Skip to content
ModelCap

LFM2.5-24B-A2B

Official publisher releaseNewRestricted license

Liquid·#124 of 359 on the current board·cheaper than #119 o4 Mini

LFM2.5-24B-A2B is a language model from Liquid. It ranks #124 of 359 on ModelCap's current board, with an Index score of 48.3, modeled from the publisher's launch results against measured models. Its score range of 36.1–60.4 spans positions #78–#195. It is listed at $0.10 per million input tokens and $1.00 per million output tokens from one provider. It reads up to 128K tokens of context, and its weights are downloadable under a use-restricted licence.

Figures as of 13 Oct 2026, 17:47 UTC · download the public dataset · methodology

ModelCap Index · Current board
48.3#124
Modeled from the publisher's launch results against measured models · range 36.1–60.4
Market Gravity
21.4
Secondary market signal
Input
$0.10
per 1M tokens
Output
$1.00
per 1M tokens
Context
128K
tokens
Providers
1
endpoint

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
Liquidfp8$0.10$1.00128Kfp8100.0%

ModelCap Index · Current board

Methodology
48.3
Modeled from the publisher's launch results against measured models
Current board
#124 of 359
Score range
36.1–60.4
Rank range
#78–#195
Technical details
Public rank basis
Modeled · peer benchmarks (architecture)
Evidence label
Modeled · peer benchmarks · 6 reported rows against measured corpus ladders (84%); global-corpus-prior over 211 held-out anchors (16%); shrunk 1.2 up toward the measured corpus
Index support
26.8% · limited
Identity binding
Exact catalogue product · liquid/liquid/lfm-2.5-24b-a2b · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata LiquidAI/LFM2.5-24B-A2B@1769516ac588c4c558089c94f27d96b0dc67b183 (not the evaluation revision)
Index observations used
0
Qualified Index evidence point
48.3
How this position was produced · fused launch placement

No general-family board lists this model yet. Its point estimate is the precision-weighted mean of every channel that spoke for it; each channel’s share is the weight it carried. Independent measurements replace this placement as boards list the model.

Fused estimate
48.3 ± 9.5
Independent share
0%
Shrink toward corpus
+1.2
Optimism haircut
None applied
Method
precision-weighted-v1
Channels fused into this model’s launch placement
ChannelEstimateShare
Corpus ladder · not independent
6 reported rows against measured corpus ladders
47.1 ± 10.384%
Publisher corpus prior · not independent
global-corpus-prior over 211 held-out anchors
54.3 ± 23.416%
Bayesian Evidence Score · measured evidence input only

BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.

Observed capability
—
Evidence status
No admitted measured evidence
General preference
—
Coding
—
Agents & tools
—
Reasoning
—
Evidence breadth
0%
Evidence coverage
0%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
—
Liquidity (providers × uptime)
35.7
Open reach (HF downloads)
—
Surface (context / tools / modalities)
70.0
Freshness
100.0
  • · 1 live provider
  • · Catalogue: context 128000, reasoning, tools
  • · First seen 2026-10-13

These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.

The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.

Experimental capability estimate

Estimate policy
35.2
21.4–48.9 uncertainty interval
Excluded from rank
Confidence
79%
Training support
220 models · 125 lineages
Out-of-domain check
in domain
Feature coverage
100%
Lineage-held-out error
8.7 MAE

Experimental estimate. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.

Deployment readiness

Metadata index
72.5
partial · 80% metadata coverage
Not capability
Artifact reproducibility
100.0
Access & legal clarity
92.5
Deployability
80.0
Evaluation provenance
0.0

Not yet published: admitted benchmark results, results across several capability areas, results from more than one source, a confident match to its benchmark entries, pinned evaluation dataset versions.

A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.

Market activity

Venue coverage
Market Gravity
21.4
OpenRouter weekly popularity
Not listed

Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.

Arena preference

No matched Arena rating

This model is visible because it is available in the live catalogue, but it has no trustworthy community result yet. ModelCap does not infer a quality score from price, features, or market activity.

Market Gravity breakdown

Usage55%
0.0

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
35.7

Independent providers versus the model's open or closed cohort, weighted by uptime.

Open reach15%
50.0

Hugging Face 30-day downloads for open models; neutral for closed models.

Freshness5%
100.0

Time since first public availability, on a six-month half-life.

Specification

Model ID
liquid/lfm-2.5-24b-a2b
Context window
128K tokens
Declared output cap
8K tokens

OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata

Inputs
Text
Outputs
Text
Tokenizer
Other
Cached input tokens
$0.05 / 1M
First seen on OpenRouter
13 Oct 2026

Capabilities

  • Supported: Reasoning
  • Supported: Tool use
  • Supported: Structured output
  • Supported: Response format
  • Not supported: Moderated

Weights & access

Restricted license. Downloadable weights use a model-specific or use-restricted license. Review the linked license before use, redistribution, or commercial deployment.

Access
Restricted license
Licence
lfm1.0
Pinned revision
1769516ac588
Parameters
24.0B
Architecture
Lfm2MoeForCausalLM
Model type
lfm2_moe
Hugging Face downloads (30d)
3K
Downloads (all time)
3K
Likes
46
Repository updated
13 Oct 2026, 16:59 UTC

Alternatives to LFM2.5-24B-A2B, by the numbers

Ranked neighbours

Models within 3 places of #124 on the ModelCap Index.

Cheaper at a similar or higher Index

Index score within 3 points of, or above, this model's, with a lower listed blended price (3:1 input:output).

LFM2.5-24B-A2B: common questions

How does LFM2.5-24B-A2B rank among AI models?

LFM2.5-24B-A2B holds ModelCap Index position #124 of 359 ranked language models as of 13 October 2026, with an Index score of 48.3 (interval 36.1–60.4); evidence: modeled · peer benchmarks. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does LFM2.5-24B-A2B cost per 1M tokens?

LFM2.5-24B-A2B is listed at $0.10 per 1M input tokens and $1.00 per 1M output tokens as of 13 October 2026. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $0.70 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.

What is the context window of LFM2.5-24B-A2B?

LFM2.5-24B-A2B has a published context window of 128K tokens (128,000). The snapshot lists a 8,192 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.

Is LFM2.5-24B-A2B open-weight?

Restricted license (lfm1.0). Downloadable weights use a model-specific or use-restricted license. Review the linked license before use, redistribution, or commercial deployment. The repository is LiquidAI/LFM2.5-24B-A2B on Hugging Face.

Which API providers serve LFM2.5-24B-A2B?

One provider serves LFM2.5-24B-A2B through OpenRouter as of 13 October 2026: Liquid. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has LFM2.5-24B-A2B been evaluated on?

LFM2.5-24B-A2B's Index position rests on the evidence listed on this page; it has no result on the public boards ModelCap tracks as separate leaderboards as of 13 October 2026. The evidence panel names each source and its publication date.

When was LFM2.5-24B-A2B released?

LFM2.5-24B-A2B first appeared in the catalogue on 13 Oct 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.