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DeepSeek-V3 0324 vs LFM3-VL-2B

DeepSeek-V3 0324 and LFM3-VL-2B are closely matched at 12.8 and 15.5 on the LLM Stats Score.

DeepSeek · Liquid AI · Updated for 2026

Which is better?

DeepSeek-V3 0324 and LFM3-VL-2B are closely matched on the overall LLM Stats Score at 12.8 and 15.5.

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

Choose DeepSeek-V3 0324

  • you want predictable pricing at $0.24/M input and $0.90/M output

Choose LFM3-VL-2B

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

At a glance

The differences that matter most.

DeepSeek-V3 0324
DeepSeek
LFM3-VL-2B
Liquid AI
Core performance indexes
LLM Stats Score
12.8
#283
15.5
#265
Reasoning
13.1
#274
16.2
#252
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.24 / M
— / M
Output price
$0.90 / M
— / M
Context window
163,840
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V3 0324
LFM3-VL-2B
Math
15.7#229
19.0#187
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

5 reported for DeepSeek-V3 0324 · 41 for LFM3-VL-2B

No common benchmarks found

DeepSeek-V3 0324 and LFM3-VL-2Bdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

669.1B diff

DeepSeek-V3 0324 has 669.1B more parameters than LFM3-VL-2B, making it 34847.9% larger.

DeepSeek
DeepSeek-V3 0324
671.0Bparameters
Liquid AI
LFM3-VL-2B
1.9Bparameters
671.0B
DeepSeek-V3 0324
1.9B
LFM3-VL-2B

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 0324 specifies input context (163,840 tokens). Only DeepSeek-V3 0324 specifies output context (163,840 tokens).

DeepSeek
DeepSeek-V3 0324
Input163,840 tokens
Output163,840 tokens
Liquid AI
LFM3-VL-2B
Input- tokens
Output- tokens
Tue Nov 03 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

LFM3-VL-2B supports multimodal inputs, whereas DeepSeek-V3 0324 does not.

LFM3-VL-2B can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3 0324

Text
Images
Audio
Video

LFM3-VL-2B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3 0324 is licensed under MIT + Model License (Commercial use allowed), while LFM3-VL-2B uses LFM Open License v1.0.

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

DeepSeek-V3 0324

MIT + Model License (Commercial use allowed)

Open weights

LFM3-VL-2B

LFM Open License v1.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 0324 was released on 2025-03-25, while LFM3-VL-2B was released on 2026-10-27.

LFM3-VL-2B is 19 months newer than DeepSeek-V3 0324.

DeepSeek-V3 0324

Mar 25, 2025

1.6 years ago

LFM3-VL-2B

Oct 27, 2026

6 days ago

1.6yr 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-V3 0324 and LFM3-VL-2B side-by-side, then vote on the output you prefer.

DeepSeek-V3 0324
✓ Preferred
LFM3-VL-2B
Open in Playground

FAQ

Common questions about DeepSeek-V3 0324 vs LFM3-VL-2B.

Which is better, DeepSeek-V3 0324 or LFM3-VL-2B?

DeepSeek-V3 0324 and LFM3-VL-2B are closely matched on the LLM Stats Score at 12.8 and 15.5. DeepSeek-V3 0324 is made by DeepSeek and LFM3-VL-2B 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-V3 0324 compare to LFM3-VL-2B in benchmarks?

DeepSeek-V3 0324 scores MATH-500: 94.0%, MMLU-Pro: 81.2%, GPQA: 68.4%, AIME 2024: 59.4%, LiveCodeBench: 49.2%. LFM3-VL-2B scores DocVQA: 96.7%, CountBench: 93.0%, ChartQA: 92.7%, RefCOCO-avg: 90.5%, POPE: 88.7%.

What are the context window sizes for DeepSeek-V3 0324 and LFM3-VL-2B?

DeepSeek-V3 0324 supports 164K tokens and LFM3-VL-2B 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-V3 0324 and LFM3-VL-2B?

Key differences include LLM Stats Score (12.8 vs 15.5), multimodal support (no vs yes), licensing (MIT + Model License (Commercial use allowed) vs LFM Open License v1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3 0324 and LFM3-VL-2B?

DeepSeek-V3 0324 is developed by DeepSeek and LFM3-VL-2B is developed by Liquid AI.

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