liquid · Efficient
LFM2.5 24B A2B
Liquid AI's text-only mixture-of-experts model for reasoning and tool-using agents, with 24B total and 2.45B active parameters. It always thinks before answering and supports structured output. Pair it with retrieval for knowledge-heavy tasks. Open weights use the LFM Open License v1.0, with a $10M annual-revenue commercial threshold; hosted API use is subject to separate service terms that permit retention and use of prompts and responses for model training.
- Reasoning
- Tools
- Structured output
- Input
- Text
- Output
- Text
- Discovery tier
- Efficient
Pricing
USD per 1M tokens- Input
- $0.05
- Output
- $0.70
- Cache read
- $0.025
Reference prices as published by the model provider. API example
Specifications
- Context window
- 128K
- Max output
- 8.2K
- Average output (7 days)
- 5.1K tokens
- Longer than 99% of 465 models
Side by side
LFM2.5 24B A2B compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| LFM2.5 24B A2BliquidThis model | LFM2.5 2.6BliquidRemove | |
|---|---|---|
| Provider | liquid | liquid |
| Discovery tier | Efficient | Open weights |
| Added | Oct 14, 2026 | Aug 12, 2026 |
| Limits | ||
| Context window | 128K | 128K |
| Max output | 8.19K | 32.77KBest |
| Average output | 5.1K tokens | 459 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.05Best | $0.10 |
| Output | $0.70 | $0.20Best |
| Cache read | $0.025 | — |
| Performance | ||
| Request success (24h) | 100.0% | 100.0% |
| Benchmark indexes | ||
| Intelligence Index | — | 8.4 |
| Coding Index | — | 7.7 |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Structured output | Yes | Yes |
| Reasoning effort | — | minimal, low, medium, high, xhigh |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- LFM2.5 24B A2B
- LFM2.5 2.6B
Intelligence Index
- LFM2.5 24B A2B—
- LFM2.5 2.6B8.4
Indexes
Coding Index
Composite of the coding evaluations
- LFM2.5 24B A2B: —
- LFM2.5 2.6B: 7.7
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- LFM2.5 24B A2B: —
- LFM2.5 2.6B: 5.7%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- LFM2.5 24B A2B: —
- LFM2.5 2.6B: 6.2%
GPQA Diamond
Graduate-level science questions
- LFM2.5 24B A2B: —
- LFM2.5 2.6B: 55.8%
Coding
SciCode
Scientific computing in Python
- LFM2.5 24B A2B: —
- LFM2.5 2.6B: 14.4%
Legacy evaluations
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- LFM2.5 24B A2B: —
- LFM2.5 2.6B: 5.7%
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Request success (24h)
- 100.0%
- Reliable
- Healthy (98% or more)
- Degraded (90–98%)
- Down (under 90%)
- No requests
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "liquid/lfm-2.5-24b-a2b",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="liquid/lfm-2.5-24b-a2b",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)liquid
Related models
Other liquid models, starting with the same family.
- Open weights