Model Comparison

Jamba 1.5 Mini vs Phi 4 Reasoning

Phi 4 Reasoning significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

Jamba 1.5 Mini outperforms in 0 benchmarks, while Phi 4 Reasoning is better at 3 benchmarks (Arena Hard, GPQA, MMLU-Pro).

Phi 4 Reasoning significantly outperforms across most benchmarks.

Fri May 08 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

38.0B diff

Jamba 1.5 Mini has 38.0B more parameters than Phi 4 Reasoning, making it 271.4% larger.

AI21 Labs
Jamba 1.5 Mini
52.0Bparameters
Microsoft
Phi 4 Reasoning
14.0Bparameters
52.0B
Jamba 1.5 Mini
14.0B
Phi 4 Reasoning

Context Window

Maximum input and output token capacity

Only Jamba 1.5 Mini specifies input context (256,144 tokens). Only Jamba 1.5 Mini specifies output context (256,144 tokens).

AI21 Labs
Jamba 1.5 Mini
Input256,144 tokens
Output256,144 tokens
Microsoft
Phi 4 Reasoning
Input- tokens
Output- tokens
Fri May 08 2026 • llm-stats.com

License

Usage and distribution terms

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

License differences may affect how you can use these models in commercial or open-source projects.

Jamba 1.5 Mini

Jamba Open Model License

Open weights

Phi 4 Reasoning

MIT

Open weights

Release Timeline

When each model was launched

Jamba 1.5 Mini was released on 2024-08-22, while Phi 4 Reasoning was released on 2025-04-30.

Phi 4 Reasoning is 8 months newer than Jamba 1.5 Mini.

Jamba 1.5 Mini

Aug 22, 2024

1.7 years ago

Phi 4 Reasoning

Apr 30, 2025

1.0 years ago

8mo newer

Knowledge Cutoff

When training data ends

Jamba 1.5 Mini has a knowledge cutoff of 2024-03-05, while Phi 4 Reasoning has a cutoff of 2025-03-01.

Phi 4 Reasoning has more recent training data (up to 2025-03-01), making it potentially better informed about events through that date compared to Jamba 1.5 Mini (2024-03-05).

Jamba 1.5 Mini

Mar 2024

Phi 4 Reasoning

Mar 2025

1 yr newer

Outputs Comparison

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Key Takeaways

AI21 Labs
Larger context window (256,144 tokens)
Microsoft
Higher Arena Hard score (73.3% vs 46.1%)
Higher GPQA score (65.8% vs 32.3%)
Higher MMLU-Pro score (74.3% vs 42.5%)

Detailed Comparison

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

FAQ

Common questions about Jamba 1.5 Mini vs Phi 4 Reasoning.

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

Phi 4 Reasoning significantly outperforms across most benchmarks. Jamba 1.5 Mini is made by AI21 Labs and Phi 4 Reasoning 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 Mini compare to Phi 4 Reasoning in benchmarks?

Jamba 1.5 Mini scores ARC-C: 85.7%, GSM8k: 75.8%, MMLU: 69.7%, TruthfulQA: 54.1%, Arena Hard: 46.1%. Phi 4 Reasoning scores FlenQA: 97.7%, HumanEval+: 92.9%, IFEval: 83.4%, OmniMath: 76.6%, AIME 2024: 75.3%.

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

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

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 Mini and Phi 4 Reasoning?

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