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GPT-4.1 nano vs LFM3-1.7B

LFM3-1.7B leads the LLM Stats Score 25.0 to 1.0.

OpenAI · Liquid AI · Updated for 2026

Which is better?

LFM3-1.7B leads the overall LLM Stats Score 25.0 to 1.0, ranking #191 overall.

In the 3 individual benchmarks reported for both models, LFM3-1.7B wins 3; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose GPT-4.1 nano

  • you want predictable pricing at $0.10/M input and $0.40/M output

Choose LFM3-1.7B

  • overall performance matters — it scores 25.0 and ranks #191 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 3 of 3 exact shared results
  • you want the most recent training data — it shipped Oct 2026
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Core performance indexes
1.0
#360
25.0
#191
1.4
#348
20.8
#216
-12.1
#302
7.4
#218
Cost, coverage & limits
Benchmark wins
0 of 3
3 of 3
Input price
$0.10 / M
— / M
Output price
$0.40 / M
— / M
Context window
1,047,576
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
GPT-4.1 nano
LFM3-1.7B
4.8#298
7.6#285
-10.7#230
14.3#118
1.5#124
5.1#112
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

24 reported for GPT-4.1 nano · 20 for LFM3-1.7B

3 shared

GPT-4.1 nano outperforms in 0 benchmarks, while LFM3-1.7B is better at 3 benchmarks (GPQA, IFEval, Multi-IF).

LFM3-1.7B significantly outperforms across most benchmarks.

Wed Nov 04 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only GPT-4.1 nano specifies input context (1,047,576 tokens). Only GPT-4.1 nano specifies output context (32,768 tokens).

OpenAI
GPT-4.1 nano
Input1,047,576 tokens
Output32,768 tokens
Liquid AI
LFM3-1.7B
Input- tokens
Output- tokens
Wed Nov 04 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

GPT-4.1 nano supports multimodal inputs, whereas LFM3-1.7B does not.

GPT-4.1 nano can handle both text and other forms of data like images, making it suitable for multimodal applications.

GPT-4.1 nano

Text
Images
Audio
Video

LFM3-1.7B

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-4.1 nano is licensed under a proprietary license, while LFM3-1.7B uses LFM Open License v1.0.

License differences may affect how you can use these models in commercial or open-source projects.

GPT-4.1 nano

Proprietary

Closed source

LFM3-1.7B

LFM Open License v1.0

Open weights

Release Timeline

When each model was launched

GPT-4.1 nano was released on 2025-04-14, while LFM3-1.7B was released on 2026-10-27.

LFM3-1.7B is 19 months newer than GPT-4.1 nano.

GPT-4.1 nano

Apr 14, 2025

1.6 years ago

LFM3-1.7B

Oct 27, 2026

1 weeks ago

1.5yr newer

Knowledge Cutoff

When training data ends

GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while LFM3-1.7B's cutoff date is not specified.

We can confirm GPT-4.1 nano's training data extends to 2024-05-31, but cannot make a direct comparison without LFM3-1.7B's cutoff date.

GPT-4.1 nano

May 2024

LFM3-1.7B

—

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against GPT-4.1 nano and LFM3-1.7B side-by-side, then vote on the output you prefer.

GPT-4.1 nano
✓ Preferred
LFM3-1.7B
Open in Playground

FAQ

Common questions about GPT-4.1 nano vs LFM3-1.7B.

Which is better, GPT-4.1 nano or LFM3-1.7B?

LFM3-1.7B leads the LLM Stats Score 25.0 to 1.0. GPT-4.1 nano is made by OpenAI and LFM3-1.7B is made by Liquid AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GPT-4.1 nano compare to LFM3-1.7B in benchmarks?

GPT-4.1 nano scores MMLU: 80.1%, IFEval: 74.5%, CharXiv-D: 73.9%, MMMLU: 66.9%, Multi-IF: 57.2%. LFM3-1.7B scores IFEval: 96.7%, Multi-IF: 89.1%, LiveCodeBench v6: 73.5%, IFBench: 73.0%, BFCL-V4: 71.4%.

What are the context window sizes for GPT-4.1 nano and LFM3-1.7B?

GPT-4.1 nano supports 1.0M tokens and LFM3-1.7B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT-4.1 nano and LFM3-1.7B?

Key differences include LLM Stats Score (1.0 vs 25.0), multimodal support (yes vs no), licensing (Proprietary vs LFM Open License v1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-4.1 nano and LFM3-1.7B?

GPT-4.1 nano is developed by OpenAI and LFM3-1.7B is developed by Liquid AI.