NVIDIA GeForce GTX 1070
No editorial image yet — generic vendor mark shown. Credentials in spec table below.
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.
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Sub-scores sum to 385 / 1000. Headline = 385 × 0.70 (Estimated-confidence discount) = 270. This is an algorithmic performance-tier score — distinct from, and often lower than, the editorial “Our verdict” below, which weighs value and real-world fit (especially for hardware we haven’t measured yet). How scoring works →
Extrapolated from 256 GB/s bandwidth — 30.7 tok/s estimated. No measured benchmarks yet.
Plain-English: Comfortable for 7B chat.
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.
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.
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.
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Specs
| VRAM | 8 GB |
| Power draw (peak) | 150 W |
| Released | 2016 |
| MSRP | $379 |
| Backends | CUDA Vulkan |
Models that fit
Open-weight models small enough to run on NVIDIA GeForce GTX 1070 with usable context.
Hardware worth comparing
The closest alternatives by price, memory bandwidth, and form factor, plus a step up and down — so you can frame the buying decision against real options.
Frequently asked
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Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify hardware specifications.