Can I Run EXAONE 3.5 on NVIDIA GeForce RTX 3070 Ti?
Written by Jakub Rusinowski · Last updated September 29, 2026
Yes, comfortably — EXAONE 3.5 7.8B at Q4_K_M needs 6.6 GB at 8K context (4.7 GB weights + 1.9 GB KV cache/overhead), leaving ~1.4 GB of the NVIDIA GeForce RTX 3070 Ti's 8 GB, at ~62 tok/s (est.), with room for up to 16K context.
See what else this hardware can run →
or compare on Vast.ai from $0.35/hr (typical low · varies)
As an Amazon Associate we earn from qualifying purchases. Cloud GPU links are referral links — we may earn a commission at no extra cost to you.
NVIDIA GeForce RTX 3070 Ti Specs
| VRAM | 8 GB |
| Memory Bandwidth | 608 GB/s |
EXAONE 3.5 7.8B on the NVIDIA GeForce RTX 3070 Ti: VRAM by quantization
| Quant | VRAM needed | Fits 8 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 17.5 GB | ✗ No | — | — |
| Q8_0 | 10.2 GB | ✗ No | — | — |
| Q6_K | 8.3 GB | ✗ No | — | — |
| Q5_K_M | 7.4 GB | ✓ Yes | 8K | — |
| Q4_K_M | 6.6 GB | ✓ Yes | 16K | — |
| Q3_K_M | 5.2 GB | ✓ Yes | 16K | — |
| Q2_K | 4.4 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 8 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 GeForce RTX 3070 Ti: 8K 6.6 GB · 32K 9.8 GB ✗. Past 32K it no longer fits 8 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
No compatible GPU? EXAONE 3.5 7.8B on 16 GB of system RAM, CPU only: runs.
EXAONE 3.5 Sizes That Fit the NVIDIA GeForce RTX 3070 Ti (at 8K context)
| EXAONE 3.5 7.8B | Q4_K_M · 6.6 GB at 8K context · ~62 tok/s (est.) |
| EXAONE 3.5 2.4B | Q4_K_M · 2.9 GB at 8K context · ~145 tok/s (est.) |
At 2 hrs/day, buying (~$599) beats renting at $0.34/hr after about 2.4 years.
Affiliate links — we may earn a commission if you sign up, at no extra cost to you.
Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
FAQ
Is the NVIDIA GeForce RTX 3070 Ti enough to run EXAONE 3.5 locally?
Yes, comfortably — EXAONE 3.5 7.8B at Q4_K_M needs 6.6 GB at 8K context (4.7 GB weights + 1.9 GB KV cache/overhead), leaving ~1.4 GB of the NVIDIA GeForce RTX 3070 Ti's 8 GB, at ~62 tok/s (est.), with room for up to 16K context.
What's the best EXAONE 3.5 size for the NVIDIA GeForce RTX 3070 Ti?
EXAONE 3.5 7.8B at Q4_K_M quantization needs 6.6 GB at 8K context (4.7 GB weights + 1.9 GB KV cache/overhead), estimated ~62 tokens/sec, up to 16K context.
Every EXAONE 3.5 size on the NVIDIA GeForce RTX 3070 Ti
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| EXAONE 3.5 32B | 22.3 GB | Does not fit | — |
| EXAONE 3.5 7.8B | 6.6 GB | Runs | ~62 tok/s |
| EXAONE 3.5 2.4B | 2.9 GB | Runs | ~145 tok/s |
EXAONE 3.5 on Other GPUs
- EXAONE 3.5 on NVIDIA GeForce RTX 5060 Ti 8GB
- EXAONE 3.5 on NVIDIA GeForce RTX 5060
- EXAONE 3.5 on NVIDIA GeForce RTX 4060
- EXAONE 3.5 on NVIDIA GeForce RTX 3070
- EXAONE 3.5 on AMD Radeon RX 9060 XT 8GB
Popular Models on the NVIDIA GeForce RTX 3070 Ti
- DeepSeek R1 on NVIDIA GeForce RTX 3070 Ti
- Qwen 3 on NVIDIA GeForce RTX 3070 Ti
- Qwen 2.5 Family on NVIDIA GeForce RTX 3070 Ti
VRAM Tier
Troubleshooting
Buying Guide
← Can I Run It? | EXAONE 3.5 Model Page | NVIDIA GeForce RTX 3070 Ti GPU Page | VRAM calculator | Check Your Hardware