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EXAONE 4.5 33B vs Mistral Large 4

Mistral Large 4 leads the LLM Stats Score 46.2 to 25.9.

LG AI Research · Mistral AI · Updated for 2026

Which is better?

Mistral Large 4 leads the overall LLM Stats Score 46.2 to 25.9, ranking #34 overall.

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

Choose EXAONE 4.5 33B

  • you are already invested in the LG AI Research ecosystem

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.

EXAONE 4.5 33B
LG AI Research
Mistral Large 4
Mistral AI
Core performance indexes
LLM Stats Score
25.9
#168
46.2
#34
Reasoning
26.5
#161
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

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
EXAONE 4.5 33B
Mistral Large 4
Vision
13.3#105
1.1#187
Tool use
10.3#135
27.1#26
Multimodal
16.2#90
1.7#160
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

15 reported for EXAONE 4.5 33B · 18 for Mistral Large 4

No common benchmarks found

EXAONE 4.5 33B 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

1017.0B diff

Mistral Large 4 has 1017.0B more parameters than EXAONE 4.5 33B, making it 3081.8% larger.

LG AI Research
EXAONE 4.5 33B
33.0Bparameters
Mistral AI
Mistral Large 4
1.1Tparameters
33.0B
EXAONE 4.5 33B
1050.0B
Mistral Large 4

Context Window

Maximum input and output token capacity

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

LG AI Research
EXAONE 4.5 33B
Input- tokens
Output- tokens
Mistral AI
Mistral Large 4
Input1,000,000 tokens
Output- tokens
Fri Oct 09 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both EXAONE 4.5 33B and Mistral Large 4 support multimodal inputs.

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

EXAONE 4.5 33B

Text
Images
Audio
Video

Mistral Large 4

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

EXAONE 4.5 33B

Proprietary

Closed source

Mistral Large 4

Proprietary

Closed source

Release Timeline

When each model was launched

EXAONE 4.5 33B was released on 2026-04-09, while Mistral Large 4 was released on 2026-10-06.

Mistral Large 4 is 6 months newer than EXAONE 4.5 33B.

EXAONE 4.5 33B

Apr 9, 2026

6 months ago

Mistral Large 4

Oct 6, 2026

2 days ago

6mo newer

Knowledge Cutoff

When training data ends

EXAONE 4.5 33B has a documented knowledge cutoff of 2024-12-01, while Mistral Large 4's cutoff date is not specified.

We can confirm EXAONE 4.5 33B's training data extends to 2024-12-01, but cannot make a direct comparison without Mistral Large 4's cutoff date.

EXAONE 4.5 33B

Dec 2024

Mistral Large 4

—

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against EXAONE 4.5 33B and Mistral Large 4 side-by-side, then vote on the output you prefer.

EXAONE 4.5 33B
✓ Preferred
Mistral Large 4
Open in Playground

FAQ

Common questions about EXAONE 4.5 33B vs Mistral Large 4.

Which is better, EXAONE 4.5 33B or Mistral Large 4?

Mistral Large 4 leads the LLM Stats Score 46.2 to 25.9. EXAONE 4.5 33B is made by LG AI Research 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 EXAONE 4.5 33B compare to Mistral Large 4 in benchmarks?

EXAONE 4.5 33B scores AIME 2025: 92.9%, AIME 2026: 92.6%, IFEval: 89.6%, AI2D: 89.0%, MathVista-Mini: 85.0%. 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 EXAONE 4.5 33B and Mistral Large 4?

EXAONE 4.5 33B 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 EXAONE 4.5 33B and Mistral Large 4?

Key differences include LLM Stats Score (25.9 vs 46.2). See the full comparison above for benchmark-by-benchmark results.

Who makes EXAONE 4.5 33B and Mistral Large 4?

EXAONE 4.5 33B is developed by LG AI Research and Mistral Large 4 is developed by Mistral AI.

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