Model Comparison

Jamba 1.5 Large vs Phi 4 MiniWhich is better in 2026?

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

Verdict: Jamba 1.5 Large vs Phi 4 Mini — which is better?

Jamba 1.5 Large (by AI21 Labs) and Phi 4 Mini (by Microsoft) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

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.

Choose Jamba 1.5 Large if…

  • you want the strongest raw capability — it leads on 5 of 7 shared benchmarks

Choose Phi 4 Mini if…

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

Performance Benchmarks

Comparative analysis across standard metrics

7 benchmarks

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.

Tue Jul 28 2026 • llm-stats.com

Arena Performance

Human preference votes

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
Tue Jul 28 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

1.9 years ago

Phi 4 Mini

Feb 1, 2025

1.5 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

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Key Takeaways

AI21 Labs
Larger context window (256,000 tokens)
Higher ARC-C score (93.0% vs 83.7%)
Higher Arena Hard score (65.4% vs 32.8%)
Higher GPQA score (36.9% vs 25.2%)
Higher MMLU score (81.2% vs 67.3%)
Higher MMLU-Pro score (53.5% vs 52.8%)
Microsoft
Higher GSM8k score (88.6% vs 87.0%)
Higher TruthfulQA score (66.4% vs 58.3%)

Detailed Comparison

Interactive Arena

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
AI Model Comparison Table
Feature
AI21 Labs
Jamba 1.5 Large
Microsoft
Phi 4 Mini

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 shows notably better performance in the majority of benchmarks. 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 benchmark scores, pricing, and capabilities 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 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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