Can I Run EXAONE 3.5 on NVIDIA RTX 6000 Ada Generation?
Written by Jakub Rusinowski · Last updated July 21, 2026
Yes, comfortably — EXAONE 3.5 32B at Q4_K_M needs 22.3 GB at 8K context (19.3 GB weights + 3 GB KV cache/overhead), leaving ~25.7 GB of the NVIDIA RTX 6000 Ada Generation's 48 GB, at ~40 tok/s (est.), with room for up to 32K context.
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NVIDIA RTX 6000 Ada Generation Specs
| VRAM | 48 GB |
| Memory Bandwidth | 960 GB/s |
EXAONE 3.5 32B on the NVIDIA RTX 6000 Ada Generation: VRAM by quantization
| Quant | VRAM needed | Fits 48 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 66.9 GB | ✗ No | — | — |
| Q8_0 | 36.9 GB | ✓ Yes | 32K | Build for this |
| Q6_K | 29.2 GB | ✓ Yes | 32K | — |
| Q5_K_M | 25.6 GB | ✓ Yes | 32K | Build for this |
| Q4_K_M | 22.3 GB | ✓ Yes | 32K | Build for this |
| Q3_K_M | 16.6 GB | ✓ Yes | 32K | — |
| Q2_K | 13.5 GB | ✓ Yes | 32K | — |
Assumes an 8K-token context with an f16 KV cache. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 48 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
Context costs VRAM too. At Q4_K_M on the NVIDIA RTX 6000 Ada Generation: 8K 22.3 GB · 32K 28.7 GB. Every window this model publishes still fits 48 GB.
No compatible GPU? EXAONE 3.5 32B on 32 GB of system RAM, CPU only: runs comfortably.
EXAONE 3.5 Sizes That Fit the NVIDIA RTX 6000 Ada Generation (at 8K context)
| EXAONE 3.5 32B | Q4_K_M · 22.3 GB at 8K context · ~40 tok/s (est.) |
| EXAONE 3.5 7.8B | Q4_K_M · 6.6 GB at 8K context · ~123 tok/s (est.) |
| EXAONE 3.5 2.4B | Q4_K_M · 2.9 GB at 8K context · ~237 tok/s (est.) |
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Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
FAQ
Does the NVIDIA RTX 6000 Ada Generation have enough VRAM for EXAONE 3.5?
Yes, comfortably — EXAONE 3.5 32B at Q4_K_M needs 22.3 GB at 8K context (19.3 GB weights + 3 GB KV cache/overhead), leaving ~25.7 GB of the NVIDIA RTX 6000 Ada Generation's 48 GB, at ~40 tok/s (est.), with room for up to 32K context.
Which quantization of EXAONE 3.5 should I use on the NVIDIA RTX 6000 Ada Generation?
EXAONE 3.5 32B at Q4_K_M quantization needs 22.3 GB at 8K context (19.3 GB weights + 3 GB KV cache/overhead), estimated ~40 tokens/sec, up to 32K context.
Every EXAONE 3.5 size on the NVIDIA RTX 6000 Ada Generation
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| EXAONE 3.5 32B | 22.3 GB | Runs | ~40 tok/s |
| EXAONE 3.5 7.8B | 6.6 GB | Runs | ~123 tok/s |
| EXAONE 3.5 2.4B | 2.9 GB | Runs | ~237 tok/s |
EXAONE 3.5 on Other GPUs
- EXAONE 3.5 on NVIDIA L40S
- EXAONE 3.5 on Apple M3 Pro
- EXAONE 3.5 on NVIDIA GeForce RTX 5090
- EXAONE 3.5 on Apple M4
- EXAONE 3.5 on Apple M2 Pro
Popular Models on the NVIDIA RTX 6000 Ada Generation
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