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Llama-3.3 Nemotron Super 49B v1 vs Mistral Large 4

Mistral Large 4 leads the LLM Stats Score 46.2 to 13.1.

NVIDIA · Mistral AI · Updated for 2026

Which is better?

Mistral Large 4 leads the overall LLM Stats Score 46.2 to 13.1, ranking #34 overall.

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

Choose Llama-3.3 Nemotron Super 49B v1

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

Choose Mistral Large 4

  • overall performance matters — it scores 46.2 and ranks #34 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

Llama-3.3 Nemotron Super 49B v1
NVIDIA
Mistral Large 4
Mistral AI
Core performance indexes
LLM Stats Score
13.1
#262
46.2
#34
Reasoning
13.2
#255
44.0
#43
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$0.68 / M
Output price
— / M
$2.09 / M
Context window
—
1,000,000

Individual benchmarks

7 reported for Llama-3.3 Nemotron Super 49B v1 · 18 for Mistral Large 4

No common benchmarks found

Llama-3.3 Nemotron Super 49B v1 and Mistral Large 4don'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

1000.1B diff

Mistral Large 4 has 1000.1B more parameters than Llama-3.3 Nemotron Super 49B v1, making it 2004.2% larger.

NVIDIA
Llama-3.3 Nemotron Super 49B v1
49.9Bparameters
Mistral AI
Mistral Large 4
1.1Tparameters
49.9B
Llama-3.3 Nemotron Super 49B v1
1050.0B
Mistral Large 4

Context Window

Maximum input and output token capacity

Only Mistral Large 4 specifies input context (1,000,000 tokens).

NVIDIA
Llama-3.3 Nemotron Super 49B v1
Input- tokens
Output- tokens
Mistral AI
Mistral Large 4
Input1,000,000 tokens
Output- tokens
Sat Oct 10 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Mistral Large 4 supports multimodal inputs, whereas Llama-3.3 Nemotron Super 49B v1 does not.

Mistral Large 4 can handle both text and other forms of data like images, making it suitable for multimodal applications.

Llama-3.3 Nemotron Super 49B v1

Text
Images
Audio
Video

Mistral Large 4

Text
Images
Audio
Video

License

Usage and distribution terms

Llama-3.3 Nemotron Super 49B v1 is licensed under Llama 3.1 Community License, while Mistral Large 4 uses a proprietary license.

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

Llama-3.3 Nemotron Super 49B v1

Llama 3.1 Community License

Open weights

Mistral Large 4

Proprietary

Closed source

Release Timeline

When each model was launched

Llama-3.3 Nemotron Super 49B v1 was released on 2025-03-18, while Mistral Large 4 was released on 2026-10-06.

Mistral Large 4 is 19 months newer than Llama-3.3 Nemotron Super 49B v1.

Llama-3.3 Nemotron Super 49B v1

Mar 18, 2025

1.6 years ago

Mistral Large 4

Oct 6, 2026

4 days ago

1.6yr newer

Knowledge Cutoff

When training data ends

Llama-3.3 Nemotron Super 49B v1 has a documented knowledge cutoff of 2023-12-31, while Mistral Large 4's cutoff date is not specified.

We can confirm Llama-3.3 Nemotron Super 49B v1's training data extends to 2023-12-31, but cannot make a direct comparison without Mistral Large 4's cutoff date.

Llama-3.3 Nemotron Super 49B v1

Dec 2023

Mistral Large 4

—

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Llama-3.3 Nemotron Super 49B v1 and Mistral Large 4 side-by-side, then vote on the output you prefer.

Llama-3.3 Nemotron Super 49B v1
✓ Preferred
Mistral Large 4
Open in Playground

FAQ

Common questions about Llama-3.3 Nemotron Super 49B v1 vs Mistral Large 4.

Which is better, Llama-3.3 Nemotron Super 49B v1 or Mistral Large 4?

Mistral Large 4 leads the LLM Stats Score 46.2 to 13.1. Llama-3.3 Nemotron Super 49B v1 is made by NVIDIA and Mistral Large 4 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 Llama-3.3 Nemotron Super 49B v1 compare to Mistral Large 4 in benchmarks?

Llama-3.3 Nemotron Super 49B v1 scores MATH-500: 96.6%, MT-Bench: 91.7%, MBPP: 91.3%, Arena Hard: 88.3%, BFCL v2: 73.7%. Mistral Large 4 scores B3 AI Security Benchmark: 93.3%, CyBench: 93.0%, SciCode: 91.8%, KORABench: 84.5%, CyberGym: 82.0%.

What are the context window sizes for Llama-3.3 Nemotron Super 49B v1 and Mistral Large 4?

Llama-3.3 Nemotron Super 49B v1 supports an unknown number of tokens and Mistral Large 4 supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Llama-3.3 Nemotron Super 49B v1 and Mistral Large 4?

Key differences include LLM Stats Score (13.1 vs 46.2), multimodal support (no vs yes), licensing (Llama 3.1 Community License vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Llama-3.3 Nemotron Super 49B v1 and Mistral Large 4?

Llama-3.3 Nemotron Super 49B v1 is developed by NVIDIA and Mistral Large 4 is developed by Mistral AI.

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