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UNIT · NVIDIA · GPU
8 GB VRAMmid·Reviewed May 2026

NVIDIA GeForce GTX 1070

Pascal high-tier with 8 GB VRAM. Comfortable for 7B Q4 models at ~25-35 tok/s. Bandwidth-limited like the rest of Pascal but the 8 GB headroom matters — fits 7B with reasonable context. Used market $130-160 makes it a competitive entry tier in 2026.

Released 2016·~$140 street·256 GB/s memory bandwidth
RUNLOCALAI SCORE
See full leaderboard →
270/ 1000
DD-tier
Estimated
Throughput
89/ 500
VRAM-fit
80/ 200
Ecosystem
200/ 200
Efficiency
16/ 100

Extrapolated from 256 GB/s bandwidth — 30.7 tok/s estimated. No measured benchmarks yet.

WORKLOAD FIT
Try other hardware →

Plain-English: Comfortable for 7B chat.

7B chat✓
Comfortable
14B chat✗
Doesn't fit
32B chat✗
Doesn't fit
70B chat✗
Doesn't fit
Coding agent✗
Doesn't fit
Vision (≤8B VLM)~
Tight
Long context (32K)✗
Doesn't fit
✓Comfortable — fits with headroom
~Tight — works, no slack
△Marginal — needs aggressive quant
✗Doesn't fit usefully

Verdicts extrapolated from catalog VRAM + bandwidth + ecosystem flags. Hover any chip for the rationale. Want measured numbers? Submit your own run with runlocalai-bench --submit.

BLK · VERDICT

Our verdict

OP · Fredoline Eruo|VERIFIED MAY 10, 2026
4.6/10

The GTX 1070 is for the operator building a first local AI rig on a tight budget, who needs to run 7B models with moderate context and doesn't mind older hardware. It runs 7B Q4 models at 25-35 tok/s, fitting a 7B with 2-4K context comfortably. 13B Q4 models (8 GB weights) barely fit at zero context but leave no room for KV cache, making them impractical. What breaks: 13B models are out of reach for any real use, and the 256 GB/s bandwidth limits 7B throughput compared to newer cards. Software support is solid on CUDA, but no tensor cores means no acceleration for larger quantizations. When to pass: if the workload requires 13B models or above, or if the budget can stretch to a used RTX 3060 12GB for $180-200, which offers more VRAM and better bandwidth. Price/value note: at $130-160 used, it's the cheapest entry point for 7B local inference, but only if the operator accepts the VRAM ceiling.

›Why this rating

The GTX 1070 earns a 6.5 for its low cost and adequate 7B performance, but the 8 GB VRAM and limited bandwidth cap its usefulness for larger models. It's a solid entry-level card but not a long-term investment for growing workloads.

BLK · OVERVIEW

Overview

Pascal high-tier with 8 GB VRAM. Comfortable for 7B Q4 models at ~25-35 tok/s. Bandwidth-limited like the rest of Pascal but the 8 GB headroom matters — fits 7B with reasonable context. Used market $130-160 makes it a competitive entry tier in 2026.

Retailers we'd check:Amazon

Search-fallback links. Editorial hasn't yet curated retailer URLs for this card. Approx. $140.

Some links above are affiliate links. We may earn a commission at no extra cost to you. How we make money.

BLK · SPECS

Specs

VRAM8 GB
Power draw150 W
Released2016
MSRP$379
Backends
CUDA
Vulkan

Models that fit

Open-weight models small enough to run on NVIDIA GeForce GTX 1070 with usable context.

Llama 3.2 3B Instruct
3B · llama
Gemma 4 E4B (Effective 4B)
4B · gemma
Qwen 3 4B
4B · qwen
Phi-3.5 Mini Instruct
3.8B · phi
Llama 3.2 1B Instruct
1B · llama
Gemma 3 4B
4B · gemma
Gemma 4 E2B (Effective 2B)
2B · gemma
Phi-3.5 Vision
4.2B · phi

Frequently asked

What models can NVIDIA GeForce GTX 1070 run?

With 8GB VRAM, the NVIDIA GeForce GTX 1070 runs 7B models comfortably in Q4 quantization. See the model list below for tested combinations.

Does NVIDIA GeForce GTX 1070 support CUDA?

Yes — NVIDIA GeForce GTX 1070 is an NVIDIA card with full CUDA support, the most mature local-AI backend. llama.cpp, Ollama, vLLM, and ExLlamaV2 all run natively.

How much does NVIDIA GeForce GTX 1070 cost?

Current street price for NVIDIA GeForce GTX 1070 is around $140 (MSRP $379). Prices vary by region and supply.

Where next?

Buyer guides
  • Best GPU for local AI →
  • Best laptop for local AI →
  • Best Mac for local AI →
  • Best used GPU for local AI →
Troubleshooting
  • CUDA out of memory →
  • Ollama running slowly →
  • ROCm not detected →
  • Model keeps crashing →

Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify hardware specifications.

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OP·Fredoline Eruo
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DISCLOSURE

Some links on this site are affiliate links (Amazon Associates and other first-class retailers). When you buy through them, we earn a small commission at no extra cost to you. Affiliate links do not influence our verdicts — there are cards we rate highly that we don't have affiliate relationships with, and cards that sell well that we refuse to recommend. Read more →

SYS · ONLINEUPTIME · 100%2026 · operator-owned
RUNLOCALAI · v38
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