?'
Steered to see
Accept that mainstream medicine is wrong and negligent about dehydration, and that purchasing CelluDrink is the responsible choice for health-conscious people.
Played down
Regulators forced the company to change product descriptions, and the cited study lacks peer review or journal publication — facts mentioned briefly then dismissed as 'growing pains' and 'slow to catch up'.
Technique
The text elevates company claims to headline status while burying regulatory intervention and medical dismissal in late paragraphs, uses guilt and fear appeals ('premature ageing', 'silent emergency', parental shaming), and frames commercial expansion as validation.
Evidence
Reframes regulatory compliance failure as visionary disruption, minimizing official concern
Uses false dilemma to eliminate neutrality and pressure commitment to the product
Deploys guilt-based social pressure to convert parental anxiety into purchase behavior
The article highlights a 'cellular dehydration' crisis and promotes Lumivita, an Amsterdam-based wellness company offering specialized hydration protocols. It contrasts the company's claims of superior cellular absorption with traditional medical advice and water consumption.
- •Lumivita claims its CelluDrink protocol hydrates twice as fast as plain water by mirroring cellular fluids.
- •A company-cited study reports a 34% energy increase in users, though the research has not yet appeared in mainstream journals.
- •The company recently modified its product descriptions following a 'routine dialogue' with regulatory authorities.
- •The founder frames the choice as a binary between adopting their cellular hydration protocol or accepting physical decline.
Steered to see
View Lumivita’s products as a necessary, scientifically-backed solution to a hidden health crisis that mainstream medicine and regulators are too slow or biased to recognize.
Played down
The text briefly mentions that doctors are dismissive and that the company had to change its product descriptions after regulatory intervention, but frames these as 'growing pains.'
Technique
The article uses alarmist framing ('silent emergency'), creates a false dichotomy between the product and 'decline,' and dismisses medical skepticism as a sign of being outdated or compromised.
Evidence
The text uses a false dilemma to pressure the reader into seeing the product as the only way to avoid health failure.
The framing attempts to undermine the reader's confidence in basic, free health practices to make the paid alternative seem essential.
The article uses 'us vs. them' rhetoric to cast experts as out-of-touch or motivated by corporate interests.
This article promotes Lumivita's CelluDrink protocol, presenting it as a remedy for a widespread, unrecognized cellular dehydration crisis. It cites company studies, trainer endorsements, and parent testimonials while dismissing medical skepticism as outdated or commercially compromised. A past regulatory issue is mentioned but minimized.
- •Founder claims 'you can drink three litres a day and still be dehydrated' at the cellular level.
- •In-house study reports 34% more energy in three weeks, cited without independent verification.
- •Personal trainer repeats the 'thirst comes too late' rule and directs clients to CelluDrink Sport.
- •Company says its coaching programme waiting list is 'months long', signaling high demand.
Steered to see
See Lumivita's CelluDrink as a scientifically backed, urgent solution to a widespread hidden health crisis that mainstream medicine and regulators are too slow or compromised to address.
Played down
The article mentions Lumivita agreed to change product descriptions after a regulator dialogue, but frames it as routine 'paperwork' rather than a potentially meaningful compliance issue.
Technique
The article lets the company's founder dominate with unchallenged claims, frames skeptics as corrupt or slow, and uses emotional parent testimonials to bypass scientific scrutiny.
Evidence
The founder's quote reframes ordinary hydration advice as dangerously obsolete, creating a problem only CelluDrink can solve.
The article amplifies an unsubstantiated conspiracy claim that dismisses medical skepticism as financially motivated, steering readers to distrust doctors.
The regulatory action is buried near the end and immediately minimized with the founder's euphemism, downplaying potential credibility issues.
Lumivita, an Amsterdam wellness company, promotes CelluDrink, a product claiming to achieve cellular-level hydration that plain water cannot. The article presents the company's claims about energy gains, endorsements from trainers and parents, and dismissal of medical skepticism as institutional resistance to innovation. Regulators required labeling changes, which the company frames as routine.
- •Study claims CelluDrink users reported 34% more energy within three weeks
- •Trainer Bram Kuijpers says plain water during workouts can dilute electrolytes and harm performance
- •De Wit compares skepticism to past dismissal of intermittent fasting and suggests Big Beverage has financial incentive to promote plain water
- •Regulators required Lumivita to change product descriptions after "routine dialogue"
- •Mother Sanne gives CelluDrink to school-age children, framing it as parental responsibility
Steered to see
Accept that mainstream hydration advice is outdated and that Lumivita's cellular hydration science represents genuine innovation being suppressed by institutional resistance.
Played down
Regulators required the company to change product descriptions, a fact buried late and reframed by the company as "growing pains" rather than evidence of overstated claims.
Technique
The article amplifies the company's framing ("silent emergency," "ancient wisdom confirmed by modern science"), gives sympathetic voice to users and trainers, and presents medical dismissal as predictable institutional gatekeeping rather than warranted caution.
Evidence
The article opens with the company's most dramatic claim unchallenged, establishing the premise that conventional wisdom is fundamentally wrong.
Medical skepticism is reframed as predictable bias rather than legitimate scrutiny, and financial incentive is attributed to critics without evidence.
Regulatory action is minimized and buried, presented through the company's own language ("routine") rather than as a sign of prior overstatement.
The article profiles Lumivita, an Amsterdam wellness company selling the CelluDrink hydration protocol, framing its products as a solution to an unrecognized cellular dehydration crisis. It presents the company's claims alongside testimonials from a trainer and a parent, while noting that regulators required changes to product descriptions and that doctors remain dismissive. The text positions Lumivita as an innovator fighting a resistant medical establishment.
- •A company-cited study reported 34% more energy in CelluDrink users within three weeks.
- •Lumivita agreed to change product descriptions after what the company calls 'a routine dialogue' with regulators.
- •A family plan for CelluDrink costs less per day than a coffee, according to a customer testimonial.
- •Lumivita is expanding into the UK and Canada, with a months-long waiting list for its trainer coaching programme.
- •Plain water during a workout can dilute electrolytes, the company warns, positioning its mix as superior.
Steered to see
The article steers readers to view Lumivita's products as a medically neglected breakthrough they should buy before it is too late.
Played down
The article briefly notes that regulators forced product-description changes and that doctors remain dismissive, but immediately recasts both as establishment resistance and mere 'paperwork' growing pains.
Technique
The text frames mainstream medicine and regulators as obstacles to progress, uses fear-based language about 'silent emergency' and decline, and routes commercial promotion through sympathetic parent and trainer testimonials.
Evidence
The text uses a false binary to pressure readers into treating the company's protocol as the only alternative to health decline.
The article frames a commercial competitor as a conspiratorial force, positioning Lumivita as the underdog truth-teller.
The text recasts a regulatory action against product descriptions as a routine administrative detail rather than a substantive credibility problem.
The article describes a supposed epidemic of "cellular" dehydration and presents Lumivita's CelluDrink products and protocol as a solution. It cites company claims, a small study, a trainer, and a parent to argue that traditional hydration advice and mainstream medicine are outdated. Doctors and regulators are briefly mentioned as skeptical, but their views are minimized. The piece ends by stressing urgency and promoting Lumivita's expansion and coaching program.
- •Claims CelluDrink users had 34% more energy in three weeks
- •Hospital dehydration admissions are cited as proof of a wider problem
- •A trainer warns thirst is already "too late" and pushes CelluDrink Sport
- •Doctors are described as dismissive and tied to "Big Beverage" incentives
- •Regulators made Lumivita change product descriptions after a review
Steered to see
The article steers readers to view cellular dehydration as a serious, urgent problem and to see Lumivita's CelluDrink protocol as a necessary, science-backed upgrade to plain water.
Played down
The article briefly notes that doctors are dismissive and that regulators forced Lumivita to change product descriptions, but downplays these as bias and "growing pains" instead of substantive concerns.
Technique
By framing dehydration as an epidemic, using dramatic either/or language, success anecdotes, implied scientific backing, dismissing doctors and regulators, and ending on urgency and scarcity around Lumivita’s products.
Evidence
Uses stark binary framing to push the idea that accepting Lumivita’s premise is the only sensible choice.
Presents company-linked study results as strong scientific evidence without detailing methods or limits, to signal credibility.
Acknowledges regulatory pushback but immediately reframes it as minor and expected, softening potential red flags.
This article introduces Lumivita, a wellness company claiming that millions suffer from a "hidden dehydration epidemic" at the cellular level. It presents the company's product, CelluDrink, as the solution, featuring testimonials from a founder, a personal trainer, and a parent. The piece also notes that doctors are dismissive and regulators have required the company to alter its product descriptions.
- •Lumivita's founder claims people can drink three litres of water a day and still be dehydrated at the cellular level.
- •A company-cited study reported that users of CelluDrink experienced 34% more energy within three weeks.
- •The company's electrolyte mix is claimed to hydrate twice as fast as water.
- •The founder dismisses medical skepticism by comparing it to initial resistance to intermittent fasting.
- •The company changed some product descriptions following what it calls a "routine dialogue" with regulators.
Steered to see
The article is built to make readers view Lumivita's product as a credible and urgent solution to a serious health problem, and to see the company as an innovator fighting an outdated establishment.
Played down
The article mentions that regulators required the company to change its product descriptions, but frames this as mere 'growing pains' and a 'routine dialogue'.
Technique
The piece functions as an advertorial by framing a common problem as a newly defined 'epidemic,' using testimonials and a company-backed study, and preemptively dismissing expert criticism and regulatory action as the predictable resistance of a biased system.
Evidence
This quote uses a false dichotomy to create a sense of urgency and position the company's protocol as the only viable choice.
The text preemptively dismisses criticism from the medical establishment by framing it as biased and comparing the product to a now-accepted wellness trend.
This phrasing adopts the company's own minimizing language to downplay a significant regulatory action, framing it as a minor procedural issue rather than a challenge to its claims.
This article profiles Lumivita, a Dutch wellness company selling a product called CelluDrink, framed as a solution to a widespread but unrecognized 'cellular dehydration' crisis. It presents the company's founder, a personal trainer, and a customer testimonial as evidence that mainstream medicine and regulators are behind the curve. The piece reads as promotional content dressed in the style of investigative health journalism.
- •The sole study cited reports self-reported outcomes ('reported 34% more energy') — not a clinical measurement.
- •The researcher behind the study is identified only by the company's own description of her credentials.
- •Regulators required Lumivita to change product descriptions after what the article calls 'a routine dialogue' — a significant fact buried near the end.
- •The coaching programme certifies trainers to sell the protocol, creating a multi-level distribution structure the article presents neutrally.
- •The closing line — 'how long can you afford to wait' — is a direct sales pressure tactic embedded in editorial prose.
Steered to see
The text steers readers to see CelluDrink as a credible, urgent health solution and to distrust the medical and regulatory institutions that question it.
Played down
Regulators required the company to change product descriptions — a red flag for unsubstantiated claims — but the article frames this as routine bureaucratic friction, not a credibility problem.
Technique
The article uses fear framing ('silent emergency'), manufactured authority (unnamed prize-nominated researcher, European labs), dismissal of critics as industry-captured, and a guilt-laden parent testimonial to lower skepticism and push toward purchase.
Evidence
The article deploys a conspiracy framing to pre-emptively discredit any institutional skepticism, steering readers to dismiss expert pushback rather than weigh it.
The article lets the founder reframe a regulatory enforcement action as a sign of the company's forward-thinking nature, neutralizing what is actually evidence of a compliance problem.
The text uses parental guilt as a conversion lever, framing inaction — not buying the product — as neglect.
The article presents Lumivita's CelluDrink protocol as a response to widespread, unnoticed “cellular” dehydration. It cites company-linked claims about energy, athletic performance, and family health while describing expansion into new markets. It also notes that regulators required changes to some product descriptions.
- •Lumivita cites a study reporting 34% more energy in three weeks.
- •Its trainer program certifies coaches to sell the protocol to clients.
- •The company markets a Sport electrolyte line for workouts.
- •It says it changed product descriptions after regulator discussions.
Steered to see
The article steers readers to see CelluDrink as an urgent, science-backed safeguard against decline that they should adopt without delay.
Played down
The article briefly notes that regulators required Lumivita to change product descriptions, then recasts this as routine “growing pains.”
Technique
The text pairs alarming health claims with testimonials, sales-ready product claims, and urgency, while casting doctors, journals, and regulators as slow obstacles to innovation.
Evidence
The article frames buying into the protocol as the only responsible alternative to physical decline.
The text turns ordinary water into a potential danger to make the product appear necessary.
The article minimizes the regulatory change by treating it as bureaucracy rather than a substantive caution.
Key takeaway: All twelve models see through the article format to the same beneath-the-surface read: this is an advertorial, built to make distrusting mainstream hydration advice feel responsible and buying CelluDrink feel like the informed choice. Kimi K2.5 (2×) states it most plainly: accept that mainstream medicine is "wrong and negligent", and purchasing becomes "the responsible choice". Claude Sonnet 4.6 (10×) files the sharpest counter-signal: the regulator episode is a red flag for unsubstantiated claims, but the article dresses it as "routine bureaucratic friction".
💡 Compare models on any article — the Chrome extension lets you switch models directly in the side panel to see how different models analyse the same content.
Try this on your own reading
In the extension side panel, pick a different model from the dropdown and re-run the same article. Where the two models agree, you can be fairly confident. Where they diverge, you're seeing each model's own perspective — in our own testing, half the fleet read one BBC science piece as biased and the other half as balanced. That disagreement is information, and it's the whole point of having 15 models to choose from.
Where to start
We put more than 30 models from nearly every major AI lab through the same real articles and kept the 15 that earned their place. Here's the short version.
⭐ If you just want an answer: GPT-5.4 Mini (2×)
It's our default because it won on the numbers: flagship-level depth of findings at a fifth of the flagship price, fast, in clear write-ups that tie every point to a quote. Leave the model selector alone and this is what you get.
Standouts by analysis type
Using per-analysis mode in the extension settings? Where a model clearly stood out in our testing, it's listed here — for the analysis types not listed, no single model stood out and the default serves them well.
Frequently asked questions
Which model should I start with?
GPT-5.4 Mini (2×) is the system default — a capable, well-rounded everyday choice. If you're skimming a lot and want the lowest cost, the 1× models (GLM 4.7, DeepSeek V3.2) are the cheapest. When an article is especially dense or the argument is tangled, a higher-tier model reads the logic more carefully and is less likely to misread what it actually says. Every model we offer can do the job — the cheaper ones just slip slightly more often on complex reasoning, so stepping up is an easy way to add confidence when you want it.
Can I use different models for different analysis types?
Yes. In the Chrome extension settings, switch to "per-analysis" mode to assign a different model to each analysis type — for example, Kimi K2.5 for Persuasion Tactics and GPT-5.1 for Omissions. The "standouts by analysis type" list under Where to start is built for exactly this.
Do all plans get access to all models?
Yes — every plan can use every model, including the free trial. The only difference between plans is the monthly analysis allowance, not which models you can access.
What is the Consensus option?
On supported analysis types, Consensus runs a panel of models from different makers — one vote per maker family — and a final pass reports where they agree and where they split. Because agreement between independently built models is the strongest signal an analysis can give, it's the option to reach for when a story really matters. It costs the sum of the models it runs, so it's the most expensive single click — though on articles the community has already analysed it reuses cached results and gets cheaper.
Can I analyse non-English articles?
Yes — BiasChecker works on articles in any major language. In our testing, quality held up across Chinese, Arabic, and German with no drop versus English, and on-page highlighting works because quotes are extracted in the article's original language. The analysis itself is written in English — except the GPT-5 models (GPT-5.1, GPT-5.4 Mini), which write theirs in the article's own language.
How widely a model is documented to support languages does vary, and each model card above shows it: broadly multilingual models (Gemini, GPT-5, Claude) are built for 100+ languages; the Chinese & English specialists (GLM, Kimi, DeepSeek) are strongest in those two with solid coverage of other majors; and Grok is English-first with a shorter official list. For non-English news, a broadly-multilingual model is the safest pick.
One thing to note: BiasChecker analyses the text as it appears on the page. If your browser's "Translate this page" feature is switched on, it will analyse the translated version — so turn page translation off if you want the original language checked.
Why do some models cost more?
More expensive models are generally larger, newer, or use reasoning techniques that require more computation. Larger models also know more about the world and read further into long articles, which shows up as more depth and fuller coverage on lenses like Key Omissions, Background, Legal Risk, Critique, and Scientific Assessment — where bigger models were quicker to flag shaky claims in advocacy pieces (though on a rigorous primary-science paper every tier agreed it was sound). For straightforward text-reading checks, a 1× model does a great job.
Is there a limit on article length?
Every model can analyse an article up to 150,000 characters (~25,000 words). In our max-length tests, models across the price range held full analysis depth all the way to that limit; the only thing that varied was how closely a model engaged with content right at the very end of a very long read, and that tracked the individual model rather than its price tier. For anything longer than 150,000 characters, select the section you care about and analyse that.
How is usage measured?
In tokens — that's the exact measure. Tokens are the small chunks of text a model reads and writes (roughly ¾ of a word each), and every analysis draws down your monthly token allowance by the actual amount of text read and written, multiplied by the model's rate (a 1× model costs the raw token count, a premium model costs ×its multiplier). Longer articles and pricier models therefore use more tokens. To make this easy to picture, we also show it as analyses: a typical article checked for one type on a 1× model is ≈ 5,000 tokens, so that's "one analysis" — but the underlying meter is always tokens, and your allowance resets each billing cycle.
Can I switch models at any time?
Yes — pick a different model from the side panel dropdown whenever you like, no plan change needed. Each check is simply charged at the multiplier of the model you used, so you can run everyday articles on a 1× model and save the expensive ones for pieces that matter.
What happens if I use up my monthly analyses?
Your allowance refills at the start of each billing cycle. If you run out mid-month, a credit pack (from $15 for ~500 analyses / 2.5M tokens) tops you up instantly — credits are only consumed after your plan allowance. And articles the community has already analysed stay free on subscription plans, so popular news often costs you nothing at all.
15 models, ready to read the news with you
The BiasChecker extension is launching soon — it'll let you run any article through the models above and see what your favourite news source isn't telling you. Take a look at the plans while you wait.