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GLM-5.3-Flash vs LFM3-VL-2B

GLM-5.3-Flash leads the LLM Stats Score 48.3 to 15.5.

Zhipu AI · Liquid AI · Updated for 2026

Which is better?

GLM-5.3-Flash leads the overall LLM Stats Score 48.3 to 15.5, ranking #32 overall.

In the 3 individual benchmarks reported for both models, GLM-5.3-Flash wins 3; 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 GLM-5.3-Flash

  • overall performance matters — it scores 48.3 and ranks #32 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 3 of 3 exact shared results

Choose LFM3-VL-2B

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

At a glance

The differences that matter most.

GLM-5.3-Flash
Zhipu AI
LFM3-VL-2B
Liquid AI
Core performance indexes
LLM Stats Score
48.3
#32
15.5
#265
Reasoning
47.2
#26
16.2
#252
Cost, coverage & limits
Benchmark wins
3 of 3
0 of 3
Input price
$0.15 / M
— / M
Output price
$0.50 / M
— / M
Context window
1,048,576
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
GLM-5.3-Flash
LFM3-VL-2B
Vision
31.3#37
11.4#133
Multimodal
30.2#40
12.6#124
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

15 reported for GLM-5.3-Flash · 41 for LFM3-VL-2B

3 shared

GLM-5.3-Flash outperforms in 3 benchmarks (CharXiv-R, MMVU, MVBench), while LFM3-VL-2B is better at 0 benchmarks.

GLM-5.3-Flash significantly outperforms across most benchmarks.

Wed Nov 04 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

318.1B diff

GLM-5.3-Flash has 318.1B more parameters than LFM3-VL-2B, making it 16566.7% larger.

Zhipu AI
GLM-5.3-Flash
320.0Bparameters
Liquid AI
LFM3-VL-2B
1.9Bparameters
320.0B
GLM-5.3-Flash
1.9B
LFM3-VL-2B

Context Window

Maximum input and output token capacity

Only GLM-5.3-Flash specifies input context (1,048,576 tokens). Only GLM-5.3-Flash specifies output context (1,048,576 tokens).

Zhipu AI
GLM-5.3-Flash
Input1,048,576 tokens
Output1,048,576 tokens
Liquid AI
LFM3-VL-2B
Input- tokens
Output- tokens
Wed Nov 04 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both GLM-5.3-Flash and LFM3-VL-2B support multimodal inputs.

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

GLM-5.3-Flash

Text
Images
Audio
Video

LFM3-VL-2B

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5.3-Flash is licensed under MIT, 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.

GLM-5.3-Flash

MIT

Open weights

LFM3-VL-2B

LFM Open License v1.0

Open weights

Release Timeline

When each model was launched

GLM-5.3-Flash was released on 2026-08-26, while LFM3-VL-2B was released on 2026-10-27.

LFM3-VL-2B is 2 months newer than GLM-5.3-Flash.

GLM-5.3-Flash

Aug 26, 2026

2 months ago

LFM3-VL-2B

Oct 27, 2026

1 weeks ago

2mo 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 GLM-5.3-Flash and LFM3-VL-2B side-by-side, then vote on the output you prefer.

GLM-5.3-Flash
✓ Preferred
LFM3-VL-2B
Open in Playground

FAQ

Common questions about GLM-5.3-Flash vs LFM3-VL-2B.

Which is better, GLM-5.3-Flash or LFM3-VL-2B?

GLM-5.3-Flash leads the LLM Stats Score 48.3 to 15.5. GLM-5.3-Flash is made by Zhipu AI 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 GLM-5.3-Flash compare to LFM3-VL-2B in benchmarks?

GLM-5.3-Flash scores CharXiv-R: 89.4%, Terminal-Bench 2.1: 84.3%, MMVU: 80.5%, Toolathlon: 78.4%, Chartography: 78.0%. 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 GLM-5.3-Flash and LFM3-VL-2B?

GLM-5.3-Flash supports 1.0M 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 GLM-5.3-Flash and LFM3-VL-2B?

Key differences include LLM Stats Score (48.3 vs 15.5), licensing (MIT vs LFM Open License v1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5.3-Flash and LFM3-VL-2B?

GLM-5.3-Flash is developed by Zhipu AI and LFM3-VL-2B is developed by Liquid AI.

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