Not affiliated with Reddit Inc. redditapis.com is an independent third-party REST proxy for Reddit's API.

Reddit API Pricing 2026: Every Provider Ranked by Cost per 1K

Reddit API pricing is not one number. It is a spread of at least six different pricing models that all claim to sell you the same thing, Reddit data, at prices that look nothing alike until you normalize them. One provider is free. One is enterprise-gated behind a review. One charges per call, one per credit, one per result, one per seat. Put a workload in front of each and the cost of pulling the same 1,000 posts ranges from zero to several dollars depending entirely on which model you land on and how you count.

This post ranks every serious Reddit data provider by real 2026 cost per 1,000 items pulled. Official Reddit Data API, PullPush, data365, redditapis.com, Apify, and the audience-research tools that people confuse for data APIs. Every price is either sourced from the provider's own public pricing at retrieval date or clearly framed as an estimate. No invented numbers.

TL;DR: In 2026 the cost of pulling 1,000 Reddit reads ranges from $0 (PullPush, free archive, no writes, no SLA) to about $4 (Apify scraper actors, estimate, plus a $45 per month rental). The official Reddit Data API is reported at $0.24 per 1,000 calls but is enterprise-gated with real minimums in the thousands per month and a mandatory pre-approval since November 2025. Self-serve managed access sits in the middle: redditapis.com at $2.00 per 1,000 reads with no floor. The catch that breaks most comparisons is that a call is not an item, so any per-call price must be normalized before you rank it.

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How much does the Reddit API cost in 2026?

There is no single Reddit API price in 2026, which is exactly why this question keeps getting the wrong answer. The official Reddit Data API is reported at an estimated $0.24 per 1,000 API calls, but that number is enterprise-gated and does not reflect what a small team actually pays. Free community APIs sit at zero. Managed self-serve providers sit in the low single dollars per 1,000 reads. Scraper marketplaces sit higher. The honest answer is a ranked table, not a figure, and the ranking below is ordered by pure cost per 1,000 reads with the caveats that matter attached to each row.

Here is the full leaderboard, ordered cheapest to most expensive on a per-1,000-reads basis, with each provider's floor and self-serve posture called out because those two columns change the real cost more than the headline rate does.

Rank	Provider	Cost per 1,000 reads	Pricing model	Monthly floor	Self-serve
1	PullPush	$0 (free)	Community archive	None	Yes
2	Reddit Data API	$0.24 per 1,000 calls (reported)	Per call, enterprise	Thousands per month (estimate)	No, pre-approval required
3	data365	About $0.60 per 1,000 (estimate)	Per credit	About $330 (EUR 300)	Yes
4	redditapis.com	$2.00 per 1,000 reads	Per call	$10 minimum credit	Yes
5	Apify (trudax)	About $4 per 1,000 results (estimate)	Rental plus usage	$45	Yes
n/a	GummySearch and successors	Seat-priced, not per item	Per seat, $29 to $199	$29	Yes, dashboard

Read the table with the caveats, not just the ranks. PullPush is cheapest because it is free, but it is read-only and historical-leaning with no uptime guarantee. The Reddit Data API is second-cheapest on paper but the hardest to actually buy. GummySearch and its successors are not ranked on cost per 1,000 items at all because they are seat-priced dashboards, not per-record data APIs. The developer question underneath all of this shows up constantly on r/redditdev, where the recurring thread is simply someone asking what the API actually costs.

r/redditdev·u/MurkyAppearance6298

Reddit API cost

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Open on Reddit

The rest of this post takes each provider in turn, shows where its published number comes from, and normalizes it to the same cost-per-1,000-items lens so the ranking holds up. For the sibling deep dive on one specific matchup, see /blogs/reddit-api-pricing-vs-apify, and for the operational throughput numbers behind these costs see /blogs/reddit-scraping-benchmarks-throughput-error-rates-2026.

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The six providers, and what each one actually sells

Before any price is comparable, the six providers need to be described in their own terms, because they are not the same product wearing different price tags. Two of them are first-party or first-party-adjacent, two are managed third-party APIs, one is a scraper marketplace, and one is an audience-research dashboard that people mistake for a data API. Lumping them into one table without noting what each sells is how buyers end up paying for the wrong thing. The matrix below fixes six providers against six dimensions that actually decide fit.

The columns that matter most are write access and self-serve. If you only need reads, more of the market opens up to you. The moment you need to write a comment, cast a vote, or send a DM, the scraper and archive paths fall away and you are choosing between the official Reddit Data API and a managed API like redditapis.com. Here is the short version of what each one is:

• PullPush is a free, community-run archive API. Best for historical research, weak on live data, cannot write.
• Reddit Data API is the first-party source. Complete and canonical, but enterprise-gated and slow to access.
• data365 is a managed multi-network data API with a credit-based subscription. Reddit is one of several networks it covers.
• redditapis.com is a managed pay-per-call REST API for reads, writes, votes, and DMs, priced per call with no tiers.
• Apify is an actor marketplace where independent developers publish Reddit scrapers that simulate browser sessions.
• GummySearch and its successors are seat-priced audience-research dashboards, not raw-data APIs.

For the write-side surface specifically, the DM endpoint docs and the full API documentation describe what a managed write API covers that a scraper never can. That capability gap is why write-heavy workloads rarely price-shop the same way read-only ones do. See /blogs/reddit-dm-vs-chat-vs-modmail-when-to-use-each-api-surface for the DM surface breakdown.

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The catch that breaks most comparisons: calls are not items

The most common pricing mistake is treating a per-call price as a per-item price, and it is the reason the official Reddit Data API looks either dirt cheap or wildly expensive depending on who is doing the math. A single listing call to the Reddit API returns up to 100 items. A single comment-tree call returns one post's replies. So the same estimated $0.24 per 1,000 calls maps to radically different per-item costs depending on whether your workload reads listings, reads posts plus their top comments, or recurses into full comment trees. Any honest ranking has to normalize per-call pricing to per-item first.

The three workload shapes produce three very different effective rates from the same headline number:

• Listings only returns up to 100 items per call, so 1,000 items cost about 25 calls once you account for pagination, or roughly six cents per 1,000 items.
• Posts plus top 10 comments needs the listing call plus one comment-tree call per post, so 1,000 items land around 1,020 calls, or an estimated $2.40 to $3.00 per 1,000 items.
• Full comment tree adds extra calls for deep threads, pushing 1,000 items to anywhere from 1,500 to 5,000 calls, or an estimated $3.60 to $12.00 per 1,000 items.

Here is the same idea in code. A listings pull and a comment-tree pull look almost identical to write, but they bill completely differently:

import requests

HEADERS = {"Authorization": "Bearer YOUR_TOKEN", "User-Agent": "pricing-demo/1.0"}

# One billable call, up to 100 items back. Cheap per item.
listings = requests.get(
    "https://oauth.reddit.com/r/python/new",
    headers=HEADERS,
    params={"limit": 100},
).json()
posts = listings["data"]["children"]

# One billable call PER POST for the comment tree. Expensive per item.
for post in posts:
    post_id = post["data"]["id"]
    comments = requests.get(
        f"https://oauth.reddit.com/comments/{post_id}",
        headers=HEADERS,
        params={"limit": 100, "depth": 2},
    ).json()
    # each of these is another billable call

The takeaway for the ranking: whenever a provider prices per call, credit, or compute unit rather than per item, you have to run this normalization before the number means anything. For the full call-budget mechanics and the rate-limit headers that govern this, see /blogs/reddit-api-rate-limits-2026 and the authentication setup at /blogs/reddit-api-authentication-oauth-2026.

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How we normalized every provider to cost per 1,000 items

The method behind this ranking is deliberately boring, because a boring method is an auditable one. Every provider was reduced to a single number, cost per 1,000 items pulled, using the same four steps regardless of whether the provider charges per call, per credit, per result, per compute unit, or per seat. Where a provider does not publish enough to compute the number exactly, the result is labeled an estimate and the assumption is stated. Nothing in the ranked table is a number we made up.

The four steps, applied to every provider in the table:

• Define the item. One post, one comment, or one record. This is fixed before any pricing is touched, so every provider is measured against the same unit.
• Count billable units per item. Calls, credits, results, or compute units. This is where the calls-are-not-items correction from the previous section gets applied.
• Add the fixed floor. Monthly rental, minimum spend, or seat cost, spread across the expected monthly volume. A $45 actor rental (Apify) is free at scale and painful at a hundred reads.
• Divide to per-1,000. Total monthly cost over thousands of items pulled, which produces the comparable number in the ranked table.

This is also exactly the calculation a buyer should run for their own volume, because the ranking shifts with scale. A fixed floor that dominates the cost at 10,000 reads per month disappears at 10 million. To model your own numbers instead of using the generic assumptions here, use /reddit-api-cost-calculator, and for the deeper REST-versus-library trade-off see /blogs/reddit-data-api-rest-vs-praw-2026.

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PullPush: the free tier of the entire market

PullPush is the cheapest provider in the ranking for the simplest possible reason: it is free. It is a community-run Reddit archive API, the spiritual successor to Pushshift, and its documentation lists no pricing, no API key requirement, and no paid plan. For historical research, academic work, and backfill jobs where the binding constraint is budget rather than freshness or reliability, nothing beats zero. That is a real and defensible top of the ranking, as long as you read the fine print on what free buys you.

What free does not buy you is the reason PullPush cannot be the only provider in a serious stack:

• No write access. PullPush reads Reddit data. It cannot post a comment, cast a vote, or send a DM.
• No service-level agreement. It is volunteer-run infrastructure. When it is down, it is down, and there is no support contract.
• Rate limits that can tighten without notice. A free community service tunes its limits to survive, not to guarantee your throughput.
• Continuity risk. Pushshift itself was shut down in 2023 as part of Reddit's policy shift. Any free archive carries the same tail risk. Broader web archives like Common Crawl exist but lag badly and undercover Reddit specifically.

The honest framing is that PullPush is the cheapest way to get historical Reddit data and a poor choice for anything customer-facing, real-time, or write-heavy. Teams commonly pair it with a paid live-data provider: PullPush for the cold archive, a managed API for the hot path. For the full archive-provider landscape and where PullPush fits among the Pushshift alternatives and others, see /blogs/best-pushshift-alternatives-2026.

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The official Reddit Data API: cheap on paper, gated in practice

The official Reddit Data API is the most misunderstood row in the ranking. On paper it is nearly the cheapest option at a reported $0.24 per 1,000 API calls, a figure that circulates from the 2023 pricing announcement and appears across developer writeups like the data365 pricing breakdown. In practice it is the hardest and most expensive path for a small team to actually use, because the number is not a self-serve rate card. Reddit does not publish standard pricing. You contact their team, describe your use case, pass a review, and receive a custom quote, and reported minimums start in the thousands of dollars per month.

Three things separate the on-paper rate from the real cost of the official path:

• No self-serve rate card. The estimated $0.24 per 1,000 calls figure is reported, not a checkout price. You get a custom quote after a review.
• Real minimums in the thousands. Reported commercial floors start around a thousand dollars per month, which dwarfs the per-call math at small volume.
• An approval gate on top. Since November 2025 every developer must be pre-approved before touching the API, including hobby projects.

The gate got higher in late 2025. As of November 11, 2025, Reddit's Responsible Builder Policy requires every developer to request and receive explicit approval before accessing Reddit data through the API, including for personal projects. So the true cost of the official API is not the per-call figure at all. It is the fixed floor plus the approval friction, which is why the monthly-floor chart tells the real story better than the per-call chart does.

The developer community has been vocal about this since the original 2023 change, which killed a generation of third-party apps and reshaped the entire pricing landscape that this post ranks. The reaction has stayed sharp even as Reddit later tried to court developers back:

Reddit Lies

@reddit_lies

A year ago Reddit changed it's API pricing in order to kill off 3rd party apps that community members had developed for free. Today Reddit announced the "Reddit Developer Fund" that will be used to pay developers up to $25,500 to develop 3rd party Reddit apps. Lol LMAO even htt… Show more

The frustration was never really about the per-call number in isolation. It was about how the pricing landed on developers who had built on the platform in good faith, a sentiment that showed up again and again in the immediate aftermath.

Vidit Bhargava

@viditb

Reddit’s API pricing choices are really bad, but what’s worse is the slander that Christian has had to go through. Horrible, horrid way to treat developers. Never using Reddit again.

The practical read for the ranking: the official Reddit Data API is the right choice when you need first-party, canonical, licensed data at enterprise scale and you have the budget and the patience for the approval process. It is the wrong choice for a prototype, a side project, or a small team that needs data this week. For the full access walkthrough see /blogs/reddit-data-api-2026, and for how the terms shape what you can build see Reddit's Data API Terms.

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redditapis.com: self-serve pay-per-call in the middle of the ranking

redditapis.com sits fourth in the ranking at $2.00 per 1,000 reads, and its position is a deliberate trade. It is more expensive per read than PullPush (free) and the official API's on-paper rate (an estimated $0.24 per 1,000 calls, reported), and cheaper than the Apify scraper path. What it buys for that middle price is the thing the cheaper rows lack: self-serve access with no contract, no approval review, no monthly minimum, and a write surface that PullPush and the scrapers do not have. The pricing is a flat per-call model with no tiers, which is what makes it easy to rank against everything else.

The full rate card, taken from the live pricing page at retrieval date, is a pure pay-per-call model:

• Reads (GET): $0.002 per call, which is $2.00 per 1,000 reads.
• Votes: $0.005 per call, which is $5.00 per 1,000 votes.
• Writes (comments, profile edits): $0.012 per call, which is $12.00 per 1,000 writes.
• Direct messages: $0.025 per call, which is $25.00 per 1,000 DMs.

There are no monthly subscriptions, no tier caps, and no minimum spend beyond a $10 smallest credit purchase. Credits never expire, and signup includes $0.50 in free credit with no card required, which is roughly 250 reads to test against your own workload before you commit. A read call looks like this:

curl -H "Authorization: Bearer YOUR_KEY" \
  "https://api.redditapis.com/api/reddit/search?q=api%20pricing&limit=25"

The reason this row exists in the middle rather than at the bottom is engineering overhead, which the raw per-read number hides. The official API is cheaper per call but you build OAuth handling, token pools, and retry logic yourself, the work that libraries like PRAW automate for the direct path. A managed pay-per-call API folds that work into the price. For the direct comparison of that trade-off see /blogs/praw-vs-redditapis-rest-2026, and to get a key see /signup.

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Apify: the scraper path at the top of the cost range

Apify sits at the expensive end of the ranking, at roughly $4 per 1,000 results plus a $45 per month actor rental, and both of those numbers come with an estimate flag for good reason. Apify is not a Reddit-specific product. It is an actor marketplace where independent developers publish scrapers that simulate browser sessions against Reddit's web frontend. The most-installed Reddit actor, trudax/reddit-scraper, lists a $45 per month rental fee (Apify) plus Apify platform usage, and Apify's own documentation offers the illustrative benchmark of roughly 1,000 results for less than $4 in platform credits (estimate).

Three things make the Apify number an estimate rather than a fixed rate, and all three matter for the ranking:

• Actor pricing is independent developer code. The maintainer can change the price month to month, and has incentive to as Reddit hardens its bot detection and raises the actor's compute cost.
• Compute varies with page weight. You pay for CPU seconds and memory, so a comment-heavy workload on a heavy Reddit page costs more per result than a light listings pull.
• Platform usage stacks on the rental. The $45 actor rental (Apify) is the floor, not the total. Platform compute is billed on top and gets cheaper on higher Apify subscription plans.

The counterintuitive appeal of the scraper path is that it can win at burst scale for internal, freshness-tolerant workloads, where parallel actor runs move a large one-time pull faster than negotiating an enterprise Reddit API tier. Some developers go further and build their own scraper to sidestep both the official pricing and the actor fees, a route this popular walkthrough documents end to end:

The trade-off in every scraper case is reliability variance and the compliance posture, both covered later in this post. For the current live pricing always check the Apify actor page and Apify platform pricing, and for the deep head-to-head see /blogs/reddit-api-pricing-vs-apify. Proxy costs also factor in at scale, covered in /blogs/best-residential-proxies-reddit-scraping-2026.

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data365 and the credit model

data365 lands third in the ranking at an estimated $0.60 per 1,000 items, and the estimate flag is doing real work here because the provider prices in credits rather than in items. Its published plans, taken from the data365 Reddit page at retrieval date, are a Basic tier at EUR 300 per month for one social network with 500,000 credits, a Standard tier at EUR 850 per month for three networks with 1,000,000 credits, and a Custom tier for larger volumes. The page does not disclose how many credits one Reddit item consumes, so the per-1,000-items number is derived by assuming a rough one-credit-per-item mapping at the Basic tier.

Under that assumption the math is straightforward, and the assumption is stated so a reader can adjust it:

• Basic: EUR 300 per month buys 500,000 credits. At one credit per item that is EUR 0.0006 per item, or about EUR 0.60 per 1,000 items, an estimated $0.60 at 2026 exchange rates.
• The floor bites at low volume. The EUR 300 monthly minimum means a team pulling only 50,000 items per month is effectively paying about EUR 6 per 1,000 items, ten times the headline rate.
• Multi-network is the real pitch. data365 covers several social networks, so its value is highest for teams that need Reddit plus other platforms from one contract, not for Reddit-only buyers.

The honest ranking note is that data365 looks cheap per item at high volume and expensive at low volume, because the monthly floor dominates until you cross a few hundred thousand items per month. If the credit-to-item ratio is higher than one, the effective cost rises accordingly, which is why the row is flagged as an estimate rather than presented as a fact. For teams comparing managed multi-network options against a Reddit-focused API, /blogs/subreddit-analytics-api-comparison covers the analytics-surface trade-offs.

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GummySearch and the audience-research tools that are not data APIs

GummySearch and its successors are in this post to correct a category error, not to be ranked on cost per 1,000 items, because they do not sell items. GummySearch was a Reddit audience-research dashboard, priced per seat from a free tier up to a $199 per month Mega plan, and it announced it is closing on November 30, 2025. Tools in this category, including the successors that are absorbing its users, are seat-priced software for humans clicking through insights, not per-record APIs for machines pulling data. Comparing them on cost per 1,000 items is a units mismatch.

The distinction matters because buyers routinely conflate the two and end up with the wrong tool:

Question	Audience-research dashboard	Raw data API
Who is it for	A marketer clicking through insights	A developer pulling records
Pricing unit	Per seat, per month	Per item or per call
Output	Charts and reports in a UI	JSON records over HTTP
Fits this ranking	No, seat-priced	Yes, per-item

The published GummySearch tiers, from its pricing page at retrieval date, ran from a free plan limited to 50 keyword searches, to a $29 Starter, a $59 Pro, and a $199 Mega plan. None of that is a per-item rate, so none of it belongs in the cost-per-1,000-items table. If what you actually need is programmatic Reddit data at a per-item price, a dashboard is the wrong purchase regardless of its monthly cost. For the successor landscape after the shutdown, see /blogs/gummysearch-alternatives-ranked-by-data-depth-2026.

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Total cost of ownership at 100K and 1M reads per month

The ranking flips depending on volume, which is why a single cost-per-1,000 number is necessary but not sufficient. The fixed floors that barely register at a million reads per month dominate the bill at a hundred thousand, and the per-item rates that look expensive at low volume compound into the biggest lines at high volume. Modeling two concrete volume tiers, 100,000 and 1,000,000 reads per month, shows how the order shuffles and where each provider's economics actually make sense.

At 100,000 reads per month the fixed floors matter most, and the order tracks the per-read rate closely once floors are added. PullPush is free. The official Reddit API direct is an estimated $24 in pure call cost but gated behind its enterprise minimum, so the real number is the floor, not the $24. data365 is dominated by its roughly $330 monthly floor. redditapis.com lands around $200 at $2.00 per 1,000 reads with no floor. Apify lands around $400 as an estimate once the rental and platform usage stack up.

At 1,000,000 reads per month the per-read rate dominates and the floors fade, as the same chart from earlier in this post showed:

• PullPush: still free, still read-only, still no SLA.
• Reddit Data API direct: around $240 in call cost at the reported rate, plus the enterprise agreement and the token-pool engineering you build yourself.
• data365: around $600 at the estimated per-item rate, floor now negligible.
• redditapis.com: around $2,000 at $2.00 per 1,000 reads, no engineering overhead.
• Apify: around $4,000 as an estimate, plus the reliability variance of scraper actors.

The pattern across both tiers is consistent: the cheapest pure-dollar options carry the most hidden engineering or reliability cost, and the managed options trade a higher per-read rate for lower total cost of ownership once you price your own engineering time. For the operational numbers behind these estimates see /blogs/reddit-scraping-benchmarks-throughput-error-rates-2026, and for the Python patterns that keep the call count down see /blogs/reddit-api-python-tutorial.

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Access model and compliance posture

Price is only half the decision, because two providers at the same cost per 1,000 items can carry wildly different risk, and for anything customer-facing the risk column can outweigh the price column entirely. The access model, meaning how each provider actually reaches Reddit's data, determines whether the data source is defensible in front of an enterprise procurement team and whether it can vanish without warning. Ranking on cost alone ignores the dimension that most often kills a data source in production.

The four providers split cleanly on risk posture, and the split does not track price:

• Reddit Data API is first-party and licensed, the most defensible on procurement grounds, with versioned schemas. Its risk is policy shifts, which have happened before and reshaped the market.
• redditapis.com is a managed third-party proxy with stable schemas and a real uptime posture. Its risk is vendor concentration, the same as any managed provider.
• PullPush is a community archive on legally unsettled terms, with continuity risk because it is volunteer-run.
• Apify reaches data by simulating browser sessions outside the authenticated API, with brittle schemas that break when Reddit changes its frontend and recover on the maintainer's timeline.

The developer-side debate on where scraping sits relative to the terms of service has run for years, and the recurring r/redditdev threads on request definitions and access rules are the best contemporaneous record of how the community reads the line. The pricing question itself keeps resurfacing there as teams re-evaluate their access path:

r/redditdev·u/Amraksin

Reddit API Pricing

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For products sold to regulated buyers, the first-party or licensed-managed paths clear procurement in a way the scraper path does not. For internal analytics where occasional gaps are acceptable, the cheaper unsettled-terms paths are often fine. The point for the ranking is that the cheapest row is not automatically the right row once compliance enters the decision.

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Which provider should you pick

The ranking answers cheapest, but cheapest is rarely the right question, so the decision collapses to matching the tool to the workload rather than chasing the lowest per-1,000 number. Four workload shapes cover almost every real case, and each points cleanly at a provider or a small set of them. The decision tree below is the one this whole post builds toward: not a single winner, but the right winner for each job.

The four cuts, mapped to the ranking:

• Historical research, no writes, budget-bound: PullPush. Free, deep archive, accept the no-SLA trade.
• Self-serve reads and writes, no contract, ship this week: redditapis.com. Pay-per-call, write surface, no approval gate.
• Enterprise licensed data at scale, procurement-sensitive: the official Reddit Data API. Budget and patience required.
• Audience research in a dashboard, not raw data: a seat-priced tool, and know you are buying software, not an API.

The spread across the whole market is the headline finding, and it is wider than most buyers expect going in. The distance from the cheapest usable per-read rate to the most expensive is large, and the November 2025 pre-approval requirement changed the calculus for the official path specifically.

If your workload needs live reads plus writes without a procurement cycle, the self-serve managed path is the pragmatic pick, and you can test it against your own workload with the $0.50 free credit at signup before committing a dollar. If your workload is historical and budget is the only constraint, start free with PullPush. If you are an enterprise with a procurement team and a real budget, the official Reddit Data API is the canonical source and worth the process. For the full REST-versus-library decision that sits underneath the managed path, see /blogs/reddit-data-api-rest-vs-praw-2026.

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The verdict

Reddit API pricing in 2026 is a spread, not a number, and the spread runs from free to several dollars per 1,000 reads depending on which of six providers you pick and how you count. The one-line summary of the ranking:

• Cheapest raw: PullPush, free, read-only, no SLA.
• Cheapest on paper, hardest to buy: the official Reddit Data API, enterprise-gated.
• Best self-serve balance: redditapis.com at $2.00 per 1,000 reads, writes included, no floor.
• Top of the cost range: Apify scraper actors, with reliability and compliance trade-offs.

PullPush wins on pure cost because it is free, but only for read-only historical work with no SLA. The official Reddit Data API is cheapest on paper and hardest to actually buy, gated behind an enterprise review and, since November 2025, a mandatory pre-approval. data365 is cheap at high volume and floor-bound at low volume. Apify sits at the top of the cost range with the reliability and compliance trade-offs of the scraper path. redditapis.com sits in the middle at $2.00 per 1,000 reads, trading a higher per-read rate for self-serve access, a write surface, and zero engineering overhead.

The number that decides your bill is not the headline rate. It is the cost per 1,000 items after you fix the item, count the billable units, add the floor, and divide, run for your real volume and your real workload shape. Do that math and the ranking will reorder itself around your job. To model your own volume against every provider in this post, use /reddit-api-cost-calculator. To test the self-serve managed rate directly, sign up for the $0.50 free credit and pull your own workload before you commit, or view pricing to run the numbers first.