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DeepSeek R1 Distill Qwen 1.5B vs Phi-3.5-MoE-instruct

DeepSeek R1 Distill Qwen 1.5B and Phi-3.5-MoE-instruct are closely matched at -2.7 and 2.0 on the LLM Stats Score.

DeepSeek · Microsoft · Updated for 2026

Which is better?

DeepSeek R1 Distill Qwen 1.5B and Phi-3.5-MoE-instruct are closely matched on the overall LLM Stats Score at -2.7 and 2.0.

In the 1 individual benchmarks reported for both models, Phi-3.5-MoE-instruct 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 DeepSeek R1 Distill Qwen 1.5B

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

Choose Phi-3.5-MoE-instruct

  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results

At a glance

The differences that matter most.

Core performance indexes
-2.7
#325
2.0
#301
-2.4
#315
1.5
#295
-4.5
#245
-3.8
#240
Cost, coverage & limits
Benchmark wins
0 of 1
1 of 1
Input price
— / M
— / M
Output price
— / M
— / M
Context window

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek R1 Distill Qwen 1.5B
Phi-3.5-MoE-instruct
5.7#260
4.7#272
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

4 reported for DeepSeek R1 Distill Qwen 1.5B · 31 for Phi-3.5-MoE-instruct

1 shared

DeepSeek R1 Distill Qwen 1.5B outperforms in 0 benchmarks, while Phi-3.5-MoE-instruct is better at 1 benchmark (GPQA).

Phi-3.5-MoE-instruct significantly outperforms across most benchmarks.

Mon Aug 31 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

58.2B diff

Phi-3.5-MoE-instruct has 58.2B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 3270.8% larger.

DeepSeek
DeepSeek R1 Distill Qwen 1.5B
1.8Bparameters
Microsoft
Phi-3.5-MoE-instruct
60.0Bparameters
1.8B
DeepSeek R1 Distill Qwen 1.5B
60.0B
Phi-3.5-MoE-instruct

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

DeepSeek R1 Distill Qwen 1.5B

MIT

Open weights

Phi-3.5-MoE-instruct

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 1.5B was released on 2025-01-20, while Phi-3.5-MoE-instruct was released on 2024-08-23.

DeepSeek R1 Distill Qwen 1.5B is 5 months newer than Phi-3.5-MoE-instruct.

DeepSeek R1 Distill Qwen 1.5B

Jan 20, 2025

1.6 years ago

5mo newer
Phi-3.5-MoE-instruct

Aug 23, 2024

2.0 years ago

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

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against DeepSeek R1 Distill Qwen 1.5B and Phi-3.5-MoE-instruct side-by-side, then vote on the output you prefer.

DeepSeek R1 Distill Qwen 1.5B
✓ Preferred
Phi-3.5-MoE-instruct
Open in Playground

FAQ

Common questions about DeepSeek R1 Distill Qwen 1.5B vs Phi-3.5-MoE-instruct.

Which is better, DeepSeek R1 Distill Qwen 1.5B or Phi-3.5-MoE-instruct?

DeepSeek R1 Distill Qwen 1.5B and Phi-3.5-MoE-instruct are closely matched on the LLM Stats Score at -2.7 and 2.0. DeepSeek R1 Distill Qwen 1.5B is made by DeepSeek and Phi-3.5-MoE-instruct is made by Microsoft. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek R1 Distill Qwen 1.5B compare to Phi-3.5-MoE-instruct in benchmarks?

DeepSeek R1 Distill Qwen 1.5B scores MATH-500: 83.9%, AIME 2024: 52.7%, GPQA: 33.8%, LiveCodeBench: 16.9%. Phi-3.5-MoE-instruct scores ARC-C: 91.0%, OpenBookQA: 89.6%, GSM8k: 88.7%, PIQA: 88.6%, RULER: 87.1%.

What are the main differences between DeepSeek R1 Distill Qwen 1.5B and Phi-3.5-MoE-instruct?

Key differences include LLM Stats Score (-2.7 vs 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Distill Qwen 1.5B and Phi-3.5-MoE-instruct?

DeepSeek R1 Distill Qwen 1.5B is developed by DeepSeek and Phi-3.5-MoE-instruct is developed by Microsoft.