Pareto 26.9

by Unbiased AIChat

Pareto is a multimodal composite model built for research, coding, and agentic workflows, while delivering frontier-level performance across a broad range of general-purpose tasks.

Context
262K tokens
Max output
131,072 tokens
Released
2026-10-13
Weights
Closed

Feed

unbiased/pareto-26-9 · also seen as unbiased/pareto-26.9-20260917

Specifications

Full facts as recorded, incl. what is unknown.

Released
2026-10-13
Weights
Closed
Input
Text, Image
Output
Text
Context window
262,144 max across endpoints
Max output
131,072
Providers
1 + 3 gateways, not counted as providers
Epoch Capabilities Index
not evaluated
Direct price range
$2.50 in · $7.50 out per 1M tokens · from its one provider
More details
Last updated
2026-10-13
Knowledge cutoff

Capabilities

Across all endpoints: supported if any endpoint supports it.

  • Tool calling
  • Parallel toolsunknown
  • Structured output
  • Reasoning
  • Image input
  • PDF input
  • Audio input
  • Audio outputunknown
  • Video input
  • Prompt caching
  • Web searchunknown
  • Computer useunknown
  • System messagesunknown
  • Assistant prefillunknown
  • Temperature
  • Streamingunknown
  • Attachments

Endpoints

One row per provider and variant; gateways are listed separately.

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Price history

Atom feed

No change since 19 Oct 2026. The cheapest direct price has been $2.50 in / $7.50 out per 1M tokens at Unbiased on every data refresh since then.

Tracked from 19 Oct 2026. Headline-eligible direct prices only, so a price the sanity check flags never draws a spike. Series as JSON

Cost calculator

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Blended rate per 1M tokens, each at its own cheapest provider (10M input : 2M output mix).

ModelBlended/1MIn/1MOut/1MContextvs Pareto 26.9
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More from Unbiased AI

Newest Unbiased AI models in the catalogue. All Unbiased AI models

ModelReleasedContextListed price
Pareto 26.102026-10-151.05Mfrom $0.80
Pareto2026-09-17262Kfrom $3.44
Heads up: prices are indicative list rates scraped from provider pricing pages; verify with the provider before relying on them. Report incorrect data for this model