NVIDIA GTX 1070 - 8GB usable
An entry into 8GB CUDA, adequate for 7B models and learning the stack. Pascal predates tensor cores, so prompts process slowly.
Specifications
| Brand | NVIDIA |
|---|---|
| Model | GTX 1070 |
| Usable VRAM | 8GB |
| Architecture | Pascal |
| CUDA / Stream Processors | 1,920 |
| Memory Bandwidth | 256 GB/s |
| TDP | 150W |
| FP32 TFLOPS | 6.5 |
Current Offers
New from $109
Prices last updated:
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Price History
- Amazon$109current
- Newegg$150at low
For AI / LLM Use
Limited VRAM restricts you to 7B quantized models. Slower generation, usable but not snappy. Older architecture may have limited software support (check CUDA compatibility).
What Models Can It Run?
- 7B Q6_K, 14B Q3_K (tight)
- 7B Q4_K_M only
Estimated Performance
Generation: ~19 tokens/sec
Prefill: ~116 tokens/sec
Recommended Quantisations
- Q4_K_M for 7B models
- Q3_K for larger experiments
Pros & Cons
Pros
- Only 150W TDP: power efficient
- Consumer card: easy to install, display output
Cons
- Only 8GB usable VRAM: limited to small models
- Low memory bandwidth: slower token generation
- Older Pascal architecture: verify current CUDA support
Community Verdict
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