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Coding & app building

Liquid AI

By liquid.ai

Liquid AI is a strong fit for evaluate an open-weight model for agent workloads, with a profile optimized for advanced users who value medium ease-of-use and medium output quality.

Best for: Evaluate an open-weight model for agent workloads

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What it is

Liquid AI's efficient language-model family for developers choosing hosted or deployable open-weight models; LFM2.5-24B-A2B targets agent and reasoning workloads with sparse active parameters.

In Choosely terms, this sits in the coding & app building lane and is commonly selected for evaluate an open-weight model for agent workloads and compare local versus hosted lfm inference.

Pricing

Usage-based

Check official pricing

Released weights can be used under the LFM Open License, free for qualifying organizations below $10M annual revenue; larger deployments require commercial terms. Official hosted API lists $0.05/M input, $0.025/M cached input and $0.70/M output tokens for LFM2.5-24B-A2B; new organizations receive $2 in credits. Hardware and hosting costs are separate.

Basis: Usage BasedConfidence: VerifiedLast checked: October 2026

Why people pick it vs where it falls short

Why people pick it

  • Downloadable weights alongside an official API
  • 24B-total / 2B-active LFM2.5-24B-A2B architecture
  • Published 131K-token context for the new model

Where it falls short

  • The LFM Open License is conditional, including a $10M annual-revenue threshold; not Apache-2.0
  • Self-hosting requires a separate inference runtime and sufficient hardware
  • Speed and quality claims largely come from vendor tests; independent results vary by workload

When it is a strong fit

A strong match when your main priority is evaluate an open-weight model for agent workloads and you need an advanced-friendly starting point.

Useful when your team values medium ease of use and fast execution over heavier setup.

Best when medium quality matters, but you still want a practical workflow rather than a complex implementation track.

How it compares in Choosely terms

  • Speed profile: Fast. This is best when you want momentum from prompt to usable output without heavy process overhead.
  • Ease profile: Medium for Advanced users. You can move quickly even if this is not your full-time specialty.
  • Control profile: High. Expect practical customization, but not an infinite-control architecture.
  • Pricing signal: Usage-based. Good for teams balancing capability with cost sensitivity.
Tradeoff: The LFM Open License is conditional, including a $10M annual-revenue threshold; not Apache-2.0.

Best-fit use cases

Practical ways Liquid AI fits the current Choosely catalog profile.

Open Weight Model Evaluation For Agents

Strong lane

Use Liquid AI for open weight model evaluation for agents when you want fast execution, medium ease of use, and medium output quality.

Efficient Local Or Hosted Reasoning Model

Strong lane

Use Liquid AI for efficient local or hosted reasoning model when you want fast execution, medium ease of use, and medium output quality.

Long Context Model API Integration

Strong lane

Use Liquid AI for long context model api integration when you want fast execution, medium ease of use, and medium output quality.

Alternatives

DeepSeek

General AI assistant for reasoning, technical help and drafting. The same family also offers DeepSeek Harness, an open-source desktop agent harness for coding and everyday work in public preview; Harness is a separate workflow from DeepSeek chat.

Choose DeepSeek when your primary need is reasoning-heavy prompts.

View tool profile

Inception Mercury

Inception's closed-weights diffusion-LLM API — Mercury 2.5 is Inception's most capable production model, tuned for extremely low latency and high throughput on supporting agent calls, RAG substeps, context compaction and structured, low-cost generation.

Choose Inception Mercury when your primary need is extremely latency-sensitive or high-throughput llm api calls.

View tool profile

Next step

Run a representative agent task against the hosted API and locally deployed weights, compare quality, cost and memory, and review the LFM license for your organization.

Get a best-fit recommendation →Browse all tools

Related reads

Compare Liquid AI vs DeepSeekCompare Liquid AI vs Inception MercuryExplore Adalo for adjacent workflowsBest AI app builder in 2026

FAQ

What is Liquid AI best for?

Liquid AI is best for evaluate an open-weight model for agent workloads, compare local versus hosted lfm inference, build a model-backed application with measured latency and quality.

Is Liquid AI beginner-friendly?

This catalog profile lists Liquid AI at advanced skill level with medium ease of use.

What should I watch out for before choosing Liquid AI?

The LFM Open License is conditional, including a $10M annual-revenue threshold; not Apache-2.0