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DeepSeek R1 Zero vs LFM3-1.7B

LFM3-1.7B leads the LLM Stats Score 25.0 to 15.4.

DeepSeek · Liquid AI · Updated for 2026

Which is better?

LFM3-1.7B leads the overall LLM Stats Score 25.0 to 15.4, ranking #192 overall.

In the 1 individual benchmarks reported for both models, DeepSeek R1 Zero wins 1; 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 DeepSeek R1 Zero

  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results

Choose LFM3-1.7B

  • overall performance matters — it scores 25.0 and ranks #192 on LLM Stats
  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

DeepSeek R1 Zero
DeepSeek
LFM3-1.7B
Liquid AI
Core performance indexes
LLM Stats Score
15.4
#266
25.0
#192
Reasoning
15.8
#256
20.8
#216
Coding
4.2
#242
7.4
#218
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
— / M
— / M
Output price
— / M
— / M
Context window
—
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek R1 Zero
LFM3-1.7B
Math
17.5#209
7.6#285
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

4 reported for DeepSeek R1 Zero · 20 for LFM3-1.7B

1 shared

DeepSeek R1 Zero outperforms in 1 benchmarks (GPQA), while LFM3-1.7B is better at 0 benchmarks.

DeepSeek R1 Zero significantly outperforms across most benchmarks.

Tue Nov 03 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

669.3B diff

DeepSeek R1 Zero has 669.3B more parameters than LFM3-1.7B, making it 38686.1% larger.

DeepSeek
DeepSeek R1 Zero
671.0Bparameters
Liquid AI
LFM3-1.7B
1.7Bparameters
671.0B
DeepSeek R1 Zero
1.7B
LFM3-1.7B

License

Usage and distribution terms

DeepSeek R1 Zero is licensed under MIT, 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.

DeepSeek R1 Zero

MIT

Open weights

LFM3-1.7B

LFM Open License v1.0

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Zero was released on 2025-01-20, while LFM3-1.7B was released on 2026-10-27.

LFM3-1.7B is 22 months newer than DeepSeek R1 Zero.

DeepSeek R1 Zero

Jan 20, 2025

1.8 years ago

LFM3-1.7B

Oct 27, 2026

4 days ago

1.8yr newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek R1 Zero and LFM3-1.7B side-by-side, then vote on the output you prefer.

DeepSeek R1 Zero
✓ Preferred
LFM3-1.7B
Open in Playground

FAQ

Common questions about DeepSeek R1 Zero vs LFM3-1.7B.

Which is better, DeepSeek R1 Zero or LFM3-1.7B?

LFM3-1.7B leads the LLM Stats Score 25.0 to 15.4. DeepSeek R1 Zero is made by DeepSeek 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 DeepSeek R1 Zero compare to LFM3-1.7B in benchmarks?

DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. 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 main differences between DeepSeek R1 Zero and LFM3-1.7B?

Key differences include LLM Stats Score (15.4 vs 25.0), licensing (MIT vs LFM Open License v1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Zero and LFM3-1.7B?

DeepSeek R1 Zero is developed by DeepSeek and LFM3-1.7B is developed by Liquid AI.

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