Ready to try Pareto on your own traffic?
Jump to the 4-step setup →An engineering leader's LLM bill has three levers, in order of size: which model serves each class of traffic (up to 9x between tiers on our measured tasks), whether caching and batching are policy or accident (2.6x and 2x measured), and only then the per-token rates everyone negotiates over.
Why the bill is illegible
Rate cards quote per-million-token prices; your traffic arrives as requests. Translating between them requires token counts nobody tracks and per-model verbosity nobody expects: we metered the same prompt at $0.1158 on Claude Opus 5 and $0.0724 on Opus 4.8, identical rate cards, 60% apart. Your invoice aggregates thousands of these surprises into one unexplainable number.
The audit that takes an afternoon
Segment last month's traffic three ways: which model served it, whether the model tier matched the task difficulty, and how much context was resent uncached. In our measured data, the gaps are worth: up to 9x for tier-mismatched routine traffic (Fable 5 at $0.1462 vs Haiku at $0.0162, same working output), 2.6x for uncached agentic context (our published Claude Code session ledger), and 2x for batchable jobs running synchronously. Price your own mix in the cost calculator.
The afternoon audit, as sliders
Directional math from our measured ratios: the tier-mismatch slice repriced at the measured 9x task gap (Fable 5 $0.1462 vs Haiku $0.0162, same working output), the uncached slice at the measured 2.6x caching saving, the batchable slice at the standard 50%. Slices are treated as non-overlapping; if they sum past 100% they are scaled down.
The part that is genuinely hard
Preliminary Pareto 26.10 scores and cost per task on four benchmarks are on the model card. These results may change before final publication, and no composite score is published.
Repricing exposure for the model you are pinned to
Events from provider announcements (sourced table in the Fable 5 breakdown); "tracked window" = November 2025 through July 2026. This is the case for owning model-to-traffic assignment as a standing process, or delegating it per request.
Before you switch: privacy, setup, cost
- Privacy. Zero data retention covers API traffic designated ZDR on the service offering page or in a written agreement. Chat and Personal plans are not ZDR. Details on private AI.
- Setup. OpenAI-format clients use base URL
https://api.unbiased.ai/v1, your key and modelpareto. Anthropic-format clients (Claude Code, the Anthropic SDK) usehttps://api.unbiased.ai, your key andpareto. Validate your client’s streaming, tools and error handling before moving traffic. Per-tool steps are in the setup guides. - Cost. One bill at $0.80 input / $3.20 output per million tokens. Your developers keep Claude Code, Cursor or Codex: Pareto works in coding agents that let you set a base URL. Commercial or production use needs a separate written agreement with Unbiased.
Get started
You do not need a call to try this. Four steps, from a fresh terminal to a first comparison:
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Sign up for a beta account. Create your account at platform.unbiased.ai. Every signup is reviewed and approved by hand; once you’re cleared, you pick up your key on the platform when you set up your workload.
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Hand the setup to your agent. Everything an agent needs lives in one file:
https://unbiased.ai/start/agent.md
In Claude Code, paste the line below and the agent takes it from there. Codex: swap
claudeforcodex.$
claude "Read https://unbiased.ai/start/agent.md and get me set up with Pareto. Walk me through it one step at a time. You do the work." -
Or make the first call yourself. Once your key is issued, send one request to the OpenAI-compatible endpoint:
$
curl https://api.unbiased.ai/v1/chat/completions -H "Authorization: Bearer $UNBIASED_API_KEY" -H "Content-Type: application/json" -d '{"model": "pareto", "messages": [{"role": "user", "content": "Hello"}]}'The same key works on the Anthropic-format
/v1/messagesendpoint. Endpoints, rate limits and error codes are in the API docs. Already on OpenRouter? Use Pareto on OpenRouter. -
Check the reply. A completion back from
paretomeans your key and endpoint work. A 401 means the key is missing or wrong.
Prefer a person, or already running real volume?
Get matched to your actual workload profile (a few quick questions, no account), put $100 of credits against a sampled slice of real traffic, and compare the metered results to your current bill. That is a one-afternoon experiment with a number at the end, which is the only format budget conversations respect.
The finance one-pager, generated
Plain-text, pasteable, every number sourced. The measured references come from our metered task table and the Verbosity Index; your own numbers come from you.
Questions we get from this seat
How do I explain the LLM bill to finance?
Translate to cost per completed task, not tokens: 'a support summarization costs $0.002, a code generation $0.07, and here is last month's volume of each.' Our measured task table gives you defensible reference points.
What is the fastest saving with no migration?
Batch what can wait (50% off both sides on both major providers) and make caching policy rather than accident (our measured session saved 2.6x). Both are configuration, not replatforming.
How do I evaluate Pareto without risking production?
Shadow a sample: identical prompts to your current model and Pareto, compare outputs and metered bills. $100 in credits covers thousands of comparison requests, and the methodology we use for our own claims is public.
Where else can I find setup and access questions answered?
The general FAQ covers the same step-by-step setup plus billing, data handling, and access questions this page doesn't get into.
Compare any two models
List rates and dated competitor measurements: prices, measured bills and the sourced LLM price index. Preliminary Pareto 26.10 benchmark costs per task from October 1, 2026 are on the model card. Verbosity: Edition 2.