Atlas / Models / Liquid / LiquidAI: LFM2.5-2.6B

LiquidAI: LFM2.5-2.6B✓ Catalog verified

liquid/lfm-2.5-2.6b

LFM2.5-2.6B is a compact reasoning model from Liquid AI. It is suited for agent workflows, data extraction, RAG, and long-context processing. Liquid advises against using it for agentic coding or...

Input price
$0.35 /1M
Output price
$0.50 /1M
Context
128K
Modalities
text
Released
Aug 11, 2026
Tool calling
✓ Yes
Atlas signal
87/100
01

Overview

LFM2.5-2.6B is a compact reasoning model from Liquid AI. It is suited for agent workflows, data extraction, RAG, and long-context processing. Liquid advises against using it for agentic coding or...

Access: available through the official Liquid API. Context window: 128K.

Pricing and metadata from the ModelsAtlas catalog.Last refreshed Oct 25, 2026
02

Specifications

API identifierliquid/lfm-2.5-2.6b
ProviderLiquid
Model typeText LLM
Context window128K catalog
Input modalitiestext
Output modalitiestext
ReleasedAug 11, 2026
ModeratedNo
Architecture modalitytext->text
Supported parameters
frequency_penaltyinclude_reasoninglogprobsmax_completion_tokensmax_tokensmin_ppresence_penaltyreasoningrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_p
Source: provider documentation + catalog feedMethodology →

API defaults

Default parameters
{
  "top_k": 50,
  "temperature": 0.1,
  "repetition_penalty": 1.1
}
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03

Pricing

Live pricing components for liquid/lfm-2.5-2.6b as published in the catalog.

$0.35
Input /1M
$0.50
Output /1M
—
Per request
—
Per image
Pricing componentRaw unit priceNormalizedUnit
Prompt tokens$3.5e-7$0.35 / 1MPer input token
Completion tokens$5e-7$0.50 / 1MPer output token
Request feeN/AN/APer request
Image feeN/AN/APer image unit
Web search feeN/AN/APer search request
Source: catalog pricing feedCompare all pricing →Cheapest models →
04

Cost calculator

Estimate monthly spend from your own token volumes.

Scale / Volume

Estimated Total Cost

$0.28Calculated from current list pricing in the ModelsAtlas catalog.
05

Capabilities

CapabilityStatusWhat it means
Visual UnderstandingNot advertisedImage and document analysis support
Audio ProcessingNot advertisedSpeech and voice aligned flows
Tool Calling✓ SupportedSupports tools / function calling
Self-HostingNot advertisedDeploy outside managed APIs
Derived from catalog capability tags and supported parameters
06

Capability signals

Directional signals derived from model metadata and capability tags — not official benchmark submissions.

LiquidAI: LFM2.5-2.6B
MMLU Signal (Reasoning)
97signal
Coding Signal (HumanEval proxy)
88signal
Math Signal (GSM8K proxy)
83signal
Science Signal (GPQA proxy)
79signal
Estimated from metadata — not an official benchmark runAll benchmarks →Methodology →
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07

Quick start

Call LiquidAI: LFM2.5-2.6B through an OpenAI-compatible client.

from openai import OpenAI

client = OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="liquid/lfm-2.5-2.6b",
    messages=[{"role": "user", "content": "Explain quantum physics."}]
)

print(response.choices[0].message.content)
08

Alternatives

Closest models by context window from a different provider.

09

Sources & attribution

Pricing and metadata are maintained in the ModelsAtlas catalog.

Capability bars use metadata tags — directional estimates onlyHow we source and verify data →
10

Frequently asked questions

How much does LiquidAI: LFM2.5-2.6B cost?

$0.35 per 1M input tokens and $0.50 per 1M output tokens on the official Liquid API.

What is the context window of LiquidAI: LFM2.5-2.6B?

LiquidAI: LFM2.5-2.6B supports up to 128K tokens of context.

Does LiquidAI: LFM2.5-2.6B support tool / function calling?

Yes, LiquidAI: LFM2.5-2.6B supports tool / function calling — you can register tools and the model will emit structured tool calls.

How do I access LiquidAI: LFM2.5-2.6B?

Use the official Liquid API with the model id `liquid/lfm-2.5-2.6b`. See the Quick start section above for code examples.

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