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⇱ RTX 5070 TI Local LLM Benchmarks, Context Scaling & Supported Models 2026 – Hardware Corner

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RTX 5070 Ti LLM Performance

Local LLM Performance: 58.0 t/s average on 14B models at 16k context. Updated Benchmarks: March 2026.

Gen (14B 4-bit) 58.0 t/s
PP (14B 4-bit) 2,304 t/s
Max Model 20B
VRAM
16 GB GDDR7
Bandwidth 896 GB/s
Token Gen (14B @ 4k Ctx)

58.0T/s

Prompt Proc (14B @ 4k Ctx)

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

Capable of running gpt-oss 20B (MXFP4) with full 128k context support completely in VRAM.
Features hardware-accelerated FP4 support, allowing for fast speeds with NVFP4 qunatizaion.
Utilizes GDDR7 memory (896 GB/s bandwidth) to achieve prompt processing speeds exceeding 2,300 t/s.
Excellent scaling in dual-GPU configurations, making it a top tier choice for Qwen3.5 agentic workflows despite the 16GB limit per card.

Current Price in US

$916

Avg. Market Value

Current Pricing

Hardware Specs
VRAM 16GB GDDR7
Capable of running 20B model
Bandwidth 896 GB/s
Architecture Blackwell
Memory speed 28 Gbps
Memory bus 256 bit
TDP 300 W
Suggested PSU 750 W
Price/GB VRAM $57.25
Price/(t/s) with 14B @ 16k $15.80

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.

gpt-oss 20B (MXFP4) Max 128k
Token Generation 66.6 t/s @ 128k context
Prompt Processing 1,363.7 t/s @ 128k context
Qwen3 14B (Q4_K) Max 32k
Token Generation 45.5 t/s @ 32k context
Prompt Processing 1,658.2 t/s @ 32k context
Qwen3 8B (Q4_K) Max 64k
Token Generation 40.4 t/s @ 64k context
Prompt Processing 1,078.7 t/s @ 64k context

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.

Prompt Processing
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 —
Token Generation
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.