---
title: "Parallel Search API Pricing 2026: $1.00 per 1,000 Requests"
category: "comparisons"
url: https://keirolabs.cloud/blog/parallel-search-api-pricing-2026
---
Parallel Search API pricing in 2026 is the most underrated number in the search API market. I have been reading the price cards in this category since 2025, and Parallel's Turbo line is the one that made me stop and look twice. Everyone is comparing the wrong numbers. The industry treats Perplexity's flat $5.00 per 1,000 as the benchmark for agent-ready search, while Parallel's Turbo mode sits at $1.00 per 1,000 with a roughly 200ms median latency. That is five times cheaper at a fraction of the latency, and almost nobody is talking about it. The price cards split into two tiers this year, and the teams still paying $5.00 for what costs $1.00 are about to discover it on the invoice.
Every number below was re-verified against Parallel's own price cards on September 20, 2026.
> **TL;DR**: Parallel Search API costs **$1.00 per 1,000 requests on Turbo mode** in 2026, with **5,000 free requests a month plus $5 in monthly credits**, and Turbo is **5x cheaper than Perplexity's flat $5.00/1K** at roughly 200ms median latency. Basic and Advanced modes cost $5.00/1K, extra results bill +$1.00/1K, and the rate limit is 600 requests per minute.
The providers priced in this comparison.
## What does Parallel Search API cost per 1,000 requests in 2026?
**Parallel Search API charges $1.00 per 1,000 requests on Turbo mode, $5.00 per 1,000 on Basic and Advanced modes, and $1.00 per 1,000 for every result beyond the default 10, as of 2026.** The free tier is 5,000 requests a month plus $5 in monthly credits, and the rate limit on Turbo is 600 requests per minute.
The full price table is on [Parallel's pricing page](https://parallel.ai/pricing) and the [pricing docs](https://docs.parallel.ai/getting-started/pricing), and it is shorter than most in this category. Three modes, one index, two prices. Turbo is the headline at $1.00 per 1,000. Basic and Advanced both run $5.00 per 1,000. The difference between the modes is depth and latency, not the base price.
| Parallel mode | Price per 1,000 | Median latency | Default results |
|---|---|---|---|
| **Turbo** | **$1.00** | ~200ms (p50) | 10 |
| Basic | $5.00 | ~1s | 10 |
| Advanced | $5.00 | ~3s | 10 |
The extra-results meter is the fine print. Every result past the default 10 bills another $1.00 per 1,000. A 20-result Turbo search is $2.00 per 1,000, not $1.00. The free tier is 5,000 requests a month plus $5 in monthly credits, which is the largest raw allowance in the category.
The pricing model is flat and predictable. There are no token fees, no per-query surcharges, and no committed-use tiers on the search endpoints. The invoice is the request count times the mode price, plus the extra-results meter. That is the whole model, and it is the reason Parallel is the easiest agent-ready API to budget against.
The flat model is the quiet advantage. Token-metered rivals hand the uncertainty to you, because a single grounded answer can run 500 to 1,500 output tokens and every search you feed it adds input tokens on top. Parallel's $1.00 per 1,000 is the whole price, and the invoice cannot surprise you when an agent decides to write longer answers. That predictability is worth real money at scale, and it is the reason the flat-rate tier keeps winning production workloads.
## What is the difference between Parallel Turbo, Basic, and Advanced modes?
**Parallel's three modes price the same search index at different depths: Turbo returns 10 results in about 200ms for $1.00/1K, Basic takes about 1 second for $5.00/1K, and Advanced takes about 3 seconds for $5.00/1K.** The mode you pick trades latency and depth against the same base price.
Turbo is the mode Parallel built for agents. It is the one the company benchmarks against Perplexity in its [Turbo announcement](https://parallel.ai/blog/parallel-search-turbo), and the one that makes the 5x claim possible. Basic and Advanced are the deeper retrieval modes, priced at $5.00 per 1,000, and they exist for workloads that need more than a fast pass over the index.
| Mode | Price / 1K | Latency | Best for |
|---|---|---|---|
| **Turbo** | **$1.00** | ~200ms | Real-time agents, chat, autocomplete |
| Basic | $5.00 | ~1s | Standard retrieval, offline jobs |
| Advanced | $5.00 | ~3s | Deep research, complex queries |
The pricing logic is worth stating plainly. **Parallel charges $1.00 for the fast pass and $5.00 for the deep pass, and the deep pass is the same price as Perplexity's only mode.** That is the whole model. If you need speed, you pay a fifth of the market rate. If you need depth, you pay the market rate. The default 10 results come with every mode, and every result past 10 bills the same $1.00 per 1,000 regardless of mode.
Which mode should you run? If your agent needs an answer in real time, Turbo is the only mode that makes sense, because 200ms is the difference between a conversation and a wait. If your workload is offline research, Basic and Advanced buy depth at the same $5.00 price, and the 1 to 3 second latency is irrelevant when nothing is waiting on the result.
The mode choice also changes your unit economics. At one million requests a month, Turbo is $1,000 and Basic or Advanced is $5,000, a 5x spread on the same index. Teams that default to the deep mode out of habit are paying for depth they do not use, and the habit is expensive. The default should always be Turbo, with Basic and Advanced reserved for the queries that actually need them.
## Does Parallel Search API have a free tier in 2026?
**Yes. Parallel gives every account 5,000 free requests a month plus $5 in free monthly credits, the largest raw free allowance in the search API category.** Serper hands out 2,500 searches, Keirolabs gives 1,000 queries, Brave credits $5, and Tavily gives 1,000 credits.
The free tier is the number most pricing pages bury. Parallel does not give you a trial that expires. It gives you 5,000 requests every month, plus $5 in credits on top, no card required. That is enough to run a real prototype through a full development cycle, and it is the largest raw allowance in the category.
| Provider | Free allowance per month | Notes |
|---|---|---|
| **Parallel** | 5,000 requests + $5 credits | Largest raw number in the category |
| **Serper** | 2,500 searches | SERP results only |
| **Keirolabs** | 1,000 queries | Covers every endpoint |
| **Brave** | ~1,000 requests ($5 in credits) | Credits, not a tier |
| **Tavily** | 1,000 credits (1,000 basic searches) | Advanced search costs 2 credits |
| **Exa** | $20 signup + $10/mo | ~1,400 searches a month recurring |
| **SerpAPI** | 250 searches | Smallest free allowance here |
The free tier comparison matters for one reason: it lets you pass the identical query to every provider for nothing and read what each one sends back. I ran this exact test while writing this post. Parallel's 5,000 requests plus $5 in credits covers a serious prototype, and it is the reason Parallel is the easiest agent-ready API to try before you spend. The credits and the free requests stack, so a new account can run roughly 5,000 to 10,000 calls in the first month without a bill.
The free allowance also tells you how each vendor thinks about acquisition. Parallel gives away the most because it wants you inside the platform, where the Task API and the Responses API live. Keirolabs gives away 1,000 queries because its whole rate card is cheap enough that the free tier is a rounding error. The size of the free tier is a signal about the size of the bill that comes after it.
## What are Parallel Search API's rate limits?
**Parallel caps Turbo at 600 requests per minute, a limit shared with the Extract API, which is 10 requests per second of sustained headroom and enough for most production agents without a queue.** The limit is per minute, not per second, which matters for bursty agent workloads.
600 requests per minute is 10 per second sustained. For a single agent that is generous. For a fleet of agents behind one key it is the number that decides whether you need a queue, a cache, or a second key. The shared limit with Extract is the detail most pricing pages miss: if your pipeline runs search and extraction on the same key, they draw from the same 600 per minute.
| Provider | Rate limit | Notes |
|---|---|---|
| **Parallel Turbo** | 600 req/min | Shared with Extract |
| **Brave Search** | 50 QPS | 2 QPS on Answers plan |
| **Exa free tier** | 5 QPS | 10 QPS on developer plan |
| **Keirolabs** | 1,000 queries/mo free | No card required |
The practical read: for high-volume agent workloads, rate limits are a bigger constraint than price at the low end. The sub-dollar tier moves volume. The $5.00-8.00 tier moves fidelity at lower throughput. Parallel's 600 per minute is the middle ground, and it is enough to run a real product without a phone call. The teams that ignore the shared limit with Extract discover it the hard way when a traffic spike hits the ceiling mid-pipeline.
The per-minute shape matters more than the raw number. A 600 per minute limit lets a burst of 600 requests through in one second, then forces a wait. A 10 QPS limit spreads the same traffic evenly and never bursts. For agent workloads that fire a batch of searches at once, the per-minute limit is friendlier. For steady streaming traffic, a per-second limit is easier to reason about. Know which shape you are buying before you build the queue.
## How much do extra results cost on Parallel Search API?
**Every result beyond the default 10 bills an additional $1.00 per 1,000, so a 20-result Turbo search costs $2.00 per 1,000 and a 30-result search costs $3.00 per 1,000.** The extra-results meter is the fine print that turns Parallel's headline price into a range.
The default is 10 results per call on every mode. If 10 is enough, the price is the headline price. If you need 20, the price doubles. If you need 30, it triples. The meter is flat at $1.00 per 1,000 per extra result, which is the same rate as the base Turbo call, so the arithmetic is easy to run.
| Results per call | Turbo price per 1,000 |
|---|---|
| 10 (default) | $1.00 |
| 20 | $2.00 |
| 30 | $3.00 |
| 50 | $5.00 |
Compare that to Exa, where the base $7.00 covers 10 results and every result past 10 bills another $1.00 per 1,000, so a 30-result Exa search costs $27.00 per 1,000, not $7.00. Parallel's extra-results meter is the same shape but a different base, and the base is what makes the difference. The teams that quote Parallel's $1.00 without reading the meter are quoting a floor, not a bill. The meter is also the reason the mode table and the results table have to be read together: the mode sets the base, and the results set the multiplier.
## How does Parallel Search API pricing compare to Perplexity, Tavily, Exa, and Keirolabs?
**Parallel Turbo at $1.00/1K is the cheapest agent-ready search API in the market, 5x cheaper than Perplexity's flat $5.00/1K, cheaper than Brave at $5.00, Exa at $7.00, and Tavily at $8.00, and only Keirolabs at $0.25/1K semantic and $0.10/1K SERP undercuts it.** The full 2026 price table is below.
On a like-for-like basis, the agent-ready tier runs from $1.00 to $8.00 per 1,000, and Parallel Turbo owns the bottom of it. Perplexity is a flat $5.00 per 1,000 with no token charges, per Parallel's published comparison. Brave is $5.00 per 1,000 from its own index. Exa is $7.00 per 1,000 for 10 results. Tavily is $8.00 per 1,000 at pay-as-you-go. Keirolabs sits below the whole tier at $0.25 per 1,000 semantic and $0.10 per 1,000 SERP.
| Provider | Base $/1K | Free tier | What the base price covers |
|---|---|---|---|
| **Keirolabs SERP** | **$0.10** | 1,000 queries/mo | Raw SERP results |
| **Keirolabs semantic** | **$0.25** | 1,000 queries/mo | Semantic search + clean content, one call |
| Serper | $0.30-1.00 | 2,500 searches/mo | Raw Google SERP, no extraction |
| **Parallel Turbo** | **$1.00** | 5,000 req/mo + $5 | Search + excerpts, 10 results, ~200ms |
| Parallel Basic/Advanced | $5.00 | 5,000 req/mo + $5 | Deeper retrieval modes |
| Brave Search | $5.00 | $5 credits/mo | LLM-ready results from Brave's own index |
| Perplexity Search API | ~$5.00 | None | Search + citations, flat rate |
| Exa | $7.00 | $20 + $10/mo | 10 results; +$1/1K per extra result |
| Tavily | $8.00 | 1,000 credits/mo | Basic search at 1 credit; advanced costs 2 |
| SerpAPI | $3.75-25.00 | 250 searches/mo | SERP scraping, many engines |
| OpenAI web search | $10-14 | None | Frontier-model search, tokens on top |
The footnote column is where the real rate lives. Exa's $7 covers ten results, and every result past ten bills another $1 per 1,000, so a 30-result search costs $27 per 1,000, not $7. Tavily's pay-as-you-go is $8 per 1,000 basic searches, and advanced search costs 2 credits, $16 per 1,000. Perplexity and OpenAI figures come from Parallel's published comparison and should be rechecked on the day you commit. What the landing page quotes and what the invoice charges are different numbers on every one of them, and the cheapest headline is the one that needs the most footnotes.
The comparison also has to account for what each vendor includes in the base price. Parallel Turbo includes excerpts in the search response, so the $1.00 buys a result a model can read. Keirolabs includes extracted content in the same call at $0.25. Brave returns an LLM-context block at $5.00. Serper returns raw links at $0.30-1.00 and stops. The base price is only comparable when the output is comparable, and the output is not comparable across the raw tier and the agent-ready tier.
Base cost per 1,000 requests, 2026. Keirolabs SERP $0.10, semantic $0.25; Serper $0.30-1.00; Parallel Turbo $1.00; Brave and Perplexity $5.00; Exa $7.00; Tavily $8.00.
## Why is Parallel Turbo the cheapest agent-ready search API in 2026?
**Parallel Turbo is the cheapest agent-ready search API because it prices a 200ms search with 10 excerpts at $1.00/1K, while Perplexity charges a flat $5.00/1K for the same category of result and the fast-search tier runs $5-7/1K.** The 5x gap is not a discount. It is a different cost structure.
Parallel's own [published comparison](https://parallel.ai/blog/parallel-search-turbo) makes the claim directly: Perplexity Search API is a flat $5.00 per 1,000 with no token charges, and Parallel Turbo is 5x cheaper. The same comparison puts SERP APIs at roughly $1.00 per 1,000, fast search APIs like Exa Instant and Tavily at $5-7 per 1,000, and frontier model search like OpenAI Web Search at $10-14 per 1,000.
The reason the gap exists is structural. **Perplexity prices its search as a finished product with a flat rate. Parallel prices Turbo as a commodity lane and makes its money on the deep modes and the rest of the platform.** That is why Turbo can sit at $1.00 while Basic and Advanced sit at $5.00. The cheap lane is the customer acquisition. The expensive lanes are the margin.
Parallel Search API price per 1,000 requests by mode, 2026. Turbo is the $1.00 lane; Basic and Advanced are the $5.00 deep lanes.
The "agent-ready" qualifier is the whole argument. SERP APIs at $1.00 per 1,000 return raw links and stop. Your pipeline then has to download each page, strip the chrome, pull the text, chunk it, and score it for relevance before a model can read anything. Parallel Turbo returns 10 results with excerpts in one call at 200ms. The $1.00 is the whole price, and the work is done. That is why the honest comparison is not $1.00 against $1.00. It is $1.00 against $1.00 plus the pipeline you have to build and run.
The 5x claim also survives the extra-results meter. A 20-result Perplexity search is still $5.00 per 1,000, because Perplexity's flat rate does not scale with results. A 20-result Parallel Turbo search is $2.00 per 1,000, still 2.5x cheaper. Even at 30 results, Parallel is $3.00 per 1,000, and Perplexity is $5.00. The meter narrows the gap but does not close it, and at the default 10 results the gap is the full 5x.
## How fast is Parallel Search API compared to its rivals?
**Parallel Turbo runs at roughly 200ms median latency (p50), Basic at about 1 second, and Advanced at about 3 seconds, against Brave's measured 669ms and Tavily's 998ms.** Speed is not a footnote in an agent loop, it compounds across every step.
In a multi-turn agent run, search latency stacks onto every step. Five searches back to back is one second on Parallel Turbo and five seconds on Tavily. A sluggish endpoint can drag a snappy agent out to a 30-second wait, and the wait is the product. Parallel's Turbo number is a vendor claim at p50, and the Basic and Advanced numbers are vendor claims too, but they are the numbers Parallel publishes and the only ones on the table.
| Provider / mode | Median latency | How measured |
|---|---|---|
| **Parallel Turbo** | ~200ms | Vendor claim (p50) |
| Exa Fast / Instant | Sub-425ms / sub-200ms | Vendor claim |
| **Parallel Basic** | ~1s | Vendor claim |
| Brave Search | 669ms | AIMultiple benchmark, measured |
| Tavily | 998ms | AIMultiple benchmark, measured |
| **Parallel Advanced** | ~3s | Vendor claim |
Median latency, 2026. Parallel Turbo ~200ms, Basic ~1s, Advanced ~3s (vendor claims); Brave 669ms and Tavily 998ms (AIMultiple, measured).
The latency spread inside Parallel's own platform is the pricing story in miniature. Turbo at 200ms is the agent lane. Advanced at 3 seconds is the research lane. They cost the same $5.00 per 1,000 on the deep modes, and the difference is what you are willing to wait for. For a real-time agent, 200ms is the only number that matters. For a batch research job, the 3-second Advanced mode is the same price as the 1-second Basic mode, and the depth is the differentiator.
## What are the other Parallel APIs and what do they cost?
**Parallel's platform spans five APIs beyond search: Task API for deep research at $5 to $2,400 per 1K runs by processor, Extract at $1 per 1K URLs, Responses at $10-$250 per 1K, Monitor at $3-$10 per 1K, and Entity Search at $5 per 1K with 100 results included.** Search is the entry point, not the product.
The Task API is the deep research lane, priced by processor from lite at $5.00 per 1,000 runs to ultra8x at $2,400 per 1,000 runs. That is the top of Parallel's price ladder, and it is where the platform makes its margin. The Extract API at $1.00 per 1,000 URLs is the same price as Turbo search, which tells you how Parallel thinks about extraction: it is a commodity lane too. The Responses API at $10-$250 per 1,000 is the OpenAI-compatible lane, and the Monitor API at $3-$10 per 1,000 is the observability lane. Entity Search at $5.00 per 1,000 with 100 results included is the structured data lane.
| Parallel API | Price | What it does |
|---|---|---|
| Search (Turbo) | $1.00 / 1K | Fast web search, 10 results, ~200ms |
| Search (Basic/Advanced) | $5.00 / 1K | Deeper retrieval modes |
| Task API | $5-$2,400 / 1K runs | Deep research, by processor (lite to ultra8x) |
| Extract API | $1.00 / 1K URLs | Structured extraction from URLs |
| Responses API | $10-$250 / 1K | OpenAI-compatible responses |
| Monitor API | $3-$10 / 1K | Monitoring executions |
| Entity Search | $5.00 / 1K | Entity search, 100 results included |
The platform logic is clear. **Parallel prices the commodity lanes at $1.00 and the compute lanes at $5.00 and up, and search is the cheapest way into the platform.** A team that starts on Turbo search at $1.00 per 1,000 can graduate to Task API deep research without changing vendors. That is the moat, and it is priced to be walked into. The full platform price list is on [Parallel's pricing page](https://parallel.ai/pricing), and the search endpoints are the cheapest lane on it.
The price ladder also explains why Parallel can afford to sell Turbo at $1.00. The Task API at up to $2,400 per 1,000 runs is where the compute margin lives, and the Responses API at $10-$250 per 1,000 is the enterprise lane. Search is the loss leader that feeds the rest of the platform. That is a deliberate structure, and it is the reason the search price is stable while the compute prices flex by processor.
## When is Parallel Search API worth it?
**Parallel is worth it when you need agent-ready search at $1.00/1K with 200ms latency and a 600 req/min limit, and it is not worth it when your workload is simple enough for Keirolabs at $0.25/1K semantic or $0.10/1K SERP.** The decision rule is short because the tier split settles it in one step.
The market now runs two lanes. The raw-data lane runs $0.10-1.00 per 1,000 and hands you the work. The agent-ready lane runs $1.00-8.00 per 1,000 and does the work for you. Parallel Turbo is the cheapest way into the agent-ready lane, and Keirolabs is the cheapest way into the lane below it. Match the lane to your workload, then match the vendor to the lane.
| Workload | Pick | Why |
|---|---|---|
| Agent needs answers, not links | **Keirolabs** $0.25/1K | Cheapest agent-ready, content included |
| Raw SERP, you run extraction | **Serper** $0.30-1.00 | Cheapest raw tier |
| High-volume, latency-critical | **Parallel Turbo** $1.00 | Fastest and cheap |
| Deep research, turnkey | **Parallel Task API** $5-$2,400 | Processor-scaled research |
| Privacy-sensitive, own-index bias | **Brave** $5.00 | Owns index, fastest measured |
| Research workflow, turnkey | **Tavily** $8.00 | Native agent integrations |
The waste case is specific. If you are paying Parallel's $5.00 Basic or Advanced mode for a workload that Turbo handles, you are paying 5x for depth you do not use. If you are paying Parallel's $1.00 Turbo and still building your own extraction on top of the excerpts, you are paying agent-ready prices and doing the raw-tier work. Pick the mode first. The vendor is a much smaller decision.
## Parallel vs Keirolabs: two ways to build the same agent
**The same agent can be built on Parallel Turbo at $1.00/1K or on Keirolabs at $0.25/1K semantic and $0.10/1K SERP, and the difference is the shape of the call, not the quality of the answer.** Parallel wins on latency at 200ms. Keirolabs wins on price at 4x cheaper.
On output quality, the top vendors sit closer together than their prices suggest. Keirolabs scores 78% on FinanceBench against roughly 19% for a standard GPT-4o plus vector RAG baseline, and 84% on SimpleQA. The vendors are competing on the same retrieval problem, and the differences at the top are smaller than the 4x to 20x price gap between them.
The benchmark numbers are the part most pricing comparisons skip. FinanceBench measures how well a retrieval system answers financial questions and cites its sources, and Keirolabs' 78% against a 19% vector RAG baseline is the difference between an agent that answers and an agent that guesses. SimpleQA at 84% measures the same thing on short factual questions. When two vendors price 4x apart, the quality gap is the only thing that can justify the premium, and at the top of this market the quality gap is small.
The whole build call rides on one number: how many queries your agent runs each month. A research tool that runs 10,000 queries a month pays $10 on Parallel Turbo and $2.50 on Keirolabs. A production assistant running a million queries a month pays $1,000 on Parallel Turbo and $250 on Keirolabs. The coding effort is comparable on either stack, because both return clean JSON that a model can read. The difference is what the bill does to your unit economics, and unit economics decide which of the two stacks keeps you alive past the first year.
The simplest test is to send the same 100 queries through both free allowances. Parallel gives 5,000 requests plus $5 monthly. Keirolabs gives 1,000 free queries with no card. Line up the outputs and the invoices, and the right pick for your volume becomes obvious. Head to [keirolabs.cloud](https://keirolabs.cloud) and read the outputs yourself.
## Two price lanes now define the search market
**The defining event of 2026 is the split between a raw-data tier at $0.10-1.00/1K and an agent-ready tier at $1.00-8.00/1K, and Parallel Turbo is the cheapest entry point into the agent-ready tier.** The raw lane sells links. The agent-ready lane sells answers.
The agent-ready lane is the one under pressure. Exa raised its base rate from $5 to $7 this year. Tavily's effective cost stayed at $8 or higher. Brave held at $5. Perplexity held at $5. Each price increase in the tier makes the entry point more valuable, and the entry point is now Parallel Turbo at $1.00, with Keirolabs at $0.25 semantic and $0.10 SERP underneath it.
The consolidation has already started. The expensive side keeps raising its prices, the acquirers keep paying premiums, and the teams whose unit economics survive a million queries a month are the ones that matter. None of those teams sit on the $5-8 tier. They sit on the $0.10-1.00 tier, and they are the ones who will run the search infrastructure that everyone else buys.
The most underrated part of Parallel's position is that it straddles both tiers. Turbo at $1.00 competes with the raw tier on price and the agent-ready tier on output. Basic and Advanced at $5.00 compete with Perplexity and Brave on depth. No other vendor in this comparison can make that claim, and it is the reason Parallel is the most underrated pricing model in the category.
Twelve months from now the split will be the default story. The vendors on the $5-8 tier will keep raising prices to fund their indexes and their models, and the vendors on the $0.10-1.00 tier will keep taking the volume. Parallel's straddle is the hedge: it can compete on price with the cheap tier and on depth with the expensive tier, and it does not have to pick a side. That is the position to watch.
## What does the free tier let you measure before you pay?
**Create both accounts and feed the same 100 queries to both free tiers: Parallel gives 5,000 requests plus $5 monthly, and Keirolabs gives 1,000 free queries with no card.** The Keirolabs free tier covers every endpoint, so the free run is the full workload, not a trimmed sample.
The Keirolabs API base is `api.keirolabs.cloud`, and the v2 content endpoint is `POST https://api.keirolabs.cloud/api/v2/search/content`, which returns search results and the extracted content in a single round trip. The [Keirolabs pricing page](https://keirolabs.cloud/pricing) lists the full rate card: $0.25 per 1,000 semantic queries, $0.10 per 1,000 SERP queries, and 1,000 free queries a month.
Send the same question set to both and read the outputs side by side. The quality gap between the top vendors will be smaller than you expect, and the price gap will be bigger. Then run the volume math on your own traffic. At 100,000 queries a month, Parallel Turbo is $100, Tavily is $800, and Keirolabs is $25. The free tier shows you the outputs. The invoice at volume is what decides the vendor.
A year from now, $1.00 Turbo will be the number everyone quotes. Parallel's $1.00 Turbo is the cheapest agent-ready search API in the market, and it stays the most underrated number in the category because everyone keeps comparing Perplexity's $5.00 against the SERP tier. The split is done. You can pay $5.00-8.00 for a query your agent can use, or you can pay $0.10-1.00 for the same result and spend the difference on everything else. Start with a free account at [keirolabs.cloud](https://keirolabs.cloud), run the same 100 queries on your own workload, and let the invoice name the winner.
## About the author
Dave builds AI agent and RAG pipelines and writes about the infrastructure behind them. He benchmarks search APIs from the bills, not the landing pages.
## FAQ
### What is Parallel's per-1,000 price in 2026?
Parallel Search API costs $1.00 per 1,000 requests on Turbo mode in 2026, with Basic and Advanced modes at $5.00 per 1,000 and extra results beyond the default 10 billing an additional $1.00 per 1,000.
### Does the Parallel Search API have a free tier?
Yes. Parallel gives every account 5,000 free requests a month plus $5 in free monthly credits, the largest raw free allowance in the search API category.
### Is Parallel Search API cheaper than Perplexity?
Yes. Parallel Turbo is $1.00 per 1,000 requests, 5x cheaper than Perplexity's flat $5.00 per 1,000, at roughly 200ms median latency.
### Which is cheaper per 1,000, Keirolabs or Parallel Turbo?
Keirolabs is the cheapest at $0.25 per 1,000 semantic queries and $0.10 per 1,000 SERP queries, with a free tier of 1,000 queries per month. Parallel Turbo is the cheapest agent-ready option at $1.00 per 1,000.
