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Jamba 1.5 Large vs Phi 4 Mini

Jamba 1.5 Large leads the LLM Stats Score 0.9 to -4.1.

AI21 Labs · Microsoft · Updated for 2026

Which is better?

Jamba 1.5 Large leads the overall LLM Stats Score 0.9 to -4.1, ranking #321 overall.

In the 7 individual benchmarks reported for both models, Jamba 1.5 Large wins 5; 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

  • overall performance matters — it scores 0.9 and ranks #321 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 5 of 7 exact shared results

Choose Phi 4 Mini

  • you want the most recent training data — it shipped Feb 2025

At a glance

The differences that matter most.

Jamba 1.5 Large
AI21 Labs
Phi 4 Mini
Microsoft
Core performance indexes
LLM Stats Score
0.9
#321
-4.1
#346
Reasoning
1.0
#313
-4.2
#339
Cost, coverage & limits
Benchmark wins
5 of 7
2 of 7
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

3 shared
Index
Jamba 1.5 Large
Phi 4 Mini
Math
4.4#282
2.3#293
Finance
5.3#169
1.1#191
Legal
5.3#155
1.1#178
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

8 reported for Jamba 1.5 Large · 17 for Phi 4 Mini

7 shared

Jamba 1.5 Large outperforms in 5 benchmarks (ARC-C, Arena Hard, GPQA, MMLU, MMLU-Pro), while Phi 4 Mini is better at 2 benchmarks (GSM8k, TruthfulQA).

Jamba 1.5 Large shows notably better performance in the majority of benchmarks.

Sat Sep 12 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

394.2B diff

Jamba 1.5 Large has 394.2B more parameters than Phi 4 Mini, making it 10264.6% larger.

AI21 Labs
Jamba 1.5 Large
398.0Bparameters
Microsoft
Phi 4 Mini
3.8Bparameters
398.0B
Jamba 1.5 Large
3.8B
Phi 4 Mini

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
Microsoft
Phi 4 Mini
Input- tokens
Output- tokens
Sat Sep 12 2026 • llm-stats.com

License

Usage and distribution terms

Jamba 1.5 Large is licensed under Jamba Open Model License, while Phi 4 Mini uses MIT.

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

Phi 4 Mini

MIT

Open weights

Release Timeline

When each model was launched

Jamba 1.5 Large was released on 2024-08-22, while Phi 4 Mini was released on 2025-02-01.

Phi 4 Mini is 5 months newer than Jamba 1.5 Large.

Jamba 1.5 Large

Aug 22, 2024

2.1 years ago

Phi 4 Mini

Feb 1, 2025

1.6 years ago

5mo newer

Knowledge Cutoff

When training data ends

Jamba 1.5 Large has a knowledge cutoff of 2024-03-05, while Phi 4 Mini has a cutoff of 2024-06-01.

Phi 4 Mini has more recent training data (up to 2024-06-01), making it potentially better informed about events through that date compared to Jamba 1.5 Large (2024-03-05).

Jamba 1.5 Large

Mar 2024

Phi 4 Mini

Jun 2024

3 mo newer

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Jamba 1.5 Large and Phi 4 Mini side-by-side, then vote on the output you prefer.

Jamba 1.5 Large
✓ Preferred
Phi 4 Mini
Open in Playground

FAQ

Common questions about Jamba 1.5 Large vs Phi 4 Mini.

Which is better, Jamba 1.5 Large or Phi 4 Mini?

Jamba 1.5 Large leads the LLM Stats Score 0.9 to -4.1. Jamba 1.5 Large is made by AI21 Labs and Phi 4 Mini is made by Microsoft. 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 Phi 4 Mini in benchmarks?

Jamba 1.5 Large scores ARC-C: 93.0%, GSM8k: 87.0%, MMLU: 81.2%, Arena Hard: 65.4%, TruthfulQA: 58.3%. Phi 4 Mini scores GSM8k: 88.6%, ARC-C: 83.7%, BoolQ: 81.2%, OpenBookQA: 79.2%, PIQA: 77.6%.

What are the context window sizes for Jamba 1.5 Large and Phi 4 Mini?

Jamba 1.5 Large supports 256K tokens and Phi 4 Mini 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 Phi 4 Mini?

Key differences include LLM Stats Score (0.9 vs -4.1), licensing (Jamba Open Model License vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Jamba 1.5 Large and Phi 4 Mini?

Jamba 1.5 Large is developed by AI21 Labs and Phi 4 Mini is developed by Microsoft.

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