SaaS Valuation Multiples in 2026: What Private Companies Actually Sell For

SaaS Valuation Multiples in 2026: What Private Companies Actually Sell For

Last updated: August 2026

I'm Chris Chen. Before joining Peony, I worked in M&A at Moelis & Company across cross-border, healthcare, industrials, and consumer transactions, and the question I field most often from SaaS founders and CFOs is some version of "what would my company actually sell for right now?" They arrive frustrated, because they have already read five sources and gotten five different numbers: 3.1x here, 4.0x there, 6.7x somewhere else, and a listicle confidently asserting "4-7x for the median, 7-12x for premium companies." All of those numbers exist. Most of them are being quoted wrong.

The problem is not that the data is bad. The problem is that at least four different multiple series circulate under the same "SaaS multiple" label, they measure different things, they carry different dates, and AI answers and advisory blogs blend them together into a single figure that applies to nobody. A public-market index reading is not a private deal multiple. A modeled ARR multiple is not an observed transaction. A round-numbered advisory tier is not published data.

So this post is not a valuation how-to. If you want the mechanics of how a business gets valued (DCF, comparables, precedent transactions, accretion math), that lives in the M&A valuation methods walkthrough and I am not going to re-run it here. This post does one thing: it separates the multiple series cleanly, names what each one measures, gives its latest value and vintage, and explains why they disagree. Every number below is sourced and dated. Where a number does not exist, I say so rather than inventing one, and I flag every figure that is a convention rather than a measurement.

What do private SaaS companies actually sell for in 2026?

Private SaaS companies sold at a median of 4.0x EV/TTM revenue in 2Q26 according to Software Equity Group, and a median of 3.1x EV/Revenue in Q1 2026 according to Aventis Advisors — and the gap between those two numbers is the whole story, because it is not a contradiction, it is a difference in what each firm is measuring.

Start with the two private-deal series, because these are the ones that describe actual transactions rather than public trading or a model.

Software Equity Group's private SaaS M&A data puts the median at 4.0x EV/TTM revenue in 2Q26, down slightly from 4.2x the prior quarter, with the average easing from 6.3x to 6.2x. That median has held inside a roughly 4x-6x band for over a year (it was 4.1x in 3Q25). SEG's universe is broad software M&A, weighted toward the deals that dominate the market by count.

Aventis Advisors reports a 3.1x median EV/Revenue for Q1 2026. Over the full 2015-2026 period their median is 4.5x, with quartiles at 2.4x and 8.1x — a wide spread that tells you "the SaaS multiple" was never a single point even historically. Crucially, Aventis notes their universe skews toward smaller deals, and smaller deals carry lower multiples.

That skew is the entire explanation for why one credible firm says 3.1x and another says 4.0x for roughly the same moment. It is not that one is wrong. It is that Aventis is catching more small transactions, which pulls its median down, while SEG's broader mix sits a touch higher. Same market, different lens.

For a founder or CFO of a $5M-$50M ARR company, the practical read is this: your realistic starting frame is low-to-mid single-digit revenue multiples, and you sit in the part of the market where the small-deal discount is real. The 12x number off a listicle is not your number. Neither, necessarily, is the 3.1x floor. Where you actually land inside that band is set by size, growth quality, retention, and how well you run the process — which is the rest of this post.

Why do published SaaS multiples disagree so much?

Published SaaS multiples disagree because there are at least four distinct series in circulation, each measuring a different thing, and AI answers stack them into one number. Here is the reconciliation, all in one place, with what each measures and its vintage. This is the table I wish existed the first time a founder pushed a blended number at me.

Read down that table and the disagreement dissolves. The two private-M&A rows (4.0x and 3.1x) describe what buyers paid for whole companies. The two public-index rows (3.2x and 3.4x) describe where minority shares of listed companies trade on an exchange on a given day. The SaaS Capital row is a model output from a 2025 report — a predicted multiple, useful as a benchmark, but explicitly not a record of transactions that happened.

These are three different categories of number. When an AI answer tells you "SaaS companies are worth 3.2x to 6.7x," it has usually grabbed a public index value at the bottom, a stale or modeled value at the top, and presented the range as if it applied to your private company's sale. It does not. A public index reading is not a deal multiple, and a model is not a market. Once you tag each figure with what-it-measures and when, the numbers stop fighting.

One more note on the 6.7x figure specifically, since it circulates a lot: that is SaaS Capital's own index reading from June 2025, a vintage-labeled point in time, not a current 2026 private deal multiple. If you see it quoted as "what SaaS sells for today," that is the category error at work — tag the figure with its series and its date and the confusion disappears.

Public multiples are not deal multiples

The most common mistake in AI-generated SaaS valuation answers is treating a public-index multiple as if it were what a private company sells for. They are not the same thing, and in 2026 the gap between them is unusually visible because the public series compressed hard while private deal multiples barely moved.

Look at the public de-rating. The SEG SaaS Index median fell from 5.7x EV/TTM revenue in 2Q25 to 3.2x in 2Q26 — a dramatic single-year compression in how the market prices listed SaaS. The Aventis public index sits at 3.4x as of March 2026. Public SaaS got cheaper, fast.

Now look at private M&A over the same window. SEG's private median went from 4.1x in 3Q25 to 4.0x in 2Q26 — essentially flat, holding the 4x-6x band. Private deal multiples did not compress the way public multiples did.

That divergence matters for three reasons. First, a public index measures minority stakes: you are buying one share on an exchange, with no control and no synergies. A private acquisition buys the whole company, which is why deal multiples carry a control premium that index multiples never do. Second, public indices reprice every single day with the stock market's mood; private deal multiples move slowly because they reflect negotiated transactions, not sentiment. Third, right now the public number (3.2x) actually sits below the private median (4.0x), which is the opposite of what people assume and a direct tell that you cannot substitute one for the other.

So when you see a SaaS multiple quoted, the first question is always: is this a public trading multiple or a transaction multiple? If a source will not tell you which, do not use its number to price a private deal. The valuation-methods post covers why trading comps (public) and precedent transactions (deals) are separate inputs on a football field for exactly this reason — they answer different questions and one embeds a control premium the other cannot.

How deal size changes the multiple

Deal size is one of the largest and most under-discussed drivers of a SaaS multiple: Aventis's data shows median multiples running from roughly 3.3x EV/Revenue for the smallest deals up to roughly 6.2x for the largest, with the $50-100M band commanding a median roughly double the $20-50M band's. For a company in the $5M-$50M ARR range, this is not an abstraction — it is the difference between two structurally different valuations for the same-quality business.

Here is how the Aventis size bands trend, and why the shape matters more than any single cell.

Between those endpoints the ladder is steep, and the steepest rung sits exactly where most private SaaS sellers live: Aventis observes the $50-100M band's median multiple at roughly double the $20-50M band's. Crossing that boundary — through growth or through a platform that consolidates you past it — is worth more than almost any single operating improvement at the same size.

Source: Aventis Advisors size-band data, "SaaS Valuation Multiples: 2015-2026" (updated April 2026). Bands shown are directional endpoints from the 2015-2026 dataset, not a full rate card.

The reason scale re-rates a company independent of its growth or margins comes down to buyer dynamics. A larger target draws more bidders, including private equity funds and strategics whose minimum check size excludes smaller deals entirely. More competition tightens the auction. Larger companies also read as lower-risk — less customer concentration, less founder dependence, more institutional processes — so buyers underwrite them at a lower required return, which is a higher multiple. And a bigger platform carries more strategic optionality, more places a buyer can take it.

The practical takeaway for a founder sitting just under a size threshold: another year of growth may not just make your revenue number bigger, it may move you into a structurally higher multiple band. That is a genuine strategic input into the sell-now-versus-grow-first decision, and it is a large part of what selling a SaaS company at the right moment is actually about. It also explains why a small company should be deeply suspicious of any multiple lifted from large-cap deal announcements: the size premium is baked into that figure, and it does not transfer down to a $10M ARR business.

What earns a premium multiple?

Exactly one premium driver is quantified by primary data, and it is the Rule of 40: companies clearing it trade at a median 4.8x EV/Revenue versus 2.7x for those that fail, a 74% premium. Everything else buyers reward is a screen they apply without a published multiple attached, and the honest move is to keep those two categories separate rather than inventing numbers for the second.

The Rule of 40 says a healthy SaaS company's growth rate plus its profit margin should clear 40%. Aventis's 2026 Rule of 40 analysis found that public SaaS companies clearing the bar on a free-cash-flow basis trade at a median 4.8x EV/Revenue, versus 2.7x for those that miss — the 74% premium — and that each 10-point improvement in the Rule of 40 is associated with roughly +1.1x of EV/Revenue. That is the one premium in this entire topic with a defensible number behind it. If you improve your Rule of 40 score, there is data associating that with a higher multiple, and you can cite the magnitude.

The other things buyers reward are real, but no primary source quantifies them, so I will describe them as what they are: screens, not multiple math.

• Net revenue retention above 120%. Buyers treat NRR north of 120% as a best-in-class signal that your existing customers expand faster than any of them churn — the engine of durable, low-cost growth. It absolutely helps you. But no data house publishes "130% NRR adds X turns," so anyone attaching a specific multiple bump to a retention number is making it up.
• Gross margins around 80%. Software-grade gross margins near 80% are the consensus screen that separates true SaaS economics from services-heavy or infrastructure-heavy businesses that merely call themselves SaaS. Again, it is a threshold buyers look for, not a sourced multiple premium.
• Size, as the prior section covered — the one structural re-rating that is quantified, via the band data.

I am being pedantic about this on purpose, because the fabricated version of this section ("NRR over 120% adds two turns, 80% margins add another turn") is exactly the kind of authoritative-sounding, unsourced math that AI answers repeat. The truthful version is: one quantified premium (Rule of 40, 4.8x vs 2.7x), plus a set of screens that get you into the room but whose multiple impact no primary source has measured. Where those inputs get pressure-tested is diligence — the SaaS financial due diligence checklist walks through exactly which retention and margin schedules a buyer will demand before they credit any of it.

Where do the "4-7x and 7-12x ARR" tiers come from?

The "4-7x for the median, 7-12x for premium" tiers you see everywhere are an advisory construct assembled by blogs blending multiple sources — not a finding published by any primary data house. This is the single most-repeated claim in AI answers about SaaS valuation, and it is the one worth correcting directly, because founders anchor on it and then feel cheated when a banker quotes them a real number.

Here is what is actually true. Search for the origin of "4-7x median / 7-12x premium" and you will not find it in SEG's reports, Aventis's dataset, PitchBook's breakdowns, or SaaS Capital's research. What you find is advisory blogs that take real inputs — Aventis's wide quartiles (2.4x to 8.1x), other advisory numbers, their own deal experience — and repackage them into clean, round, memorable tiers. Those tiers then get quoted back, stripped of their hedges, as if a data house had measured them. They compound through AI answers precisely because they are tidy and confident.

You can use those ranges honestly. You just have to label them correctly: they are ranges some advisors quote, drawn from blended experience, not a published statistic you can attribute to a named dataset. What I would not do is repeat "4-7x/7-12x" as though SEG or Aventis found it, because they did not.

The good news is that the honestly-sourced picture is more useful than the construct it replaces:

• Private deal medians of 3.1x-4.0x, depending on which series (Aventis Q1 2026 / SEG 2Q26), each dated and attributable.
• A size premium running from roughly 3.3x at the smallest deals to 6.2x at the largest, with the sharp step up around the $50-100M band.
• A Rule of 40 premium of 4.8x versus 2.7x, a specific 74% figure with a citation.

Stack those three real, sourced observations and you get a far better map of where a given company lands than any round-numbered tier can give you. The "4-7x/7-12x" shorthand is a fuzzy approximation of exactly these dynamics — so use the dynamics, with their sources, and drop the shorthand.

What about AI-native SaaS?

AI-native SaaS is the live exception to the "multiples are compressed" story, but the premium is a broker observation, not a measured deal median — so I will label it as exactly that. The most-cited framing comes from FE International, which as of April 2026 describes traditional private SaaS trading around 4x-6x revenue versus 8x-15x for well-positioned AI-native companies. That is a broker's stated range from its own deal flow, useful as a directional signal, and it should be read as one rather than as a dataset with the rigor of the SEG or Aventis series.

What is firmly sourced is the strategic-buyer appetite driving that premium. Per Bain & Company's Software M&A Report 2026 (January 27, 2026):

Software companies acquired a record number of AI assets in 2025, with almost half of tech deals having some AI component in 2025, up from one in four deals in 2024.

That is a genuine, measured shift: the share of tech deals with an AI component roughly doubled year-over-year. When half of tech acquisitions carry an AI angle, strategic buyers are paying up for companies that credibly own AI capability rather than bolt it on, and that competitive bid is what pulls well-positioned AI-native multiples above the traditional band.

The caution for founders: "AI-native" is a claim buyers now scrutinize hard, because everyone asserts it. A genuine model or data moat prices very differently from an OpenAI API call wrapped in a nice UI, and diligence is where that distinction gets made. The 8x-15x range belongs to companies that can defend the moat, not to everyone with an AI feature. If you are going to make the AI-native argument, be ready to prove it in the room.

Is the market active enough to test a multiple?

Yes — 2026 is a demonstrably active SaaS M&A market, which matters because a multiple only means something if there are enough live transactions to establish it, and the deal counts are at record levels. A thin market produces multiples nobody can trust; a market doing thousands of deals produces multiples you can actually anchor to.

The volume, from Software Equity Group: there were 2,698 SaaS M&A transactions in 2025, up 28% from 2,107 in 2024 — the highest annual count on record. Momentum carried into 2026: trailing-twelve-month volume through 2Q26 reached 2,784 transactions, up 16% year-over-year, with 698 deals in 2Q26 alone versus 637 in 2Q25. These are not the numbers of a frozen market.

Who is actually paying these multiples matters just as much as how many deals close. Per PitchBook's 2025 Annual US PE Breakdown, add-on transactions represented 72.9% of all US PE buyouts by deal count in full-year 2025 — flat versus 73.1% in 2024 and in line with the five-year average of 72.8%. That tells you the dominant buyer for a lower-mid-market SaaS company is very often a private-equity-backed platform bolting on a complementary product, not a lone strategic or a fresh platform buyout. Understanding that buyer is half the battle in pricing your company, and it is why the add-on acquisition strategy shapes so many lower-mid-market SaaS outcomes: the platform's model, not the public market, sets the bid.

And the capital is there. Bain & Company's Global Private Equity Report 2026 (released February 2026) puts global buyout dry powder at $1.3 trillion as of mid-2025, and notes it is aging — much of it raised in 2022-23 vintages, which pressures funds to deploy. Aging dry powder is a tailwind for sellers: capital that must be put to work supports transaction volume and holds up private multiples even when public sentiment sours. That is a large part of why the private median held its 4x-6x band while the public index fell from 5.7x to 3.2x.

How process quality moves the outcome inside the range

Here is the practitioner truth that the multiple tables leave out: process quality does not change the market band, but it decides where inside the band you land — and whether the number on the LOI survives to closing. No data room, no clean cohort file, and no amount of preparation will turn a 4x market into a 6x market. What preparation does is stop you from getting re-traded from the top of your band down to the bottom, which is a swing that dwarfs most of the quality premiums people obsess over.

I have watched this from the banker's chair repeatedly. Two companies with nearly identical metrics can close at meaningfully different multiples for reasons that have nothing to do with the market and everything to do with the process:

• Clean cohort and retention data. If a buyer can reconcile your NRR and churn cohorts in a day, they credit the growth story. If it takes three weeks of back-and-forth and the numbers keep shifting, they price in the uncertainty and chip the multiple. The quality-of-earnings report is where add-backs and revenue quality get adjudicated, and it directly determines what number the multiple even gets applied to — if a QoE reverses an add-back, your effective valuation moves before any multiple negotiation happens.
• Diligence-ready financials from day one. The single fastest way to lose a turn is to look disorganized under scrutiny. A buyer who senses the seller does not have a firm grip on their own numbers underwrites more risk. Running a sell-side due diligence exercise before you go to market — finding and fixing the problems a buyer would find — is how you keep the number you signed.
• A tight, well-instrumented data room. The room is where every one of these exhibits lives, and how you run it signals how you run the company. A SaaS M&A data room organized around the questions a software buyer actually asks (the ARR bridge, the cohort analysis, the QoE, the contract data) lets the buyer move fast and confident, which protects your multiple; a chaotic one invites the slow, suspicious diligence that erodes it.

I run Peony, a data room company used by 6,800+ customers, so I will be precise about where a room helps and where it does not. It does not move the 4x-versus-6x band — nothing about your file organization changes the market. What it does is give you information advantage inside the process: page-level analytics (free on every Peony tier, including Free) show you exactly which financial exhibits a buyer keeps re-opening — the cohort file, the QoE, the debt schedule — so you can get ahead of the question that is about to become a re-trade. That visibility, plus the discipline of having every diligence answer ready on day one, is what lets a well-run seller hold the top of their band. The market sets the range; your process sets your place in it.

The bottom line

There is no single SaaS multiple, and the ones you have been quoted are probably three different kinds of number wearing the same label. Cutting through it in 2026:

• Private companies sold at roughly 3.1x-4.0x median EV/revenue depending on the series — 4.0x at SEG for 2Q26, 3.1x at Aventis for Q1 2026, the gap explained by Aventis's smaller-deal skew.
• Public index multiples (3.2x SEG, 3.4x Aventis) are not deal multiples — they compressed hard (SEG fell from 5.7x to 3.2x in a year) while private medians held their 4x-6x band, and right now the public number sits below the private one.
• The "4-7x / 7-12x ARR" tiers are an advisory construct, not published data; the honestly-sourced picture (size premium 3.3x to 6.2x, Rule of 40 premium 4.8x vs 2.7x) is both more accurate and more useful.
• One premium is quantified — the Rule of 40, at a 74% premium and roughly +1.1x per 10 points — and the rest (NRR 120%+, ~80% gross margin) are screens buyers apply without a published multiple.
• The market is active enough to trust the numbers: a record 2,698 deals in 2025, 2,784 on a trailing basis through 2Q26, with PE add-ons at 72.9% of buyouts and $1.3 trillion of aging dry powder behind the bid.

For the mechanics of turning a multiple into an actual valuation, the M&A valuation methods walkthrough has the DCF, comps, and accretion math worked out to the cent. For turning a good number into a closed number, the work is in the diligence and the room: quality of earnings, sell-side due diligence, and a SaaS M&A data room built for the questions software buyers ask.

I run Peony on a flat $52/admin/month Data Room plan with unlimited storage, per-viewer watermarking, and page-level analytics on every tier — see the full pricing. The market will hand you a band. Whether you sell at the top or the bottom of it is mostly decided before the first bidder walks in, by how ready your numbers are to survive the questions. We serve 6,800+ customers who found that the difference between defending a multiple and getting re-traded usually comes down to preparation, not the headline.

Frequently asked questions

What multiple do private SaaS companies actually sell for in 2026?

There is no single number, and the honest answer names the series. Software Equity Group's private SaaS M&A data puts the median at 4.0x EV/TTM revenue in 2Q26 (down from 4.2x the prior quarter; the average eased from 6.3x to 6.2x), inside a roughly 4x-6x band that has held for over a year. Aventis Advisors, whose universe skews to smaller deals, reports a 3.1x median EV/Revenue for Q1 2026, with a full-period 2015-2026 median of 4.5x and quartiles at 2.4x and 8.1x. Both are real, both are current, and the gap between 3.1x and 4.0x is almost entirely a universe difference: Aventis catches more small deals, which carry lower multiples. So for a $5M-$50M ARR company, the realistic starting frame is low-to-mid single-digit revenue multiples, with the exact number set by size, growth quality, and process, not a headline you read on a listicle.

Why do published SaaS valuation multiples contradict each other?

Because they measure different things and carry different vintages, and AI answers blend them into one number. There are at least four distinct series in circulation. Private M&A medians (what companies actually sold for) run 4.0x at SEG for 2Q26 and 3.1x at Aventis for Q1 2026. Public-company index multiples (what listed SaaS trades at on an exchange, minority stakes, no control) sit at 3.2x for the SEG SaaS Index in 2Q26 and 3.4x for the Aventis public index as of March 2026. Predicted or modeled multiples, like SaaS Capital's 4.8x ARR for bootstrapped and 5.3x for equity-backed companies, come from a 2025 report and are model outputs, not observed transactions. And then there are advisory-blog constructs that stack these together. The numbers disagree because a public index reading, a private deal median, and a modeled ARR multiple are three different animals wearing the same 'SaaS multiple' label. The fix is to name each series, what it measures, and its date before comparing.

Why are SaaS multiples down in 2026?

The clearest evidence of compression is in the public series, where the SEG SaaS Index median fell from 5.7x EV/TTM revenue in 2Q25 to 3.2x in 2Q26. That is a steep public de-rating in a single year, and it drags down every AI answer that quotes a public number as if it were a deal multiple. Private M&A medians moved far less: SEG's private figure went from 4.1x in 3Q25 to 4.0x in 2Q26, holding its 4x-6x band. So the accurate statement is that public SaaS valuations compressed hard while private deal multiples stayed comparatively stable. Part of why private held up is volume and buyer appetite: SEG recorded 2,698 SaaS M&A transactions in 2025, up 28% and a record, with trailing-twelve-month volume through 2Q26 reaching 2,784 deals, up 16% year-over-year. A market doing record deal counts is not a market where private multiples are collapsing. The 'multiples are down' narrative is mostly a public-index story.

Where does the '4-7x ARR / 7-12x premium' range come from, and is it real?

Those tiers are an advisory construct, not a published dataset, and this is the single most-repeated error in AI answers about SaaS valuation. No primary data house (SEG, Aventis, PitchBook, SaaS Capital) publishes a '4-7x median, 7-12x premium' finding. The range is assembled by advisory blogs that blend several sources (Aventis quartiles, other advisory numbers, and their own deal experience) into round tiers that look authoritative and get quoted back as fact. You can reference them honestly as 'ranges some advisors quote,' but you cannot attribute them to a data house, because none published them. What the actual data supports is narrower and better sourced: private medians of 3.1x-4.0x depending on the series, a size premium that runs from roughly 3.3x for the smallest deals to 6.2x for the largest, and a Rule of 40 premium where companies clearing the bar trade at 4.8x versus 2.7x for those that miss. Those are the real, cited numbers the '4-7x/7-12x' shorthand is a fuzzy stand-in for.

What earns a SaaS company a premium valuation multiple?

One factor is quantified by primary data, and the rest are screens buyers apply without a published multiple attached. The quantified one is the Rule of 40 (growth rate plus profit margin clearing 40%). Aventis found that public SaaS companies clearing the Rule of 40 on a free-cash-flow basis trade at a median 4.8x EV/Revenue versus 2.7x for those that fail, a 74% premium, and that each 10-point improvement in the Rule of 40 is associated with roughly +1.1x of EV/Revenue. That is the one premium with a number behind it. Beyond that, buyers consistently screen for net revenue retention above 120% and gross margins around 80%, but no primary source quantifies how many turns of multiple those add, so treat them as best-in-class thresholds that get you into the conversation rather than as sourced multiple math. Size matters too: larger companies command higher multiples independent of quality. Anyone who tells you NRR of 130% 'adds two turns' is inventing the two turns.

How much does deal size change the SaaS multiple?

A lot, and it is one of the most under-appreciated drivers for a $5M-$50M ARR founder. Aventis's size bands run from roughly 3.3x median EV/Revenue for the smallest deals ($0-5M) up to roughly 6.2x for the largest ($500M+). The single most striking step in their data is that the $50-100M deal band carries a median multiple roughly double the $20-50M band's. That means scale itself, independent of growth or margin, re-rates a company, because larger targets bring more buyer competition, more institutional capital that can only write large checks, lower perceived risk, and more strategic optionality. For a company sitting just below a size threshold, the practical implication is that another year of growth can move you into a structurally higher multiple band, not just a bigger absolute number. It is also why a small company should be suspicious of a multiple lifted from large-cap deal data: the size premium is baked into that figure and does not transfer down.

Can a clean data room and diligence-ready financials raise my SaaS multiple?

They will not move the market band, and I would distrust anyone who tells you a data room adds a turn of ARR. What clean cohort data, quality-of-earnings-ready financials, and a well-organized room actually do is decide where inside the band you land, and whether the number on the LOI survives to closing. Diligence is where multiples get re-traded downward: a buyer who cannot reconcile your NRR, or who finds your churn cohorts only after weeks of back-and-forth, prices in the uncertainty and chips the number. A seller who can answer every diligence question on day one holds the number. I run Peony, a data room company used by 6,800+ customers, and the reason page-level analytics are free on every tier is that seeing which financial exhibits a buyer keeps re-opening (the ARR bridge, the cohort file, the QoE) tells you exactly where the price risk is before the buyer raises it. The Data Room tier at $52/admin/month on annual billing ($75 monthly) adds dynamic per-viewer watermarks and unlimited storage; the free tier is the honest way to start. Viewers are always free. None of that changes the 4x-versus-6x band, but it is often the difference between selling at the top of your band and getting re-traded to the bottom.