API cost decision in 10 seconds

NewLFM2.5-24B-A2B vs NewPareto 26.10 Preview

Pick LFM2.5-24B-A2B for lower cost; pick Pareto 26.10 Preview only if the larger context window matters more.

Page updated:  Data confirmed:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick LFM2.5-24B-A2B for lower cost; pick Pareto 26.10 Preview only if the larger context window matters more.

On the standard 1M input plus 500K output workload, LFM2.5-24B-A2B is estimated at $0.4 vs $2.4 for Pareto 26.10 Preview, saving $2 (83.3% lower).

Cost-first pickLFM2.5-24B-A2B
Context-first pickPareto 26.10 Preview
Sample savings$283.3%
10x traffic gap$20

Pareto 26.10 Preview has more context, but LFM2.5-24B-A2B saves $2 on the standard workload. At 10x that traffic, the same price gap is about $20. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

LFM2.5-24B-A2B stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickLFM2.5-24B-A2BPareto 26.10 Preview
Input-heavy / RAG5M input + 500K outputLFM2.5-24B-A2B$0.6$5.6
Balanced workload1M input + 1M outputLFM2.5-24B-A2B$0.75$4
Output-heavy chatbot1M input + 5M outputLFM2.5-24B-A2B$3.55$16.8
Cheaper input LFM2.5-24B-A2B $0.05 vs $0.8 / 1M

LFM2.5-24B-A2B is $0.75 cheaper per 1M input tokens (93.8% lower; 16x difference).

Cheaper output LFM2.5-24B-A2B $0.7 vs $3.2 / 1M

LFM2.5-24B-A2B is $2.5 cheaper per 1M output tokens (78.1% lower; 4.57x difference).

Larger context Pareto 26.10 Preview 128K vs 1.05M

Pareto 26.10 Preview has 920.58K more context (8.19x larger).

Sample workload LFM2.5-24B-A2B $0.4 vs $2.4

LFM2.5-24B-A2B is $2 cheaper on the standard workload (83.3% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
LFM2.5-24B-A2B Calculating… Estimated API cost
Pareto 26.10 Preview 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

LFM2.5-24B-A2B has the lower input price; LFM2.5-24B-A2B has the lower output price; Pareto 26.10 Preview offers the larger context window. For the 1M input plus 500K output sample, LFM2.5-24B-A2B is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.4 for LFM2.5-24B-A2B and $2.4 for Pareto 26.10 Preview.

Best Fit

Choose LFM2.5-24B-A2B when you care most about lower input-token price, and lower output-token price.

Choose Pareto 26.10 Preview when you care most about larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, LFM2.5-24B-A2B is estimated at $0.4 vs $2.4 for Pareto 26.10 Preview, saving $2 (83.3% lower).
  • LFM2.5-24B-A2B is $2 cheaper on the standard workload (83.3% lower).
  • LFM2.5-24B-A2B is $0.75 cheaper per 1M input tokens (93.8% lower; 16x difference).
  • LFM2.5-24B-A2B is $2.5 cheaper per 1M output tokens (78.1% lower; 4.57x difference).
  • Pareto 26.10 Preview has 920.58K more context (8.19x larger).
Head-to-Head Specs
FeatureNewLFM2.5-24B-A2B
(LiquidAI)
NewPareto 26.10 Preview
(unbiased)
Input Price
prompt tokens per 1M
$0.05$0.8
Completion Price
per 1M tokens
$0.7$3.2
Sample Workload Cost
1M input + 500K output
$0.4$2.4
Context Window128K1.05M
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionLFM2.5-24B-A2BOn the standard 1M input plus 500K output workload, LFM2.5-24B-A2B is estimated at $0.4 vs $2.4 for Pareto 26.10 Preview, saving $2 (83.3% lower).
High-volume input processingLFM2.5-24B-A2BLower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsLFM2.5-24B-A2BLower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workPareto 26.10 PreviewA larger context window leaves more room for retrieved passages, conversation history, or source files.

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Provider catalogs

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LiquidAI catalog

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unbiased catalog

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LFM2.5-24B-A2B

LFM2.5-24B-A2B is a mixture-of-experts reasoning model from Liquid AI with 24B total and 2.45B active parameters. It always reasons before answering and is built for agents that call tools. Liquid...

Pareto 26.10 Preview

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. This is a preview of the...