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Kimi K3.1 Pro vs Phi-3.5-MoE-instruct

Kimi K3.1 Pro leads the LLM Stats Score 55.5 to 1.4.

Moonshot AI · Microsoft · Updated for 2026

Which is better?

Kimi K3.1 Pro leads the overall LLM Stats Score 55.5 to 1.4, ranking #5 overall.

In the 1 individual benchmarks reported for both models, Kimi K3.1 Pro 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 Kimi K3.1 Pro

  • overall performance matters — it scores 55.5 and ranks #5 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Oct 2026

Choose Phi-3.5-MoE-instruct

  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Core performance indexes
55.5
#5
1.4
#354
54.3
#6
1.0
#347
42.7
#9
-3.9
#288
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$2.00 / M
— / M
Output price
$10.00 / M
— / M
Context window
1,048,576
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Kimi K3.1 Pro
Phi-3.5-MoE-instruct
38.6#26
4.3#304
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

30 reported for Kimi K3.1 Pro · 31 for Phi-3.5-MoE-instruct

1 shared

Kimi K3.1 Pro outperforms in 1 benchmarks (GPQA), while Phi-3.5-MoE-instruct is better at 0 benchmarks.

Kimi K3.1 Pro significantly outperforms across most benchmarks.

Fri Oct 30 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only Kimi K3.1 Pro specifies input context (1,048,576 tokens). Only Kimi K3.1 Pro specifies output context (1,048,576 tokens).

Moonshot AI
Kimi K3.1 Pro
Input1,048,576 tokens
Output1,048,576 tokens
Microsoft
Phi-3.5-MoE-instruct
Input- tokens
Output- tokens
Fri Oct 30 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Kimi K3.1 Pro supports multimodal inputs, whereas Phi-3.5-MoE-instruct does not.

Kimi K3.1 Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.

Kimi K3.1 Pro

Text
Images
Audio
Video

Phi-3.5-MoE-instruct

Text
Images
Audio
Video

Release Timeline

When each model was launched

Kimi K3.1 Pro was released on 2026-10-23, while Phi-3.5-MoE-instruct was released on 2024-08-23.

Kimi K3.1 Pro is 26 months newer than Phi-3.5-MoE-instruct.

Kimi K3.1 Pro

Oct 23, 2026

2 days ago

2.2yr newer
Phi-3.5-MoE-instruct

Aug 23, 2024

2.2 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?

Judge for yourself.

Run your own prompts against Kimi K3.1 Pro and Phi-3.5-MoE-instruct side-by-side, then vote on the output you prefer.

Kimi K3.1 Pro
✓ Preferred
Phi-3.5-MoE-instruct
Open in Playground

FAQ

Common questions about Kimi K3.1 Pro vs Phi-3.5-MoE-instruct.

Which is better, Kimi K3.1 Pro or Phi-3.5-MoE-instruct?

Kimi K3.1 Pro leads the LLM Stats Score 55.5 to 1.4. Kimi K3.1 Pro is made by Moonshot AI 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 Kimi K3.1 Pro compare to Phi-3.5-MoE-instruct in benchmarks?

Kimi K3.1 Pro scores BabyVision: 95.4%, GPQA: 94.2%, BenchCAD (with Python tool): 92.7%, BrowseComp: 92.1%, Chartography: 90.2%. 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 Kimi K3.1 Pro and Phi-3.5-MoE-instruct?

Kimi K3.1 Pro 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 Kimi K3.1 Pro and Phi-3.5-MoE-instruct?

Key differences include LLM Stats Score (55.5 vs 1.4), multimodal support (yes vs no), licensing (Unknown vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Kimi K3.1 Pro and Phi-3.5-MoE-instruct?

Kimi K3.1 Pro is developed by Moonshot AI and Phi-3.5-MoE-instruct is developed by Microsoft.