Grok-1.5 vs Phi-3.5-mini-instruct Comparison

Comparing Grok-1.5 and Phi-3.5-mini-instruct across benchmarks, pricing, and capabilities.

Performance Benchmarks

Comparative analysis across standard metrics

6 benchmarks

Grok-1.5 outperforms in 6 benchmarks (GPQA, GSM8k, HumanEval, MATH, MMLU, MMLU-Pro), while Phi-3.5-mini-instruct is better at 0 benchmarks.

Grok-1.5 significantly outperforms across most benchmarks.

Fri Mar 20 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Fri Mar 20 2026 • llm-stats.com
xAI
Grok-1.5
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Microsoft
Phi-3.5-mini-instruct
Input tokens$0.10
Output tokens$0.10
Best providerAzure
Notice missing or incorrect data?Start an Issue

Context Window

Maximum input and output token capacity

Only Phi-3.5-mini-instruct specifies input context (128,000 tokens). Only Phi-3.5-mini-instruct specifies output context (128,000 tokens).

xAI
Grok-1.5
Input- tokens
Output- tokens
Microsoft
Phi-3.5-mini-instruct
Input128,000 tokens
Output128,000 tokens
Fri Mar 20 2026 • llm-stats.com

License

Usage and distribution terms

Grok-1.5 is licensed under a proprietary license, while Phi-3.5-mini-instruct uses MIT.

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

Grok-1.5

Proprietary

Closed source

Phi-3.5-mini-instruct

MIT

Open weights

Release Timeline

When each model was launched

Grok-1.5 was released on 2024-03-28, while Phi-3.5-mini-instruct was released on 2024-08-23.

Phi-3.5-mini-instruct is 5 months newer than Grok-1.5.

Grok-1.5

Mar 28, 2024

2.0 years ago

Phi-3.5-mini-instruct

Aug 23, 2024

1.6 years ago

4mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

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Key Takeaways

Higher GPQA score (35.9% vs 30.4%)
Higher GSM8k score (90.0% vs 86.2%)
Higher HumanEval score (74.1% vs 62.8%)
Higher MATH score (50.6% vs 48.5%)
Higher MMLU score (81.3% vs 69.0%)
Higher MMLU-Pro score (51.0% vs 47.4%)
Larger context window (128,000 tokens)
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
xAI
Grok-1.5
Microsoft
Phi-3.5-mini-instruct