# Parallel Decisions API pricing and access

> Parallel Decisions API searches the live web to answer typed questions with probabilities and sources. Its listed price is $1 per 1,000 calls.

Updated 2026-11-04 (Australia/Adelaide)

By Parallel · Released: 2026-10-25 · HOSTED

A decision engine that searches the live web before it answers. You send typed questions about a company, product or policy, and one call returns typed answers with probabilities (or a refusal) plus a shared list of the web pages it used, so it can answer things a model only knows from training data cannot, such as whether a company has an open job right now.

## Facts

- Access: Hosted API, with a playground; 5,000 free requests to start
- Price: $1 per 1,000 calls (as of 25 Oct 2026) · [Compare prices](<https://decisionmodels.ai/pricing>)
- Grounding: Searches the live web per request; citations cover the whole call, not each answer
- Latency: VENDOR-REPORTED: 0.56 seconds median on PWS-Decisions, measured by Parallel on 29 Oct 2026 (Pacific).

## Claims and sources

- **VENDOR-REPORTED**: Parallel says it costs 10x less than a standalone model [source](<https://parallel.ai/blog/decisions-api>)
- **VENDOR-REPORTED**: Parallel reports 76.22% on its own 300-question PWS-Decisions set with live web search, against Perplexity [Decider](<https://decisionmodels.ai/models/pplx-decider>) v1.2 at 50.89%, OpenAI's [Decisions API](<https://decisionmodels.ai/models/openai-decisions>) at 41.67% and [Jev](<https://decisionmodels.ai/models/jev>) 1.14 at 33.44%, run without web access or supplied external context. Uniform random guessing is 42.42%. LLMs with native search scored 96.56% to 97.33% at about 16.5 to 28.8 times the cost. Parallel generated these questions from its own customer topics; dataset terms prohibit redistribution. [source](<https://github.com/parallel-web/pws-decisions-benchmark>)
- **VENDOR-REPORTED**: The benchmark blog chart labels Baseten Elephant at 32.4% overall and 32.3% public. The repository records Baseten Mammoth at 45.0% overall and 37.0% public. [source](<https://parallel.ai/blog/pws-decisions-benchmark>)

## Links

- [Source: Announcement](<https://parallel.ai/blog/decisions-api>)
- [Source: Docs](<https://docs.parallel.ai/decisions/decisions-quickstart>)
- [Source: Benchmark](<https://github.com/parallel-web/pws-decisions-benchmark>)
- [Source: Benchmark announcement](<https://parallel.ai/blog/pws-decisions-benchmark>)

## Related projects

### Stock signals with sources, from Parallel

[Stock signals with sources, from Parallel](<https://decisionmodels.ai/projects#project-parallel-ticker>)

[Source: hckmstrrahul/parallel-ticker](<https://github.com/hckmstrrahul/parallel-ticker>)

A small demo with a live site: type a US or Indian stock and two Parallel Decisions calls, through Parallel's free MCP endpoint, assess its technicals and trading activity from the live web and return probabilities and sources.

- Creator: hckmstrrahul

- Stars: 0

- Licence: no licence

- Model: [Parallel Decisions API](<https://decisionmodels.ai/models/parallel-decisions>)

- Tags: web, trading