Can I Run Cogito v1 on NVIDIA GeForce RTX 5070?
Written by Jakub Rusinowski · Last updated July 12, 2026
Yes, but it's tight — Cogito v1 14B at Q4_K_M needs 10.9 GB at 8K context (8.5 GB weights + 2.4 GB KV cache/overhead), leaving ~1.1 GB of the NVIDIA GeForce RTX 5070's 12 GB, at ~54 tok/s (est.), with room for up to 8K context.
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NVIDIA GeForce RTX 5070 Specs
| VRAM | 12 GB |
| Memory Bandwidth | 672 GB/s |
Cogito v1 14B on the NVIDIA GeForce RTX 5070: VRAM by quantization
| Quant | VRAM needed | Fits 12 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 30.4 GB | ✗ No | — | — |
| Q8_0 | 17.3 GB | ✗ No | — | — |
| Q6_K | 13.9 GB | ✗ No | — | — |
| Q5_K_M | 12.3 GB | ✗ No | — | — |
| Q4_K_M | 10.9 GB | ✓ Yes | 8K | — |
| Q3_K_M | 8.4 GB | ✓ Yes | 16K | — |
| Q2_K | 7 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 12 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 5070: 8K 10.9 GB · 32K 15.7 GB ✗ · 128K 35 GB ✗. Past 32K it no longer fits 12 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
No compatible GPU? Cogito v1 14B on 16 GB of system RAM, CPU only: runs, but it is tight.
Cogito v1 Sizes That Fit the NVIDIA GeForce RTX 5070 (at 8K context)
| Cogito v1 14B | Q4_K_M · 10.9 GB at 8K context · ~54 tok/s (est.) |
| Cogito v1 8B | Q4_K_M · 6.7 GB at 8K context · ~86 tok/s (est.) |
| Cogito v1 3B | Q4_K_M · 3.6 GB at 8K context · ~160 tok/s (est.) |
At 2 hrs/day, buying (~$549) beats renting at $0.34/hr after about 2.2 years.
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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 GeForce RTX 5070 have enough VRAM for Cogito v1?
Yes, but it's tight — Cogito v1 14B at Q4_K_M needs 10.9 GB at 8K context (8.5 GB weights + 2.4 GB KV cache/overhead), leaving ~1.1 GB of the NVIDIA GeForce RTX 5070's 12 GB, at ~54 tok/s (est.), with room for up to 8K context.
Which quantization of Cogito v1 should I use on the NVIDIA GeForce RTX 5070?
Cogito v1 14B at Q4_K_M quantization needs 10.9 GB at 8K context (8.5 GB weights + 2.4 GB KV cache/overhead), estimated ~54 tokens/sec, up to 8K context.
Every Cogito v1 size on the NVIDIA GeForce RTX 5070
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| Cogito v1 70B | 45.7 GB | Does not fit | — |
| Cogito v1 32B | 22.3 GB | Does not fit | — |
| Cogito v1 14B | 10.9 GB | Runs | ~54 tok/s |
| Cogito v1 8B | 6.7 GB | Runs | ~86 tok/s |
| Cogito v1 3B | 3.6 GB | Runs | ~160 tok/s |
Cogito v1 on Other GPUs
- Cogito v1 on NVIDIA GeForce RTX 4070 Ti
- Cogito v1 on NVIDIA GeForce RTX 4070 Super
- Cogito v1 on NVIDIA GeForce RTX 4070
- Cogito v1 on NVIDIA GeForce RTX 3060 (12GB)
- Cogito v1 on Intel Arc B580
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VRAM Tier
Troubleshooting
- CUDA out of memory — why it happens and how to fix it
- Which GGUF quant should I download? (Q4 vs Q5 vs Q8)
Buying Guide
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