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LFM3-VL-2B vs Phi-4-multimodal-instruct

LFM3-VL-2B leads the LLM Stats Score 15.5 to 2.3.

Liquid AI · Microsoft · Updated for 2026

Which is better?

LFM3-VL-2B leads the overall LLM Stats Score 15.5 to 2.3, ranking #265 overall.

In the 8 individual benchmarks reported for both models, LFM3-VL-2B wins 8; 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 LFM3-VL-2B

  • overall performance matters — it scores 15.5 and ranks #265 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 8 of 8 exact shared results
  • you want the most recent training data — it shipped Oct 2026

Choose Phi-4-multimodal-instruct

  • you want predictable pricing at $0.05/M input and $0.10/M output

At a glance

The differences that matter most.

LFM3-VL-2B
Liquid AI
Phi-4-multimodal-instruct
Microsoft
Core performance indexes
LLM Stats Score
15.5
#265
2.3
#352
Reasoning
16.2
#252
-0.7
#361
Cost, coverage & limits
Benchmark wins
8 of 8
0 of 8
Input price
— / M
$0.05 / M
Output price
— / M
$0.10 / M
Context window
—
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
LFM3-VL-2B
Phi-4-multimodal-instruct
Vision
11.4#133
1.4#202
Multimodal
12.6#124
3.3#164
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

41 reported for LFM3-VL-2B · 15 for Phi-4-multimodal-instruct

8 shared

LFM3-VL-2B outperforms in 8 benchmarks (BLINK, ChartQA, DocVQA, InfoVQA, MMMU-Pro, OCRBench, POPE, TextVQA), while Phi-4-multimodal-instruct is better at 0 benchmarks.

LFM3-VL-2B 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

3.7B diff

Phi-4-multimodal-instruct has 3.7B more parameters than LFM3-VL-2B, making it 191.7% larger.

Liquid AI
LFM3-VL-2B
1.9Bparameters
Microsoft
Phi-4-multimodal-instruct
5.6Bparameters
1.9B
LFM3-VL-2B
5.6B
Phi-4-multimodal-instruct

Context Window

Maximum input and output token capacity

Only Phi-4-multimodal-instruct specifies input context (128,000 tokens). Only Phi-4-multimodal-instruct specifies output context (128,000 tokens).

Liquid AI
LFM3-VL-2B
Input- tokens
Output- tokens
Microsoft
Phi-4-multimodal-instruct
Input128,000 tokens
Output128,000 tokens
Tue Nov 03 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both LFM3-VL-2B and Phi-4-multimodal-instruct support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

LFM3-VL-2B

Text
Images
Audio
Video

Phi-4-multimodal-instruct

Text
Images
Audio
Video

License

Usage and distribution terms

LFM3-VL-2B is licensed under LFM Open License v1.0, while Phi-4-multimodal-instruct uses MIT.

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

LFM3-VL-2B

LFM Open License v1.0

Open weights

Phi-4-multimodal-instruct

MIT

Open weights

Release Timeline

When each model was launched

LFM3-VL-2B was released on 2026-10-27, while Phi-4-multimodal-instruct was released on 2025-02-01.

LFM3-VL-2B is 21 months newer than Phi-4-multimodal-instruct.

LFM3-VL-2B

Oct 27, 2026

4 days ago

1.7yr newer
Phi-4-multimodal-instruct

Feb 1, 2025

1.7 years ago

Knowledge Cutoff

When training data ends

Phi-4-multimodal-instruct has a documented knowledge cutoff of 2024-06-01, while LFM3-VL-2B's cutoff date is not specified.

We can confirm Phi-4-multimodal-instruct's training data extends to 2024-06-01, but cannot make a direct comparison without LFM3-VL-2B's cutoff date.

LFM3-VL-2B

—

Phi-4-multimodal-instruct

Jun 2024

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against LFM3-VL-2B and Phi-4-multimodal-instruct side-by-side, then vote on the output you prefer.

LFM3-VL-2B
✓ Preferred
Phi-4-multimodal-instruct
Open in Playground

FAQ

Common questions about LFM3-VL-2B vs Phi-4-multimodal-instruct.

Which is better, LFM3-VL-2B or Phi-4-multimodal-instruct?

LFM3-VL-2B leads the LLM Stats Score 15.5 to 2.3. LFM3-VL-2B is made by Liquid AI and Phi-4-multimodal-instruct is made by Microsoft. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does LFM3-VL-2B compare to Phi-4-multimodal-instruct in benchmarks?

LFM3-VL-2B scores DocVQA: 96.7%, CountBench: 93.0%, ChartQA: 92.7%, RefCOCO-avg: 90.5%, POPE: 88.7%. Phi-4-multimodal-instruct scores ScienceQA Visual: 97.5%, DocVQA: 93.2%, MMBench: 86.7%, POPE: 85.6%, OCRBench: 84.4%.

What are the context window sizes for LFM3-VL-2B and Phi-4-multimodal-instruct?

LFM3-VL-2B supports an unknown number of tokens and Phi-4-multimodal-instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between LFM3-VL-2B and Phi-4-multimodal-instruct?

Key differences include LLM Stats Score (15.5 vs 2.3), licensing (LFM Open License v1.0 vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes LFM3-VL-2B and Phi-4-multimodal-instruct?

LFM3-VL-2B is developed by Liquid AI and Phi-4-multimodal-instruct is developed by Microsoft.

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