API cost decision in 10 seconds

NewLFM2.5-24B-A2B vs NewExtract

Pick Extract when budget and context both matter.

Page updated:  Data confirmed:  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 $0.4 for LFM2.5-24B-A2B, saving $0.36 (90% lower).

Cost-first pickExtract
Context-first pickExtract
Sample savings$0.3690%
10x traffic gap$3.6

Extract is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $3.6. 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 shapeToken mixBetter pickLFM2.5-24B-A2BExtract
Input-heavy / RAG5M input + 500K outputExtract$0.6$0.2
Balanced workload1M input + 1M outputExtract$0.75$0.04
Output-heavy chatbot1M input + 5M outputExtract$3.55$0.04
Cheaper input Extract $0.05 vs $0.04 / 1M

Extract is $0.01 cheaper per 1M input tokens (20% lower; 1.25x difference).

Cheaper output Extract $0.7 vs $0 / 1M

Extract is free for output tokens while LFM2.5-24B-A2B costs $0.7 per 1M tokens.

Larger context Extract 128K vs 1M

Extract has 872K more context (7.81x larger).

Sample workload Extract $0.4 vs $0.04

Extract is $0.36 cheaper on the standard workload (90% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
LFM2.5-24B-A2B 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 $0.4 for LFM2.5-24B-A2B and $0.04 for Extract.

Best Fit

Choose LFM2.5-24B-A2B 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 $0.4 for LFM2.5-24B-A2B, saving $0.36 (90% lower).
  • Extract is $0.36 cheaper on the standard workload (90% lower).
  • Extract is $0.01 cheaper per 1M input tokens (20% lower; 1.25x difference).
  • Extract is free for output tokens while LFM2.5-24B-A2B costs $0.7 per 1M tokens.
  • Extract has 872K more context (7.81x larger).
Head-to-Head Specs
FeatureNewLFM2.5-24B-A2B
(LiquidAI)
NewExtract
(ScaleDown)
Input Price
prompt tokens per 1M
$0.05$0.04
Completion Price
per 1M tokens
$0.7$0
Sample Workload Cost
1M input + 500K output
$0.4$0.04
Context Window128K1M
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionExtractOn the standard 1M input plus 500K output workload, Extract is estimated at $0.04 vs $0.4 for LFM2.5-24B-A2B, saving $0.36 (90% lower).
High-volume input processingExtractLower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsExtractLower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workExtractA larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps
Larger context near this budget
  • 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.
  • GPT-6 Luna offers 1.05M context with $0.35 sample workload cost.
  • GPT-6 Luna Pro offers 1.05M context with $0.35 sample workload cost.

Cheaper alternatives

Review low-cost models sorted by a standard 1M input plus 500K output workload.

Open cheapest models

Larger context alternatives

Find models with larger context windows for RAG, long documents, and codebase review.

Open largest context models

Provider catalogs

Compare models within provider hubs before choosing a final API vendor.

Open provider hubs

LiquidAI catalog

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

Open LiquidAI models

ScaleDown catalog

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

Open ScaleDown models
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...

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...