API cost decision in 10 seconds

NewLFM2.5-24B-A2B vs NewSummarize

Pick Summarize when budget and context both matter.

Page updated: 2026-10-13T20:10:44Z Data confirmed: 2026-10-15T01:07:46Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Summarize when budget and context both matter.

On the standard 1M input plus 500K output workload, Summarize is estimated at $0.04 vs $0.4 for LFM2.5-24B-A2B, saving $0.36 (90% lower).

Cost-first pickSummarize

Context-first pickSummarize

Sample savings$0.3690%

10x traffic gap$3.6

Summarize 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.

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

Workload shape	Token mix	Better pick	LFM2.5-24B-A2B	Summarize
Input-heavy / RAG	5M input + 500K output	Summarize	$0.6	$0.2
Balanced workload	1M input + 1M output	Summarize	$0.75	$0.04
Output-heavy chatbot	1M input + 5M output	Summarize	$3.55	$0.04

Cheaper input Summarize $0.05 vs $0.04 / 1M

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

Cheaper output Summarize $0.7 vs $0 / 1M

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

Larger context Summarize 128K vs 1M

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

Sample workload Summarize $0.4 vs $0.04

Summarize 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.

Monthly input tokens Monthly output tokens

LFM2.5-24B-A2B Calculating… Estimated API cost

Summarize 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

Summarize has the lower input price; Summarize has the lower output price; Summarize offers the larger context window. For the 1M input plus 500K output sample, Summarize 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 Summarize.

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 Summarize 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, Summarize is estimated at $0.04 vs $0.4 for LFM2.5-24B-A2B, saving $0.36 (90% lower).
Summarize is $0.36 cheaper on the standard workload (90% lower).
Summarize is $0.01 cheaper per 1M input tokens (20% lower; 1.25x difference).
Summarize is free for output tokens while LFM2.5-24B-A2B costs $0.7 per 1M tokens.
Summarize has 872K more context (7.81x larger).

Head-to-Head Specs

Feature	NewLFM2.5-24B-A2B (LiquidAI)	NewSummarize (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 Window	128K	1M
Release Date	2026-10-13	2026-10-13

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Summarize	On the standard 1M input plus 500K output workload, Summarize is estimated at $0.04 vs $0.4 for LFM2.5-24B-A2B, saving $0.36 (90% lower).
High-volume input processing	Summarize	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Summarize	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	Summarize	A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps

LFM2.5-2.6B (free) can replace LFM2.5-24B-A2B when lower sample workload cost matters most: $0.
LFM2.5-1.2B-Thinking (free) can replace LFM2.5-24B-A2B when lower sample workload cost matters most: $0.
LFM2.5-1.2B-Instruct (free) can replace LFM2.5-24B-A2B when lower sample workload cost matters most: $0.
LFM2-24B-A2B can replace LFM2.5-24B-A2B when lower sample workload cost matters most: $0.09.

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.

Popular competitors

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GLM 5.3 Flash · Z.ai · #3
MiMo-V2.6-Flash · Xiaomi · #4

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LiquidAI catalog

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ScaleDown 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...

Summarize

Summarize is an abstractive summarization model from ScaleDown. It condenses long text and documents into a fluent, faithful rewrite rather than lifting sentences from the source, and is suited for...