RTX 5070 Ti LLM Performance
Local LLM Performance: 58.0 t/s average on 14B models at 16k context. Updated Benchmarks: March 2026.
58.0T/s
2,304T/s
Summary
In our 2026 testing, we found the RTX 5070 Ti to be a strong performer, though it is hampered by its memory capacity. Thanks to its high-bandwidth GDDR7 memory, we measured speeds that outpace the RTX 3090 in both token generation and prompt processing. However, at its current price, the 16GB VRAM cap makes it a difficult recommendation for single-card users compared to the, 24GB RTX 3090. That said, for those building dual-GPU rigs, we believe this card is a solid choice; the combined bandwidth and FP4 capability provide a great foundation for local agentic workflows like Qwen3.5.
Key Insights
Relative Performance (Token Generation)
Current Price in US
$916
Avg. Market Value
Current Pricing
Biggest LLMs You Can Run on This GPU
The models below represent the largest language models that fit fully in VRAM on this GPU using 4-bit quantization (GGUF). Benchmarks include token generation and prompt processing speeds measured at their maximum supported context length.
Note: Context values are grouped into standard tiers (4K, 16K, 32K, 64K, 128K). Models may support slightly higher context, but they remain in the lower tier unless they reach the next bracket.
RTX 5070 Ti local LLM Inference Performance vs Similar GPUs
Compare prompt ingestion and token generation speeds against similar GPUs across widely used local models and extended context lengths up to 256K.
Local LLM Benchmarks
Prompt processing (t/s) and token generation speed (t/s) across different open weight models and context lengths.
| Model | 4k Ctx | 16k Ctx | 32k Ctx | 64k Ctx | 128k Ctx | 256k Ctx |
|---|---|---|---|---|---|---|
| Qwen3 8B (Q4_K) | 5,557.3 | 3,653.8 | 2,269.0 | 1,078.7 | — | — |
| Qwen3 14B (Q4_K) | 3,264.7 | 2,303.9 | 1,658.2 | — | — | — |
| gpt-oss 20B (MXFP4) | 6,178.3 | 4,940.7 | 3,903.5 | 2,644.9 | 1,363.7 | — |
| Model | 4k Ctx | 16k Ctx | 32k Ctx | 64k Ctx | 128k Ctx | 256k Ctx |
|---|---|---|---|---|---|---|
| Qwen3 8B (Q4_K) | 120.5 | 87.5 | 63.3 | 40.4 | — | — |
| Qwen3 14B (Q4_K) | 74.3 | 58.0 | 45.5 | — | — | — |
| gpt-oss 20B (MXFP4) | 156.0 | 133.1 | 115.9 | 91.3 | 66.6 | — |
Frequently Asked Questions
Common questions about running LLMs on the RTX 5070 Ti.
Does the RTX 5070 Ti support FP4?
Yes, the RTX 5070 Ti includes native hardware support for FP4. While our standard tests used 4-bit quantization, this feature allows for accelerated performance in specialized workflows.
Is the RTX 5070 Ti faster than the RTX 3090?
The RTX 5070 Ti is faster in prompt processing (2,304 t/s) and slower in token generation (58 t/s) compared to the RTX 3090. However, the RTX 3090 offers 24GB of VRAM compared to the 5070 Ti's 16GB.
What is the largest model I can run on the RTX 5070 Ti?
Due to the 16GB VRAM limit, the card maxes out at approximately 20B parameter models (such as gpt-oss 20B) for full offloading.
What are the memory specifications?
It features 16GB of GDDR7 memory with a bandwidth of 896 GB/s.