The AI arena is free today

Open Superagent

Kimi K2 0905 vs Ministral 3 (8B Instruct 2512)

Kimi K2 0905 leads the LLM Stats Score 21.4 to 7.4.

Moonshot AI · Mistral AI · Updated for 2026

Which is better?

Kimi K2 0905 leads the overall LLM Stats Score 21.4 to 7.4, ranking #209 overall.

In the 1 individual benchmarks reported for both models, Kimi K2 0905 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 K2 0905

  • overall performance matters — it scores 21.4 and ranks #209 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results

Choose Ministral 3 (8B Instruct 2512)

  • you want the most recent training data — it shipped Dec 2025
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Kimi K2 0905
Moonshot AI
Ministral 3 (8B Instruct 2512)
Mistral AI
Core performance indexes
LLM Stats Score
21.4
#209
7.4
#308
Reasoning
21.7
#196
9.0
#286
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$0.60 / M
— / M
Output price
$2.50 / M
— / M
Context window
262,144
—

Individual benchmarks

6 reported for Kimi K2 0905 · 4 for Ministral 3 (8B Instruct 2512)

1 shared

Kimi K2 0905 outperforms in 1 benchmarks (MATH), while Ministral 3 (8B Instruct 2512) is better at 0 benchmarks.

Kimi K2 0905 significantly outperforms across most benchmarks.

Tue Oct 20 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

992.0B diff

Kimi K2 0905 has 992.0B more parameters than Ministral 3 (8B Instruct 2512), making it 12400.0% larger.

Moonshot AI
Kimi K2 0905
1.0Tparameters
Mistral AI
Ministral 3 (8B Instruct 2512)
8.0Bparameters
1000.0B
Kimi K2 0905
8.0B
Ministral 3 (8B Instruct 2512)

Context Window

Maximum input and output token capacity

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

Moonshot AI
Kimi K2 0905
Input262,144 tokens
Output262,144 tokens
Mistral AI
Ministral 3 (8B Instruct 2512)
Input- tokens
Output- tokens
Tue Oct 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Ministral 3 (8B Instruct 2512) supports multimodal inputs, whereas Kimi K2 0905 does not.

Ministral 3 (8B Instruct 2512) can handle both text and other forms of data like images, making it suitable for multimodal applications.

Kimi K2 0905

Text
Images
Audio
Video

Ministral 3 (8B Instruct 2512)

Text
Images
Audio
Video

License

Usage and distribution terms

Kimi K2 0905 is licensed under a proprietary license, while Ministral 3 (8B Instruct 2512) uses Apache 2.0.

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

Kimi K2 0905

Proprietary

Closed source

Ministral 3 (8B Instruct 2512)

Apache 2.0

Open weights

Release Timeline

When each model was launched

Kimi K2 0905 was released on 2025-09-05, while Ministral 3 (8B Instruct 2512) was released on 2025-12-04.

Ministral 3 (8B Instruct 2512) is 3 months newer than Kimi K2 0905.

Kimi K2 0905

Sep 5, 2025

1.1 years ago

Ministral 3 (8B Instruct 2512)

Dec 4, 2025

10 months ago

3mo 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

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Kimi K2 0905 and Ministral 3 (8B Instruct 2512) side-by-side, then vote on the output you prefer.

Kimi K2 0905
✓ Preferred
Ministral 3 (8B Instruct 2512)
Open in Playground

FAQ

Common questions about Kimi K2 0905 vs Ministral 3 (8B Instruct 2512).

Which is better, Kimi K2 0905 or Ministral 3 (8B Instruct 2512)?

Kimi K2 0905 leads the LLM Stats Score 21.4 to 7.4. Kimi K2 0905 is made by Moonshot AI and Ministral 3 (8B Instruct 2512) is made by Mistral AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Kimi K2 0905 compare to Ministral 3 (8B Instruct 2512) in benchmarks?

Kimi K2 0905 scores HumanEval: 94.5%, MMLU: 90.2%, MATH: 89.1%, MMLU-Pro: 82.5%, GPQA: 75.8%. Ministral 3 (8B Instruct 2512) scores MATH: 87.6%, Wild Bench: 66.8%, Arena Hard: 50.9%, MM-MT-Bench: 8.1%.

What are the context window sizes for Kimi K2 0905 and Ministral 3 (8B Instruct 2512)?

Kimi K2 0905 supports 262K tokens and Ministral 3 (8B Instruct 2512) 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 0905 and Ministral 3 (8B Instruct 2512)?

Key differences include LLM Stats Score (21.4 vs 7.4), multimodal support (no vs yes), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Kimi K2 0905 and Ministral 3 (8B Instruct 2512)?

Kimi K2 0905 is developed by Moonshot AI and Ministral 3 (8B Instruct 2512) is developed by Mistral AI.

Related comparisons