Data as of October 27, 2026 · How the score is built
Released Oct 27, 2026256K contextLiquid AI LFM3-1.7B-Base model card
LFM3-1.7B-Base
Decision readingLFM3-1.7B-Base is tracked, but not publicly ranked yet. The profile exposes 0 sourced benchmark rows and leaves unsupported fields blank until a published record exists.
Released Oct 27, 2026 — see all recent releases
Lineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- LiquidAI/LFM3-1.7B-BaseLiquid AI LFM3-1.7B-Base model card
- Context window
- 256KLiquid AI LFM3-1.7B-Base model card
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not sourced yet
- Availability
- Liquid AI publishes the 1.73B-parameter pre-trained checkpoint in BF16 under the LFM Open License v1.0, with a 262,144-token context. Liquid recommends it only for heavy fine-tuning, continued pre-training or new post-training work, and points chat, tool-calling and agent use to LFM3-1.7B.
- Cloud regions
- Not tracked yet
- Lifecycle
- Current
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Not documented in the pricing recordLiquid AI LFM3-1.7B-Base model card
- Self-host
- Open weights available; hardware estimate not sourced
- Rate limits
- Not tracked yet
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
We track LFM3-1.7B-Base, but no weighted text-model benchmark result is published on the site yet. This page shows the metadata and separate protocol evidence we can verify now; a BenchLM score will appear only if compatible public evaluations land.
LFM3-1.7B-Base is a open weight model with a 256K context window. No explicit reasoning mode is documented in this profile.
Liquid AI publishes the 1.73B-parameter pre-trained checkpoint in BF16 under the LFM Open License v1.0, with a 262,144-token context. Liquid recommends it only for heavy fine-tuning, continued pre-training or new post-training work, and points chat, tool-calling and agent use to LFM3-1.7B.
Pre-trained base checkpoint behind every LFM3 model, trained on 22T tokens; the last 3.5T tokens are a mid-training stage that adds agentic traces and tool calls and extends the context to 256K tokens. Liquid publishes no benchmark results for the base checkpoint, so the row has no scores and stays unranked.
LFM3-1.7B-Base sits in the LFM3 family with LFM3-1.7B, LFM3-Audio-2B, LFM3-Omni-2B. The profile has no source-displayable benchmark row yet.
Last updated October 27, 2026. Runtime fields remain blank until a sourced snapshot exists.
Deployment options
Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.
Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.
Estimate VRAM from known parametersQuestions
How does LFM3-1.7B-Base perform overall in AI benchmarks?
LFM3-1.7B-Base does not have any source-displayable benchmark rows yet, so this profile does not assign a public score or rank. Documented specifications remain visible, while score-led charts and claims stay unavailable until a published evaluation can be attached to the exact model.
Is LFM3-1.7B-Base open source?
LFM3-1.7B-Base is an open-weight model from LiquidAI. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.
Which sibling models are related to LFM3-1.7B-Base?
LFM3-1.7B-Base belongs to the LFM3 family. Related tracked variants include LFM3-1.7B, LFM3-Audio-2B, LFM3-Omni-2B. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.
Does LFM3-1.7B-Base have full benchmark coverage on BenchLM?
No. LFM3-1.7B-Base currently has 0 source-displayable rows. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of LFM3-1.7B-Base?
LFM3-1.7B-Base has a documented context window of 256K. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.