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Jamba 1.5 Large vs LFM3-VL-2B

LFM3-VL-2B leads the LLM Stats Score 15.5 to 0.4.

AI21 Labs · Liquid AI · Updated for 2026

Which is better?

LFM3-VL-2B leads the overall LLM Stats Score 15.5 to 0.4, ranking #265 overall.

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

Choose Jamba 1.5 Large

  • you want predictable pricing at $2.00/M input and $8.00/M output

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 want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

Core performance indexes
0.4
#363
15.5
#265
0.5
#355
16.2
#252
Cost, coverage & limits
Benchmark wins
—
—
Input price
$2.00 / M
— / M
Output price
$8.00 / M
— / M
Context window
256,000
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Jamba 1.5 Large
LFM3-VL-2B
4.3#304
19.0#187
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

8 reported for Jamba 1.5 Large · 41 for LFM3-VL-2B

No common benchmarks found

Jamba 1.5 Large 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

396.1B diff

Jamba 1.5 Large has 396.1B more parameters than LFM3-VL-2B, making it 20629.2% larger.

AI21 Labs
Jamba 1.5 Large
398.0Bparameters
Liquid AI
LFM3-VL-2B
1.9Bparameters
398.0B
Jamba 1.5 Large
1.9B
LFM3-VL-2B

Context Window

Maximum input and output token capacity

Only Jamba 1.5 Large specifies input context (256,000 tokens). Only Jamba 1.5 Large specifies output context (256,000 tokens).

AI21 Labs
Jamba 1.5 Large
Input256,000 tokens
Output256,000 tokens
Liquid AI
LFM3-VL-2B
Input- tokens
Output- tokens
Mon Nov 02 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

LFM3-VL-2B supports multimodal inputs, whereas Jamba 1.5 Large does not.

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

Jamba 1.5 Large

Text
Images
Audio
Video

LFM3-VL-2B

Text
Images
Audio
Video

License

Usage and distribution terms

Jamba 1.5 Large is licensed under Jamba Open Model License, 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.

Jamba 1.5 Large

Jamba Open Model License

Open weights

LFM3-VL-2B

LFM Open License v1.0

Open weights

Release Timeline

When each model was launched

Jamba 1.5 Large was released on 2024-08-22, while LFM3-VL-2B was released on 2026-10-27.

LFM3-VL-2B is 27 months newer than Jamba 1.5 Large.

Jamba 1.5 Large

Aug 22, 2024

2.2 years ago

LFM3-VL-2B

Oct 27, 2026

6 days ago

2.2yr newer

Knowledge Cutoff

When training data ends

Jamba 1.5 Large has a documented knowledge cutoff of 2024-03-05, while LFM3-VL-2B's cutoff date is not specified.

We can confirm Jamba 1.5 Large's training data extends to 2024-03-05, but cannot make a direct comparison without LFM3-VL-2B's cutoff date.

Jamba 1.5 Large

Mar 2024

LFM3-VL-2B

—

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Jamba 1.5 Large and LFM3-VL-2B side-by-side, then vote on the output you prefer.

Jamba 1.5 Large
✓ Preferred
LFM3-VL-2B
Open in Playground

FAQ

Common questions about Jamba 1.5 Large vs LFM3-VL-2B.

Which is better, Jamba 1.5 Large or LFM3-VL-2B?

LFM3-VL-2B leads the LLM Stats Score 15.5 to 0.4. Jamba 1.5 Large is made by AI21 Labs 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 Jamba 1.5 Large compare to LFM3-VL-2B in benchmarks?

Jamba 1.5 Large scores ARC-C: 93.0%, GSM8k: 87.0%, MMLU: 81.2%, Arena Hard: 65.4%, TruthfulQA: 58.3%. 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 Jamba 1.5 Large and LFM3-VL-2B?

Jamba 1.5 Large supports 256K 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 Jamba 1.5 Large and LFM3-VL-2B?

Key differences include LLM Stats Score (0.4 vs 15.5), multimodal support (no vs yes), licensing (Jamba Open Model License vs LFM Open License v1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Jamba 1.5 Large and LFM3-VL-2B?

Jamba 1.5 Large is developed by AI21 Labs and LFM3-VL-2B is developed by Liquid AI.