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DeepSeek-V4.1-Flash vs LFM3-1.7B

DeepSeek-V4.1-Flash leads the LLM Stats Score 49.5 to 25.0.

DeepSeek · Liquid AI · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 49.5 to 25.0, ranking #24 overall.

In the 4 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 4; 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-V4.1-Flash

  • overall performance matters — it scores 49.5 and ranks #24 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 4 of 4 exact shared results

Choose LFM3-1.7B

  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash
DeepSeek
LFM3-1.7B
Liquid AI
Core performance indexes
LLM Stats Score
49.5
#24
25.0
#191
Reasoning
47.1
#27
20.8
#216
Coding
40.8
#13
7.4
#218
Agents
38.2
#15
18.1
#97
Cost, coverage & limits
Benchmark wins
4 of 4
0 of 4
Input price
$0.22 / M
— / M
Output price
$0.66 / M
— / M
Context window
1,040,000
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek-V4.1-Flash
LFM3-1.7B
Math
35.3#46
7.6#285
Tool use
32.1#7
14.3#118
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 20 for LFM3-1.7B

4 shared

DeepSeek-V4.1-Flash outperforms in 4 benchmarks (AutomationBench, GPQA, Humanity's Last Exam, Terminal-Bench 2.1), while LFM3-1.7B is better at 0 benchmarks.

DeepSeek-V4.1-Flash significantly outperforms across most benchmarks.

Thu Nov 05 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

761.5B diff

DeepSeek-V4.1-Flash has 761.5B more parameters than LFM3-1.7B, making it 44015.9% larger.

DeepSeek
DeepSeek-V4.1-Flash
763.2Bparameters
Liquid AI
LFM3-1.7B
1.7Bparameters
763.2B
DeepSeek-V4.1-Flash
1.7B
LFM3-1.7B

Context Window

Maximum input and output token capacity

Only DeepSeek-V4.1-Flash specifies input context (1,040,000 tokens). Only DeepSeek-V4.1-Flash specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
Liquid AI
LFM3-1.7B
Input- tokens
Output- tokens
Thu Nov 05 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash supports multimodal inputs, whereas LFM3-1.7B does not.

DeepSeek-V4.1-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4.1-Flash

Text
Images
Audio
Video

LFM3-1.7B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash 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-V4.1-Flash

MIT

Open weights

LFM3-1.7B

LFM Open License v1.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while LFM3-1.7B was released on 2026-10-27.

LFM3-1.7B is 2 months newer than DeepSeek-V4.1-Flash.

DeepSeek-V4.1-Flash

Sep 10, 2026

1 months ago

LFM3-1.7B

Oct 27, 2026

1 weeks ago

1mo 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-V4.1-Flash and LFM3-1.7B side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash
✓ Preferred
LFM3-1.7B
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash vs LFM3-1.7B.

Which is better, DeepSeek-V4.1-Flash or LFM3-1.7B?

DeepSeek-V4.1-Flash leads the LLM Stats Score 49.5 to 25.0. DeepSeek-V4.1-Flash 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-V4.1-Flash compare to LFM3-1.7B in benchmarks?

DeepSeek-V4.1-Flash scores CodeForces: 100.0%, GPQA: 90.9%, Terminal-Bench 2.1: 90.6%, BabyVision: 89.6%, CyberGym: 88.1%. 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 DeepSeek-V4.1-Flash and LFM3-1.7B?

DeepSeek-V4.1-Flash 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 DeepSeek-V4.1-Flash and LFM3-1.7B?

Key differences include LLM Stats Score (49.5 vs 25.0), multimodal support (yes vs no), licensing (MIT vs LFM Open License v1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash and LFM3-1.7B?

DeepSeek-V4.1-Flash is developed by DeepSeek and LFM3-1.7B is developed by Liquid AI.

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