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DeepSeek-V4-Flash-0731 vs Phi-3.5-MoE-instruct

DeepSeek-V4-Flash-0731 leads the LLM Stats Score 44.7 to 1.9.

DeepSeek · Microsoft · Updated for 2026

Which is better?

DeepSeek-V4-Flash-0731 leads the overall LLM Stats Score 44.7 to 1.9, ranking #36 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V4-Flash-0731

  • overall performance matters — it scores 44.7 and ranks #36 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Jul 2026

Choose Phi-3.5-MoE-instruct

  • you are already invested in the Microsoft ecosystem

At a glance

The differences that matter most.

DeepSeek-V4-Flash-0731
DeepSeek
Phi-3.5-MoE-instruct
Microsoft
Core performance indexes
LLM Stats Score
44.7
#36
1.9
#318
Reasoning
42.3
#46
1.4
#311
Coding
33.0
#37
-3.8
#254
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.06 / M
— / M
Output price
$0.18 / M
— / M
Context window
1,048,576
—

Individual benchmarks

9 reported for DeepSeek-V4-Flash-0731 · 31 for Phi-3.5-MoE-instruct

No common benchmarks found

DeepSeek-V4-Flash-0731 and Phi-3.5-MoE-instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

244.0B diff

DeepSeek-V4-Flash-0731 has 244.0B more parameters than Phi-3.5-MoE-instruct, making it 406.7% larger.

DeepSeek
DeepSeek-V4-Flash-0731
304.0Bparameters
Microsoft
Phi-3.5-MoE-instruct
60.0Bparameters
304.0B
DeepSeek-V4-Flash-0731
60.0B
Phi-3.5-MoE-instruct

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Flash-0731 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Flash-0731 specifies output context (1,048,576 tokens).

DeepSeek
DeepSeek-V4-Flash-0731
Input1,048,576 tokens
Output1,048,576 tokens
Microsoft
Phi-3.5-MoE-instruct
Input- tokens
Output- tokens
Sun Sep 20 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under MIT.

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

DeepSeek-V4-Flash-0731

MIT

Open weights

Phi-3.5-MoE-instruct

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Flash-0731 was released on 2026-07-31, while Phi-3.5-MoE-instruct was released on 2024-08-23.

DeepSeek-V4-Flash-0731 is 24 months newer than Phi-3.5-MoE-instruct.

DeepSeek-V4-Flash-0731

Jul 31, 2026

1 months ago

1.9yr newer
Phi-3.5-MoE-instruct

Aug 23, 2024

2.1 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-V4-Flash-0731 and Phi-3.5-MoE-instruct side-by-side, then vote on the output you prefer.

DeepSeek-V4-Flash-0731
✓ Preferred
Phi-3.5-MoE-instruct
Open in Playground

FAQ

Common questions about DeepSeek-V4-Flash-0731 vs Phi-3.5-MoE-instruct.

Which is better, DeepSeek-V4-Flash-0731 or Phi-3.5-MoE-instruct?

DeepSeek-V4-Flash-0731 leads the LLM Stats Score 44.7 to 1.9. DeepSeek-V4-Flash-0731 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-V4-Flash-0731 compare to Phi-3.5-MoE-instruct in benchmarks?

DeepSeek-V4-Flash-0731 scores Terminal-Bench 2.1: 82.7%, CyberGym: 76.7%, Toolathlon: 70.3%, DSBench-FullStack: 68.7%, DSBench-Hard: 59.6%. 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 context window sizes for DeepSeek-V4-Flash-0731 and Phi-3.5-MoE-instruct?

DeepSeek-V4-Flash-0731 supports 1.0M tokens and Phi-3.5-MoE-instruct 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 DeepSeek-V4-Flash-0731 and Phi-3.5-MoE-instruct?

Key differences include LLM Stats Score (44.7 vs 1.9). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Flash-0731 and Phi-3.5-MoE-instruct?

DeepSeek-V4-Flash-0731 is developed by DeepSeek and Phi-3.5-MoE-instruct is developed by Microsoft.

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