The AI arena is free today

Open Superagent

Gemini 4 Argon vs Ministral 3 (8B Instruct 2512)

Gemini 4 Argon leads the LLM Stats Score 55.1 to 7.3.

Google · Mistral AI · Updated for 2026

Which is better?

Gemini 4 Argon leads the overall LLM Stats Score 55.1 to 7.3, ranking #4 overall.

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

Choose Gemini 4 Argon

  • overall performance matters — it scores 55.1 and ranks #4 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026

Choose Ministral 3 (8B Instruct 2512)

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

At a glance

The differences that matter most.

Gemini 4 Argon
Google
Ministral 3 (8B Instruct 2512)
Mistral AI
Core performance indexes
LLM Stats Score
55.1
#4
7.3
#310
Reasoning
53.2
#6
8.9
#288
Cost, coverage & limits
Benchmark wins
—
—
Input price
$2.00 / M
— / M
Output price
$10.00 / M
— / M
Context window
1,048,576
—

Individual benchmarks

19 reported for Gemini 4 Argon · 4 for Ministral 3 (8B Instruct 2512)

No common benchmarks found

Gemini 4 Argon 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

Context Window

Maximum input and output token capacity

Only Gemini 4 Argon specifies input context (1,048,576 tokens). Only Gemini 4 Argon specifies output context (1,048,576 tokens).

Google
Gemini 4 Argon
Input1,048,576 tokens
Output1,048,576 tokens
Mistral AI
Ministral 3 (8B Instruct 2512)
Input- tokens
Output- tokens
Thu Oct 22 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Gemini 4 Argon and Ministral 3 (8B Instruct 2512) support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Gemini 4 Argon

Text
Images
Audio
Video

Ministral 3 (8B Instruct 2512)

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 4 Argon 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.

Gemini 4 Argon

Proprietary

Closed source

Ministral 3 (8B Instruct 2512)

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemini 4 Argon was released on 2026-09-30, while Ministral 3 (8B Instruct 2512) was released on 2025-12-04.

Gemini 4 Argon is 10 months newer than Ministral 3 (8B Instruct 2512).

Gemini 4 Argon

Sep 30, 2026

2 weeks ago

10mo newer
Ministral 3 (8B Instruct 2512)

Dec 4, 2025

10 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?

Judge for yourself.

Run your own prompts against Gemini 4 Argon and Ministral 3 (8B Instruct 2512) side-by-side, then vote on the output you prefer.

Gemini 4 Argon
✓ Preferred
Ministral 3 (8B Instruct 2512)
Open in Playground

FAQ

Common questions about Gemini 4 Argon vs Ministral 3 (8B Instruct 2512).

Which is better, Gemini 4 Argon or Ministral 3 (8B Instruct 2512)?

Gemini 4 Argon leads the LLM Stats Score 55.1 to 7.3. Gemini 4 Argon is made by Google 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 Gemini 4 Argon compare to Ministral 3 (8B Instruct 2512) in benchmarks?

Gemini 4 Argon scores Graphwalks BFS <128k: 99.7%, Vibe Code Bench: 91.9%, LVBench: 91.7%, LABBench2: 88.8%, Graphwalks BFS >128k: 84.2%. 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 Gemini 4 Argon and Ministral 3 (8B Instruct 2512)?

Gemini 4 Argon supports 1.0M 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 Gemini 4 Argon and Ministral 3 (8B Instruct 2512)?

Key differences include LLM Stats Score (55.1 vs 7.3), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 4 Argon and Ministral 3 (8B Instruct 2512)?

Gemini 4 Argon is developed by Google and Ministral 3 (8B Instruct 2512) is developed by Mistral AI.

Related comparisons