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Jamba 1.5 Large vs LFM3-1.7B

LFM3-1.7B leads the LLM Stats Score 25.0 to 0.4.

AI21 Labs · Liquid AI · Updated for 2026

Which is better?

LFM3-1.7B leads the overall LLM Stats Score 25.0 to 0.4, ranking #192 overall.

In the 1 individual benchmarks reported for both models, LFM3-1.7B wins 1; 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 Jamba 1.5 Large

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

Choose LFM3-1.7B

  • overall performance matters — it scores 25.0 and ranks #192 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

Jamba 1.5 Large
AI21 Labs
LFM3-1.7B
Liquid AI
Core performance indexes
LLM Stats Score
0.4
#363
25.0
#192
Reasoning
0.5
#355
20.8
#216
Cost, coverage & limits
Benchmark wins
0 of 1
1 of 1
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
LFM3-1.7B
Math
4.3#304
7.6#285
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

8 reported for Jamba 1.5 Large · 20 for LFM3-1.7B

1 shared

Jamba 1.5 Large outperforms in 0 benchmarks, while LFM3-1.7B is better at 1 benchmark (GPQA).

LFM3-1.7B significantly outperforms across most benchmarks.

Mon Nov 02 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

396.3B diff

Jamba 1.5 Large has 396.3B more parameters than LFM3-1.7B, making it 22905.8% larger.

AI21 Labs
Jamba 1.5 Large
398.0Bparameters
Liquid AI
LFM3-1.7B
1.7Bparameters
398.0B
Jamba 1.5 Large
1.7B
LFM3-1.7B

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
LFM3-1.7B
Input- tokens
Output- tokens
Mon Nov 02 2026 • llm-stats.com

License

Usage and distribution terms

Jamba 1.5 Large is licensed under Jamba Open Model License, while LFM3-1.7B 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

LFM3-1.7B

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 LFM3-1.7B was released on 2026-10-27.

LFM3-1.7B is 27 months newer than Jamba 1.5 Large.

Jamba 1.5 Large

Aug 22, 2024

2.2 years ago

LFM3-1.7B

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 LFM3-1.7B'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 LFM3-1.7B's cutoff date.

Jamba 1.5 Large

Mar 2024

LFM3-1.7B

—

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Jamba 1.5 Large and LFM3-1.7B side-by-side, then vote on the output you prefer.

Jamba 1.5 Large
✓ Preferred
LFM3-1.7B
Open in Playground

FAQ

Common questions about Jamba 1.5 Large vs LFM3-1.7B.

Which is better, Jamba 1.5 Large or LFM3-1.7B?

LFM3-1.7B leads the LLM Stats Score 25.0 to 0.4. Jamba 1.5 Large is made by AI21 Labs and LFM3-1.7B 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 LFM3-1.7B in benchmarks?

Jamba 1.5 Large scores ARC-C: 93.0%, GSM8k: 87.0%, MMLU: 81.2%, Arena Hard: 65.4%, TruthfulQA: 58.3%. LFM3-1.7B scores IFEval: 96.7%, Multi-IF: 89.1%, LiveCodeBench v6: 73.5%, IFBench: 73.0%, BFCL-V4: 71.4%.

What are the context window sizes for Jamba 1.5 Large and LFM3-1.7B?

Jamba 1.5 Large supports 256K tokens and LFM3-1.7B 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 LFM3-1.7B?

Key differences include LLM Stats Score (0.4 vs 25.0), 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 LFM3-1.7B?

Jamba 1.5 Large is developed by AI21 Labs and LFM3-1.7B is developed by Liquid AI.

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