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Kimi K2-Thinking-0905 vs QvQ-72B-Preview

Kimi K2-Thinking-0905 leads the LLM Stats Score 36.0 to 7.9.

Moonshot AI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Kimi K2-Thinking-0905 leads the overall LLM Stats Score 36.0 to 7.9, ranking #81 overall.

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

Choose Kimi K2-Thinking-0905

  • overall performance matters — it scores 36.0 and ranks #81 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2025

Choose QvQ-72B-Preview

  • you are already invested in the Alibaba Cloud / Qwen Team ecosystem

At a glance

The differences that matter most.

Core performance indexes
36.0
#81
7.9
#282
36.2
#74
8.2
#275
Cost, coverage & limits
Benchmark wins
Input price
$0.47 / M
— / M
Output price
$2.00 / M
— / M
Context window
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Kimi K2-Thinking-0905
QvQ-72B-Preview
38.0#27
9.6#253
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

21 reported for Kimi K2-Thinking-0905 · 4 for QvQ-72B-Preview

No common benchmarks found

Kimi K2-Thinking-0905 and QvQ-72B-Previewdon'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

926.6B diff

Kimi K2-Thinking-0905 has 926.6B more parameters than QvQ-72B-Preview, making it 1262.4% larger.

Moonshot AI
Kimi K2-Thinking-0905
1.0Tparameters
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
73.4Bparameters
1000.0B
Kimi K2-Thinking-0905
73.4B
QvQ-72B-Preview

Context Window

Maximum input and output token capacity

Only Kimi K2-Thinking-0905 specifies input context (262,144 tokens). Only Kimi K2-Thinking-0905 specifies output context (262,144 tokens).

Moonshot AI
Kimi K2-Thinking-0905
Input262,144 tokens
Output262,144 tokens
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
Input- tokens
Output- tokens
Mon Sep 21 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

QvQ-72B-Preview supports multimodal inputs, whereas Kimi K2-Thinking-0905 does not.

QvQ-72B-Preview can handle both text and other forms of data like images, making it suitable for multimodal applications.

Kimi K2-Thinking-0905

Text
Images
Audio
Video

QvQ-72B-Preview

Text
Images
Audio
Video

License

Usage and distribution terms

Kimi K2-Thinking-0905 is licensed under MIT, while QvQ-72B-Preview uses Qwen.

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

Kimi K2-Thinking-0905

MIT

Open weights

QvQ-72B-Preview

Qwen

Open weights

Release Timeline

When each model was launched

Kimi K2-Thinking-0905 was released on 2025-09-05, while QvQ-72B-Preview was released on 2024-12-25.

Kimi K2-Thinking-0905 is 8 months newer than QvQ-72B-Preview.

Kimi K2-Thinking-0905

Sep 5, 2025

1.0 years ago

8mo newer
QvQ-72B-Preview

Dec 25, 2024

1.7 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 Kimi K2-Thinking-0905 and QvQ-72B-Preview side-by-side, then vote on the output you prefer.

Kimi K2-Thinking-0905
✓ Preferred
QvQ-72B-Preview
Open in Playground

FAQ

Common questions about Kimi K2-Thinking-0905 vs QvQ-72B-Preview.

Which is better, Kimi K2-Thinking-0905 or QvQ-72B-Preview?

Kimi K2-Thinking-0905 leads the LLM Stats Score 36.0 to 7.9. Kimi K2-Thinking-0905 is made by Moonshot AI and QvQ-72B-Preview is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Kimi K2-Thinking-0905 compare to QvQ-72B-Preview in benchmarks?

Kimi K2-Thinking-0905 scores AIME 2025: 100.0%, HMMT 2025: 97.5%, MMLU-Redux: 94.4%, FRAMES: 87.0%, MMLU-Pro: 84.6%. QvQ-72B-Preview scores MathVista: 71.4%, MMMU: 70.3%, MathVision: 35.9%, OlympiadBench: 20.4%.

What are the context window sizes for Kimi K2-Thinking-0905 and QvQ-72B-Preview?

Kimi K2-Thinking-0905 supports 262K tokens and QvQ-72B-Preview 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 K2-Thinking-0905 and QvQ-72B-Preview?

Key differences include LLM Stats Score (36.0 vs 7.9), multimodal support (no vs yes), licensing (MIT vs Qwen). See the full comparison above for benchmark-by-benchmark results.

Who makes Kimi K2-Thinking-0905 and QvQ-72B-Preview?

Kimi K2-Thinking-0905 is developed by Moonshot AI and QvQ-72B-Preview is developed by Alibaba Cloud / Qwen Team.