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Hy4 preview vs Ministral 3 (8B Instruct 2512)

Hy4 preview leads the LLM Stats Score 51.0 to 7.7.

Tencent · Mistral AI · Updated for 2026

Which is better?

Hy4 preview leads the overall LLM Stats Score 51.0 to 7.7, ranking #14 overall.

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

Choose Hy4 preview

  • overall performance matters — it scores 51.0 and ranks #14 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Aug 2026

Choose Ministral 3 (8B Instruct 2512)

  • you are already invested in the Mistral AI ecosystem

At a glance

The differences that matter most.

Core performance indexes
51.0
#14
7.7
#285
50.8
#10
9.2
#263
Cost, coverage & limits
Benchmark wins
Input price
— / M
— / M
Output price
— / M
— / M
Context window

Individual benchmarks

32 reported for Hy4 preview · 4 for Ministral 3 (8B Instruct 2512)

No common benchmarks found

Hy4 preview and Ministral 3 (8B Instruct 2512)don'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

762.0B diff

Hy4 preview has 762.0B more parameters than Ministral 3 (8B Instruct 2512), making it 9525.0% larger.

Tencent
Hy4 preview
770.0Bparameters
Mistral AI
Ministral 3 (8B Instruct 2512)
8.0Bparameters
770.0B
Hy4 preview
8.0B
Ministral 3 (8B Instruct 2512)

Input capabilities

Documented input modalities across available providers

Ministral 3 (8B Instruct 2512) supports multimodal inputs, whereas Hy4 preview does not.

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

Hy4 preview

Text
Images
Audio
Video

Ministral 3 (8B Instruct 2512)

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

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

Hy4 preview

Apache 2.0

Open weights

Ministral 3 (8B Instruct 2512)

Apache 2.0

Open weights

Release Timeline

When each model was launched

Hy4 preview was released on 2026-08-28, while Ministral 3 (8B Instruct 2512) was released on 2025-12-04.

Hy4 preview is 9 months newer than Ministral 3 (8B Instruct 2512).

Hy4 preview

Aug 28, 2026

3 weeks ago

8mo newer
Ministral 3 (8B Instruct 2512)

Dec 4, 2025

9 months 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 Hy4 preview and Ministral 3 (8B Instruct 2512) side-by-side, then vote on the output you prefer.

Hy4 preview
✓ Preferred
Ministral 3 (8B Instruct 2512)
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FAQ

Common questions about Hy4 preview vs Ministral 3 (8B Instruct 2512).

Which is better, Hy4 preview or Ministral 3 (8B Instruct 2512)?

Hy4 preview leads the LLM Stats Score 51.0 to 7.7. Hy4 preview is made by Tencent 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 Hy4 preview compare to Ministral 3 (8B Instruct 2512) in benchmarks?

Hy4 preview scores GPQA: 92.3%, Terminal-Bench 2.1: 85.4%, WideSearch: 83.9%, MCP Atlas: 83.7%, SWE-bench Multilingual: 82.9%. 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 main differences between Hy4 preview and Ministral 3 (8B Instruct 2512)?

Key differences include LLM Stats Score (51.0 vs 7.7), multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.

Who makes Hy4 preview and Ministral 3 (8B Instruct 2512)?

Hy4 preview is developed by Tencent and Ministral 3 (8B Instruct 2512) is developed by Mistral AI.