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unbiased · Balanced

Pareto 26.10

Added Oct 1, 2026

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Use in the app

Pareto 26.10 is Unbiased AI's multimodal composite model for research, coding, and agentic workflows. It accepts text and images, supports tool calling, and provides a 1M-token context window with up to 131K output tokens. This is the stable release of Pareto 26.10. Tool selection is automatic; forced tool selection, structured output, and adjustable reasoning controls are not supported.

  • Tools
  • Vision
Input
Text, Images
Output
Text
Discovery tier
Balanced

Pricing

USD per 1M tokens
Input
$0.80
Output
$3.20
Cache read
$0.03

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
131.1K
Average output (7 days)
346 tokens
Longer than 37% of 473 models

Side by side

Pareto 26.10 compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Pareto 26.10unbiasedThis modelAmazon Nova Pro 1.0amazonRemove
Providerunbiasedamazon
Discovery tierBalancedBalanced
AddedOct 1, 2026Dec 3, 2024
Limits
Context window1.05MBest300K
Max output131.07KBest32K
Average output346 tokens56 tokens
Pricing, USD per 1M tokens
Input$0.80$0.80Best
Output$3.20$3.20Best
Cache read$0.03—
Benchmark indexes
Intelligence Index—7.0
Math Index—7.0
Capabilities
ToolsYesNo
VisionYesNo
Reasoning effort——

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Pareto 26.10
  • Amazon Nova Pro 1.0

Intelligence Index

  • Pareto 26.10—
  • Amazon Nova Pro 1.07.0
3.8Catalog models by score55.1

Indexes

  • Math Index

    Composite of the math evaluations

    • Pareto 26.10: —
    • Amazon Nova Pro 1.0: 7.0

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • Pareto 26.10: —
    • Amazon Nova Pro 1.0: 21.0%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Pareto 26.10: —
    • Amazon Nova Pro 1.0: 3.2%

  • GPQA Diamond

    Graduate-level science questions

    • Pareto 26.10: —
    • Amazon Nova Pro 1.0: 49.9%

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Pareto 26.10: —
    • Amazon Nova Pro 1.0: 69.1%

  • IFBench

    Following precise output instructions

    • Pareto 26.10: —
    • Amazon Nova Pro 1.0: 38.1%

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • Pareto 26.10: —
    • Amazon Nova Pro 1.0: 23.3%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Pareto 26.10: —
    • Amazon Nova Pro 1.0: 7.0%

  • AIME

    Competition mathematics

    • Pareto 26.10: —
    • Amazon Nova Pro 1.0: 10.7%

  • MATH-500

    Competition math problems

    • Pareto 26.10: —
    • Amazon Nova Pro 1.0: 78.6%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Pareto 26.10: —
    • Amazon Nova Pro 1.0: 6.1%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Pareto 26.10: —
    • Amazon Nova Pro 1.0: 14.0%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Pareto 26.10: —
    • Amazon Nova Pro 1.0: 21.0%

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Prompt cache hits
0.0%
About $0.80 per 1M input tokens with caching

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "unbiased/pareto-26.10",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="unbiased/pareto-26.10",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

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