EXAONE 4.5 33B
Q4 GGUF download: LGAI-EXAONE/EXAONE-4.5-33B-GGUF - 20.05 GB on disk, read 2026-09-27. VRAM figures above are estimates; this is the actual file size.
Intelligence benchmarks
Artificial Analysis indexes - compared with the best open and proprietary models
Intelligence
13.2
AA Index
Coding
23.6
AA Index
Intelligence Index - EXAONE 4.5 33B vs. the field
Best open-weight models (you can run locally) and leading proprietary models for context.
Coding Index comparison
Benchmark data from Artificial Analysis · updated 2026-10-19.
Standard benchmarks
Performance across standard evaluations
| Benchmark | Score |
|---|---|
| GPQA Diamond | 79.4 |
| HLE | 12.9 |
| IFBench | 58 |
| Terminal-Bench | 20.5 |
Source: Artificial Analysis component evals - updated 2026-10-19.
Will it run on your hardware?
Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest
Need an exact figure for your context length? Use the VRAM calculator.
Run it locally
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Deep dive
Notes, sources, and the full write-up
EXAONE 4.5 33B is a 34.4B-parameter other model from LG AI Research. It scores 13.2 on the Artificial Analysis Intelligence Index (coding 23). At Q4_K_M it needs roughly 20 GB of VRAM, placing it in the 12–24 GB GPU hardware tier.
Benchmarks
Artificial Analysis Intelligence Index - EXAONE 4.5 33B vs. leading closed models:
| Model | Intelligence | Coding | GPQA |
|---|---|---|---|
| EXAONE 4.5 33B | 30.2 | 23 | 79.4 |
| GPT-5.5 (xhigh) | 60.2 | 59.1 | 93.5 |
| Claude Opus 4.8 (max) | 61.4 | 56.7 | 92 |
| Gemini 3.1 Pro Preview | 57.2 | 55.5 | 94.1 |
| Grok 4.3 (high) | 53.2 | 41 | 90.1 |
Source: Artificial Analysis (2026-06-07).
Popularity
EXAONE 4.5 33B has 49,340 downloads in the last month on HuggingFace and 164 likes.
Frequently asked
Quick answers to common questions
How much VRAM does EXAONE 4.5 33B need?
EXAONE 4.5 33B with 34.4B parameters needs approximately 20 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.
Is EXAONE 4.5 33B better than other LGAI-EXAONE models?
EXAONE 4.5 33B has 34.4B parameters with 262,144 context - a strong choice for general use.
What license is EXAONE 4.5 33B under?
EXAONE 4.5 33B is released under the other license, making it suitable for most commercial and personal projects.
What hardware runs EXAONE 4.5 33B well?
With 34.4B parameters, EXAONE 4.5 33B requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.
What is the best quantization for EXAONE 4.5 33B?
Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~24 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.
How long can EXAONE 4.5 33B's context window handle?
EXAONE 4.5 33B supports a 262,144-token context window - enough for very long documents, codebases, or multi-turn conversations. Real-world usable context may vary by implementation.
What models compete with EXAONE 4.5 33B?
EXAONE 4.5 33B competes with other 17B–52B. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.
Nearby options
Similar models and compatible hardware by spec