# OpenAlex vs Valyu: A Feature-by-Feature Research Platform Comparison > Source: > Published: 2026-08-28 19:03:47+00:00 OpenAlex and Valyu solve similar research problems. [Valyu](https://www.valyu.ai) is a search and DeepResearch API built for AI agents, built for retrieving full-text evidence with attached citations across academic literature, scientific research, papers, and specialist sources in a single call. [OpenAlex](https://openalex.org) is an open scholarly metadata graph of more than 322 million works, built for bibliometric discovery, citation analysis, and structured queries across works, authors, institutions, and topics. [Valyu](https://valyu.ai) gives you usage-based semantic retrieval of full-text passages with structured citations across academic literature, scientific research, papers, journals and specialist sources in a single call for both humans and AI agents. [OpenAlex](https://openalex.org) gives you an open scholarly graph of 322 million-plus works with structured metadata, filters, authors, institutions, topics, and citation relationships OpenAlex indexes scholarly works as a connected graph. A "work" is any scholarly document: a journal article, conference paper, book or book chapter, dataset, dissertation, or preprint. Works are split across two corpora, which is worth knowing before you compare headline numbers. The **core** is the curated catalogue and it is what every query returns by default: a live call to `api.openalex.org/works` in August 2026 gives **322,147,582** works. An **expansion** layer adds a rawer 165,253,218 records, mostly datasets and single-repository entries, and `corpus=all` returns both for **487,400,800**. Every "320 million" figure you see quoted, including the one in this article, is the core. The graph connects works to authors, sources (journals, conference proceedings, repositories), institutions, topics, keywords, funders, awards, and publishers. Bibliographic coverage is assembled from upstream indexes including Crossref, PubMed, DataCite, DOAJ, and arXiv. The `search` parameter for works matches across title, abstract, and fulltext, and the `fulltext.search` filter covers the same three fields. Separately, OpenAlex maintains a content archive of cached full text: 50M+ PDFs (roughly 250 TB) and ~43M TEI XML files parsed by Grobid. Filtering on `has_content.pdf:true` returns **52,407,611** works, every one of them open access. Retrieval runs through a separate content API at $0.01 per file, which is about 100 files a day on the free $1 budget. OpenAlex does not provide full text for paywalled or subscription-only publications. It returns metadata and links to locations where full text may be available, and what you can actually retrieve depends on the open-access status of each work. Valyu indexes roughly 40 million academic papers alongside web results, financial market data, and licensed and specialist collections. The academic sources break down as: | Source | Coverage | Update frequency | |---|---|---| | PubMed | 37M+ papers | Monthly | | arXiv | 2.5M+ papers | Monthly | | bioRxiv | 250K+ papers | Monthly | | medRxiv | 80K+ papers | Monthly | | chemRxiv | 30K+ papers | Monthly | Licensed Wiley collections cover finance journals and finance books (quantitative finance, risk, investment theory) on a monthly cycle, and Wiley Health & Life Sciences journals (medicine, nursing, pharmacology, allied health) quarterly. Beyond academic content, the index covers clinical trials from ClinicalTrials.gov (500K+, real-time), USPTO patents (8M+, weekly), EPO patents (4M+, weekly), FDA drug labels (150K+, real-time) and others. [Valyu](https://platform.valyu.ai) does not provide full text for every indexed publication. Full-text retrieval covers open-access content and sources where access has been licensed, and licensed content carries usage restrictions. The [Valyu platform](https://platform.valyu.ai) provides a search playground that queries across source categories and returns title, URL, content, and structured citations. Because retrieval is semantic, an exact-title query matches by meaning rather than string equality, which returns the target work plus related material rather than a single row. The [OpenAlex interface](https://openalex.org) presents a search box and filter options. Boolean operators (`AND` , `OR` , `NOT` ) must be capitalised, and quotation marks give you phrase matching. Author searches run through the `/authors` endpoint, and citation searching runs through citation filters. | Feature | OpenAlex | Valyu | |---|---|---| | Corpus size | 322M core works, 487M including the expansion layer | ~40M academic papers, plus web, financial, and specialist sources | | API base URL | `api.openalex.org` | `api.valyu.ai` | | Authentication | Optional free key ($0.10/day without, $1/day with) | `x-api-key` header, required | | Query type | Keyword, Boolean, phrase, proximity, wildcard, semantic | Semantic full-text retrieval | | Max query size | ~4 KB URL | Not a documented constraint | | Filters | Structured entity filters across all endpoints | `search_type` , `included_sources` , `excluded_sources` , `source_biases` , `relevance_threshold` , `start_date` , `end_date` , `category` , `country_code` , `max_num_results` , `max_price` | | Pagination | `page` / `per-page` (max 100), 10,000-result ceiling, cursor paging beyond | `max_num_results` | | Response fields | Selectable via `select` ; full metadata schema | title, url, content, relevance_score, citations | | Citations | Citation graph: `cited_by_count` , references, related works | `doi` , `authors` , `citation` , `citation_count` , `references` on academic results | | Full text | 52.4M works with a cached PDF, all open access | Open-access papers plus licensed collections | | Web search | Not included | Included | | Financial data | Not included | 75 exchanges, structured JSON | | Free tier | $1/day of API usage with a free key | $10 in credits, $20 with a work email | **Freshness.** OpenAlex updates continuously from its upstream indexes. Valyu’s indexes daily, monthly and quarterly. If your workflow depends on a paper published last week, Valyu will surface it faster. **Access rights.** OpenAlex provides metadata for all indexed works and full text only for open-access ones. Valyu provides full text for open-access papers plus licensed collections where access has been secured. Both operate inside publisher restrictions. **Coverage gaps.** OpenAlex’s 322 million core works are bibliographic records, not 322 million retrievable full texts: 52.4 million carry a cached PDF. Valyu’s roughly 40 million academic papers are a fraction of OpenAlex’s record count but gives full-text depth. **Valyu** fits full-text evidence retrieval and multi-source search: **OpenAlex** fits structured metadata discovery and citation graph analysis: The combined pipeline uses OpenAlex for discovery and Valyu for evidence retrieval: An agent can move across domains in a single run: OpenAlex establishes which works matter and how they connect, Valyu pulls the text that supports a claim. Discovery and retrieval are handled by services designed for each, rather than one tool doing both adequately. The two services return different object types for identical input, which is the clearest way to see the design split. A topic search for "melanoma immunotherapy" on OpenAlex returns work records: titles, citation counts, author and institution links, topic assignments. The same query on Valyu returns full-text passages with citations attached to each one. The same query on Valyu returns full-text passages with citations attached to each one. An exact-title search on OpenAlex uses the `search` parameter or a title filter and resolves to the record. On Valyu, semantic matching returns the target work alongside related content, because it is matching meaning rather than a string. An author search on OpenAlex uses the dedicated `/authors` endpoint with affiliation and output data. Valyu has no equivalent author endpoint; author filtering depends on metadata in the indexed source. A supporting-evidence search on OpenAlex returns related works through the citation graph. Valyu returns passages that address the query directly. This is a difference in design goal, not in quality. OpenAlex is built for graph discovery. Valyu is built for evidence retrieval. **OpenAlex** is a REST API at `api.openalex.org` . Every entity type is an endpoint: `/works` , `/authors` , `/sources` , `/institutions` , `/topics` , `/keywords` , `/funders` and more, each supporting list, filter, search, sort, and group operations. Query syntax supports phrase matching with quotes, proximity search via `~N` (`"climate change"~5` finds the terms within five words of each other), and unstemmed exact matching plus wildcards through `search.exact` (`machin*` matches machine, machines, machinery, with a three-character minimum before the wildcard). Maximum URL length is approximately **4 KB**; longer queries return a 400, and the documented fix is to split the Boolean query and combine the returned IDs client-side. Semantic search is generally available as its own method, priced the same as keyword search, capped at 2,000 characters of input, rate limited to 1 request per second, and returning at most 50 results. Pagination uses `page` and `per-page` , where **100 is the supported maximum** (200 is deprecated legacy behaviour). Basic paging reaches only the first 10,000 results, since `page * per_page` must not exceed 10,000. Cursor paging (`cursor=*` , then follow `next_cursor` ) goes deeper, and for genuinely bulk work the docs point you at the OpenAlex snapshot instead. An API key is **not** required. You can make basic queries with no key at all, at $0.10 of usage per day; a free key raises that 10x to $1 per day. The key travels as `?api_key=KEY` or an `Authorization: Bearer KEY` header, and both work identically. **Valyu** is a [REST API](https://api.valyu.ai) authenticated with an `x-api-key` header, with Python, TypeScript, and Rust (alpha) SDKs. ``` python import os from valyu import Valyu valyu = Valyu(api_key=os.environ["VALYU_API_KEY"]) response = valyu.search( "Phase 3 melanoma immunotherapy trials", search_type="proprietary", included_sources=["valyu/valyu-pubmed", "valyu/valyu-clinical-trials"], start_date="2024-01-01", max_num_results=10, max_price=20, ) for result in response.results: print(result.title, result.url) print(result.content) ``` `search_type` takes four values: `all` (web plus proprietary, with an LLM router picking sources), `web` , `proprietary` , and `news` . Alongside it the endpoint documents `included_sources` , `excluded_sources` , `source_biases` (soft-rank any source from -5 to +5 instead of filtering it out), `max_num_results` , `max_price` , `relevance_threshold` , `start_date` , `end_date` , `category` , `country_code` , `response_length` , and `is_tool_call` . `included_sources` accepts dataset ids, bare domains, presets (`academic` , `finance` , `patent` , `legal` , `medical` , `health` , `genomics` , `chemistry` , `physics` , `politics` , `transportation` , `cybersecurity` , `compliance` , `environment` , `automotive` , `pulse` ), and saved `collection:` groups. Beyond search, the API surface includes Contents, Answer (grounded answers with citations), and DeepResearch (an autonomous agent with fast, standard, heavy, and max modes producing cited reports and xlsx/docx/pptx/pdf/csv deliverables). Results carry title, URL, content, source, and `relevance_score` . Academic results add `doi` , `authors` , `citation` , `citation_count` , and `references` , plus `abstract` and figures where the source provides them. The whole shape is built for LLM context windows. No. You can make basic queries with no key at all. A free key raises your daily budget 10x, from $0.10 to $1, and is passed either as `?api_key=KEY` or an `Authorization: Bearer KEY` header. Valyu provides full text for open-access papers from PubMed, arXiv, bioRxiv, medRxiv, and chemRxiv, plus licensed Wiley finance and Health & Life Sciences collections. Licensed content carries usage restrictions. OpenAlex updates continuously from Crossref, PubMed, DataCite, DOAJ, and arXiv. Valyu refreshes academic sources monthly, SEC filings daily, and clinical trials, drug labels, and market data in real time. Yes. Web search costs $1.50 per 1,000 results. Setting `search_type` to `all` queries web and proprietary sources in one call, with a router selecting sources; `web` , `proprietary` , and `news` narrow it. Yes, and free DOI lookups on OpenAlex make it cheap. OpenAlex identifies works by topic, author, or citation relationship, and Valyu retrieves full-text passages and citations for them. $10 in free credits with no credit card, or $20 with a work email. Credits work across every source type. Keys come from [platform.valyu.ai](https://platform.valyu.ai). No. Preprints from arXiv, bioRxiv, medRxiv, and chemRxiv are not peer-reviewed, and both services index them alongside peer-reviewed articles. Filter on source or publication type when evidence quality matters.