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GLM-5 vs LFM3-VL-2B

GLM-5 leads the LLM Stats Score 36.6 to 15.5.

Zhipu AI · Liquid AI · Updated for 2026

Which is better?

GLM-5 leads the overall LLM Stats Score 36.6 to 15.5, ranking #95 overall.

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

Choose GLM-5

  • overall performance matters — it scores 36.6 and ranks #95 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes

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
Zhipu AI
LFM3-VL-2B
Liquid AI
Core performance indexes
LLM Stats Score
36.6
#95
15.5
#265
Reasoning
36.9
#93
16.2
#252
Cost, coverage & limits
Benchmark wins
—
—
Input price
$1.00 / M
— / M
Output price
$3.20 / M
— / M
Context window
200,000
—

Individual benchmarks

5 reported for GLM-5 · 41 for LFM3-VL-2B

No common benchmarks found

GLM-5 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

742.1B diff

GLM-5 has 742.1B more parameters than LFM3-VL-2B, making it 38650.0% larger.

Zhipu AI
GLM-5
744.0Bparameters
Liquid AI
LFM3-VL-2B
1.9Bparameters
744.0B
GLM-5
1.9B
LFM3-VL-2B

Context Window

Maximum input and output token capacity

Only GLM-5 specifies input context (200,000 tokens). Only GLM-5 specifies output context (128,000 tokens).

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 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 GLM-5 does not.

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

GLM-5

Text
Images
Audio
Video

LFM3-VL-2B

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5 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

MIT

Open weights

LFM3-VL-2B

LFM Open License v1.0

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while LFM3-VL-2B was released on 2026-10-27.

LFM3-VL-2B is 9 months newer than GLM-5.

GLM-5

Feb 11, 2026

8 months ago

LFM3-VL-2B

Oct 27, 2026

5 days ago

8mo 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 and LFM3-VL-2B side-by-side, then vote on the output you prefer.

GLM-5
✓ Preferred
LFM3-VL-2B
Open in Playground

FAQ

Common questions about GLM-5 vs LFM3-VL-2B.

Which is better, GLM-5 or LFM3-VL-2B?

GLM-5 leads the LLM Stats Score 36.6 to 15.5. GLM-5 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 compare to LFM3-VL-2B in benchmarks?

GLM-5 scores t2-bench: 89.7%, SWE-Bench Verified: 77.8%, BrowseComp: 75.9%, MCP Atlas: 67.8%, Terminal-Bench 2.0: 56.2%. 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 GLM-5 and LFM3-VL-2B?

GLM-5 supports 200K 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 and LFM3-VL-2B?

Key differences include LLM Stats Score (36.6 vs 15.5), multimodal support (no vs yes), licensing (MIT vs LFM Open License v1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5 and LFM3-VL-2B?

GLM-5 is developed by Zhipu AI and LFM3-VL-2B is developed by Liquid AI.

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