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DeepSeek-V3 vs LFM2.5-VL-3B

DeepSeek-V3 significantly outperforms across most benchmarks.

DeepSeek · Liquid AI · Updated for 2026

Which is better?

DeepSeek-V3 outperforms in 1 benchmarks (IFEval), while LFM2.5-VL-3B is better at 0 benchmarks. DeepSeek-V3 significantly outperforms across most benchmarks.

Based on current benchmark, pricing, and model metadata for 2026.

Choose DeepSeek-V3

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks

Choose LFM2.5-VL-3B

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

At a glance

The differences that matter most.

DeepSeek-V3
DeepSeek
LFM2.5-VL-3B
Liquid AI
Benchmark wins
1 of 1
0 of 1
Input price
$0.27 / M
— / M
Output price
$1.10 / M
— / M
Context window
131,072
—
Released
Dec 2024
Aug 2026
License
MIT + Model License (Commercial use allowed)
LFM Open License v1.0

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek-V3 outperforms in 1 benchmarks (IFEval), while LFM2.5-VL-3B is better at 0 benchmarks.

DeepSeek-V3 significantly outperforms across most benchmarks.

Mon Aug 24 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

667.9B diff

DeepSeek-V3 has 667.9B more parameters than LFM2.5-VL-3B, making it 21382.4% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
Liquid AI
LFM2.5-VL-3B
3.1Bparameters
671.0B
DeepSeek-V3
3.1B
LFM2.5-VL-3B

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 specifies input context (131,072 tokens). Only DeepSeek-V3 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Liquid AI
LFM2.5-VL-3B
Input- tokens
Output- tokens
Mon Aug 24 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

LFM2.5-VL-3B supports multimodal inputs, whereas DeepSeek-V3 does not.

LFM2.5-VL-3B can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3

Text
Images
Audio
Video

LFM2.5-VL-3B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while LFM2.5-VL-3B uses LFM Open License v1.0.

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

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

LFM2.5-VL-3B

LFM Open License v1.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while LFM2.5-VL-3B was released on 2026-08-12.

LFM2.5-VL-3B is 20 months newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.7 years ago

LFM2.5-VL-3B

Aug 12, 2026

1 weeks 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?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V3 and LFM2.5-VL-3B side-by-side, then vote on the output you prefer.

DeepSeek-V3
✓ Preferred
LFM2.5-VL-3B
Open in Playground

FAQ

Common questions about DeepSeek-V3 vs LFM2.5-VL-3B.

Which is better, DeepSeek-V3 or LFM2.5-VL-3B?

DeepSeek-V3 significantly outperforms across most benchmarks. DeepSeek-V3 is made by DeepSeek and LFM2.5-VL-3B is made by Liquid AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V3 compare to LFM2.5-VL-3B in benchmarks?

DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. LFM2.5-VL-3B scores DocVQA: 91.1%, POPE: 88.7%, RefCOCO-avg: 87.9%, TextVQA: 84.3%, OCRBench: 84.2%.

What are the context window sizes for DeepSeek-V3 and LFM2.5-VL-3B?

DeepSeek-V3 supports 131K tokens and LFM2.5-VL-3B 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 and LFM2.5-VL-3B?

Key differences include 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 and LFM2.5-VL-3B?

DeepSeek-V3 is developed by DeepSeek and LFM2.5-VL-3B is developed by Liquid AI.

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