LFM2.5 8B A1B
LFM2.5 8B A1B is a released rag, agents, and long context model with open-weight and 128k context; evaluate it while provider pricing coverage matures.
Use it for
- Teams evaluating rag, agents, and long context
- Workloads that can use a 128k context window
Do not use it for
- Cost-sensitive launches that need sourced token pricing
- Vision or document-understanding workloads
- Teams that need a tracked hosted API route today
- Family
- LFM-2.5
- Released
- 2026-05-28
- Context
- 128k
- Max output
- 8,192
- Parameters
- 8.3B
- Architecture
- Mixture of Experts
- Specialization
- general
- Openness
- Open weights
- License
- LFM Open License v1.0Commercial use: conditional
- Weights
- Available
- Code
- Unknown
- Training
- Pretrained
No tracked provider token pricing is available yet.
About
LFM2.5-8B-A1B is Liquid AI's latest on-device mixture-of-experts model, succeeding LFM2-8B-A1B. It has 8.3B total parameters with approximately 1.5B active per token (the A1B label uses a rounded ~1B figure). The architecture combines 18 double-gated LIV convolutional layers with 6 GQA attention layers, trained on 38 trillion tokens. The context window expands to 128K tokens (up from 32K in the predecessor). It is a reasoning model that generates explicit chain-of-thought steps before producing its final answer, making reasoning tokens cheap due to the MoE design. Strong tool-calling, function-calling, and instruction-following capabilities make it well-suited for agentic workflows on edge hardware.
Top use-case fit: coding, agents, and build tasks
RAG
Included by capability and metadata signals in the decision map.
Agents
1 relevant benchmark in the decision map.
Long context
Included by capability and metadata signals in the decision map.
Provider price ladder
No tracked provider token pricing is available for this model yet.
Capabilities
Benchmark peer barsfor Agents
Benchmark scores(6)
| Benchmark | Score | Version | Evaluation | Source |
|---|---|---|---|---|
| Instruction-Following Evaluation | 91.8 | —Observed 2026-05-28 | — | Source |
| MATH-500 | 88.8 | MATH-500 (accuracy)Observed 2026-06-07 | — | Source |
| AIME 2025 | 42.5 | —Observed 2026-05-28 | — | Source |
| Google-Proof Q&A | 34.4 | GPQA Diamond (accuracy)Observed 2026-06-07 | — | Source |
| MMLU PRO | 50.5 | Third-party evaluation (accuracy)Observed 2026-06-07 | — | Source |
| τ-bench | 88.1 | τ² Telecom benchmark (accuracy)Observed 2026-06-07 | — | Source |
Migration checks
No linked migration route is available for this model yet.
No tracked provider token pricing is available yet.