NVIDIA · Blackwell · 2025
NVIDIA GeForce RTX 5070 for local AI
Fast memory, but 12GB caps it at 14B-class models; the RTX 5060 Ti 16GB holds larger ones.
Updated · Speeds marked ~ are estimates; seemethodology
- VRAM
- 12GB
- Bandwidth
- 672 GB/s
- Power
- 250W
- Runs well
- 3 models
RTX 5070
Typically about $800
Can the RTX 5070 run LLMs?
The RTX 5070 has 12GB of GDDR7 and 672 GB/s of memory bandwidth, which decides how big a model fits and how fast it generates text. It comfortably runs models up to about 15B parameters: the largest in our catalog is Phi-4 at Q3_K_M (9.8GB with 8K context, ~69 tokens/sec). Our top all-round pick for it is Qwen3.5 9B (Q6_K, ~60 tokens/sec). Llama 3.3 70B Instruct only runs with partial CPU offload, at about 1.2 tokens/sec with CPU offload.
Recommendations
Best models for the RTX 5070
Best overall · also coding, reasoning, vision, fastest
Qwen3.5 9BQ6_K · 10GB · ~60 tokens/sec
Runs wellLargest model that fits
Phi-4Q3_K_M · 10GB · ~69 tokens/sec
Runs wellStretch pick (CPU offload)
Qwen3.6 35B-A3BQ4_K_M · 24GB · about 35 tokens/sec with CPU offload
Partial offload
Compatibility
What runs on the RTX 5070
Every current model in our catalog, at the best quantization that fits in 12GB with 8K tokens of context. "Partial offload" means part of the model runs from system RAM (we assume 64GB), which is much slower.
| Model | Parameters | Best quant | Memory | Speed | Verdict |
|---|---|---|---|---|---|
| Gemma 4 E4B | 8B | Q8_0 | 10 GB | ~54 tok/s | Runs well |
| Qwen3.5 9B | 9B | Q6_K | 9.5 GB | ~60 tok/s | Runs well |
| Phi-4 | 14.7B | Q3_K_M | 9.8 GB | ~69 tok/s | Runs well |
| gpt-oss-20b | 20.9B (3.6B active) | MXFP4 | 15 GB | ~47 tok/s | Partial offload |
| Gemma 4 26B A4B | 26B (3.8B active) | Q4_K_M | 17 GB | ~39 tok/s | Partial offload |
| Qwen3.8 27B | 27B | Q4_K_M | 18 GB | ~6.0 tok/s | Partial offload |
| Gemma 4 31B | 31B | Q4_K_M | 22 GB | ~3.8 tok/s | Partial offload |
| Qwen3.6 35B-A3B | 35B (3B active) | Q4_K_M | 24 GB | ~35 tok/s | Partial offload |
| GLM-4.5-Air | 106B (12B active) | — | — | — | Won't fitWhat it needs |
| Llama 4 Scout | 109B (17B active) | — | — | — | Won't fitWhat it needs |
| gpt-oss-120b | 117B (5.1B active) | — | — | — | Won't fitWhat it needs |
| Qwen3.5 122B-A10B | 122B (10B active) | — | — | — | Won't fitWhat it needs |
| DeepSeek V4 Flash | 284B (13B active) | — | — | — | Won't fitWhat it needs |
| GLM-5.3-Flash | 320B (18B active) | — | — | — | Won't fitWhat it needs |
| GLM-5.3 | 744B (40B active) | — | — | — | Won't fitWhat it needs |
Performance
RTX 5070 vs. alternatives on Qwen3.8 27B
Generation speed in tokens per second for a single user. Token generation is limited mostly by memory bandwidth, which is why bandwidth predicts these results so well.
Measured
RTX 5070 benchmark results
| Model | Quant | Runtime | Generation | Prompt | Source |
|---|---|---|---|---|---|
| Llama 2 7B Chat | Q4_0 | llama.cpp (CUDA) | 130 tok/s | 5185 tok/s | llama.cpp discussion #15013: Performance of llama.cpp on NVIDIA CUDA · October 2026 |
Our take
Should you buy the RTX 5070 for AI?
The RTX 5070 has 12GB of GDDR7 on a 192-bit bus, good for 672 GB/s. That bandwidth makes 8B and 14B models fast, but 12GB leaves little room for 20B-plus models or long context. Gaming performance is well ahead of the RTX 5060 Ti 16GB, yet for LLMs the cheaper 5060 Ti can load models the 5070 cannot. At about $800 new in October 2026, buy it for gaming first and local AI second.
What we like
- 672 GB/s makes small models very fast
- Efficient 250W board power
- Full CUDA support
Watch out for
- 12GB limits model size and context
- Costs more than the RTX 5060 Ti 16GB, which holds larger models
Best for: Gaming PCs that also run 8B to 14B models · Fast chat and coding assistants built on small models
Specifications
RTX 5070 specs that matter for AI
- Memory
- 12GB GDDR7
- Memory bandwidth
- 672 GB/s
- Memory bus
- 192-bit
- Architecture
- Blackwell
- Power
- 250W
- Interface
- PCIe 5.0 x16
- Released
- 2025
- Launch price
- $549
- Street price (new)
- ~$800 (2026-10)
- Street price (used)
- ~$650 (2026-10)
- Software
- CUDA, Vulkan
Cross-shop
Alternatives to the RTX 5070
Frequently asked questions
How much VRAM does the RTX 5070 have?
The NVIDIA GeForce RTX 5070 has 12GB of GDDR7 with 672 GB/s of memory bandwidth on a 192-bit bus.
What is the largest LLM the RTX 5070 can run?
Fully in GPU memory, the largest model in our catalog that runs comfortably is Phi-4 (14.7B) at Q3_K_M, using about 10GB with 8K context at ~69 tokens/sec.
Can the RTX 5070 run Llama 3.3 70B?
Only with partial CPU offload. At Q4_K_M the model needs about 47GB with 8K context, so part of it spills into system RAM and speed drops to about 1.2 tokens/sec with CPU offload. For usable 70B speeds you want 48GB of VRAM or more (for example two 24GB cards).
What is the best LLM to run on the RTX 5070?
Our top pick is Qwen3.5 9B at Q6_K, which fits in 12GB with room for 8K of context and runs at ~60 tokens/sec. See our full list of the best models for the RTX 5070 for coding, reasoning, and vision picks.
Is the RTX 5070 good for local AI in 2026?
Fast memory, but 12GB caps it at 14B-class models; the RTX 5060 Ti 16GB holds larger ones.