API cost decision in 10 seconds

NewPareto 26.9 vs NewExtract

Pick Extract when budget and context both matter.

Page updated: 2026-10-14T04:07:47Z Data confirmed: 2026-10-15T02:07:54Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Extract when budget and context both matter.

On the standard 1M input plus 500K output workload, Extract is estimated at $0.04 vs $6.25 for Pareto 26.9, saving $6.21 (99.4% lower).

Cost-first pickExtract

Context-first pickExtract

Sample savings$6.2199.4%

10x traffic gap$62.1

Extract is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $62.1. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Extract stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shape	Token mix	Better pick	Pareto 26.9	Extract
Input-heavy / RAG	5M input + 500K output	Extract	$16.25	$0.2
Balanced workload	1M input + 1M output	Extract	$10	$0.04
Output-heavy chatbot	1M input + 5M output	Extract	$40	$0.04

Cheaper input Extract $2.5 vs $0.04 / 1M

Extract is $2.46 cheaper per 1M input tokens (98.4% lower; 62.5x difference).

Cheaper output Extract $7.5 vs $0 / 1M

Extract is free for output tokens while Pareto 26.9 costs $7.5 per 1M tokens.

Larger context Extract 262.14K vs 1M

Extract has 737.86K more context (3.81x larger).

Sample workload Extract $6.25 vs $0.04

Extract is $6.21 cheaper on the standard workload (99.4% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

Pareto 26.9 Calculating… Estimated API cost

Extract Calculating… Estimated API cost

Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

Extract has the lower input price; Extract has the lower output price; Extract offers the larger context window. For the 1M input plus 500K output sample, Extract is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $6.25 for Pareto 26.9 and $0.04 for Extract.

Best Fit

Choose Pareto 26.9 when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

Choose Extract when you care most about lower input-token price, lower output-token price, and larger context window.

Decision Notes

On the standard 1M input plus 500K output workload, Extract is estimated at $0.04 vs $6.25 for Pareto 26.9, saving $6.21 (99.4% lower).
Extract is $6.21 cheaper on the standard workload (99.4% lower).
Extract is $2.46 cheaper per 1M input tokens (98.4% lower; 62.5x difference).
Extract is free for output tokens while Pareto 26.9 costs $7.5 per 1M tokens.
Extract has 737.86K more context (3.81x larger).

Head-to-Head Specs

Feature	NewPareto 26.9 (unbiased)	NewExtract (ScaleDown)
Input Price prompt tokens per 1M	$2.5	$0.04
Completion Price per 1M tokens	$7.5	$0
Sample Workload Cost 1M input + 500K output	$6.25	$0.04
Context Window	262.14K	1M
Release Date	2026-10-13	2026-10-13

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Extract	On the standard 1M input plus 500K output workload, Extract is estimated at $0.04 vs $6.25 for Pareto 26.9, saving $6.21 (99.4% lower).
High-volume input processing	Extract	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Extract	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	Extract	A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps

Pareto 26.10 Preview can replace Pareto 26.9 when lower sample workload cost matters most: $2.4.

Larger context near this budget

Grok 4.20 Multi-Agent offers 2M context with $2.5 sample workload cost.
Grok 4.20 offers 2M context with $2.5 sample workload cost.
Llama 4 Scout offers 1.31M context with $0.47 sample workload cost.
MiMo-V2.6-Flash offers 1.05M context with $0.28 sample workload cost.

Popular competitors

DeepSeek V4.1 Flash · DeepSeek · #1
Step 5 Preview · StepFun · #2
GLM 5.3 Flash · Z.ai · #3
MiMo-V2.6-Flash · Xiaomi · #4

Cheaper alternatives

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Larger context alternatives

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Provider catalogs

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unbiased catalog

Review all tracked unbiased models before deciding whether this matchup is the right shortlist.

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ScaleDown catalog

Check other ScaleDown models with comparable pricing, context, or release timing.

Open ScaleDown models

Pareto 26.9

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.

Extract

Extract is a description-driven entity extraction model from ScaleDown. Instead of a fixed set of entity types, callers describe the fields they want in plain English through `provider.options.scaledown.entities`, and the...