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⇱ RTX 4070 TI Local LLM Benchmarks, Context Scaling & Supported Models 2026 – Hardware Corner

Tier 1 Enthusiast

RTX 4070 Ti LLM Performance

Local LLM Performance: 37.8 t/s average on 14B models at 16k context.

Gen (14B 4-bit) 37.8 t/s
PP (14B 4-bit) 1,951 t/s
Max Model 14B
VRAM
12 GB GDDR6X
Bandwidth 504 GB/s
Token Gen (14B @ 4k Ctx)

37.8T/s

Prompt Proc (14B @ 4k Ctx)

1,951T/s

Summary

In our testing, we found the RTX 4070 Ti to be a high-performance card crippled by its memory capacity. While it is measurably faster than the RTX 4070 SUPER—particularly in prompt processing where we saw speeds approach 2,000 t/s—we believe it sits in the same awkward market position regarding value. At the current price, paying for only 12GB of VRAM limits you to 14B models, making it difficult for us to recommend over 16GB alternatives that offer much better longevity and model support for the price.

Key Insights

Capable of running Qwen3 14B using GGUF (Q4_K) completely in VRAM.
Outperforms the RTX 4070 SUPER in prompt processing, achieving 1,951 t/s.
Delivers consistent token generation speeds of 37.8 t/s on 14B models at 16k context.
Suffers from a poor price-to-VRAM ratio, making it a questionable value for LLMs despite the speed.

Current Price in US

$550

Avg. Market Value

Current Pricing

Hardware Specs
VRAM 12GB GDDR6X
Capable of running 14B model
Bandwidth 504 GB/s
Architecture Ada Lovelace
Memory speed 21 Gbps
Memory bus 192 bit
TDP 285 W
Suggested PSU 700 W
Price/GB VRAM $45.83
Price/(t/s) with 14B @ 16k $14.57

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.

Qwen3 14B (Q4_K) Max 16k
Token Generation 37.8 t/s @ 16k context
Prompt Processing 1,951.4 t/s @ 16k context
Qwen3 8B (Q4_K) Max 32k
Token Generation 42.1 t/s @ 32k context
Prompt Processing 1,099.7 t/s @ 32k 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 4070 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) 4,877.7 2,274.8 1,099.7 — — —
Qwen3 14B (Q4_K) 2,866.6 1,951.4 — — — —
Token Generation
Model 4k Ctx 16k Ctx 32k Ctx 64k Ctx 128k Ctx 256k Ctx
Qwen3 8B (Q4_K) 75.8 57.6 42.1 — — —
Qwen3 14B (Q4_K) 45.8 37.8 — — — —

Frequently Asked Questions

Common questions about running LLMs on the RTX 4070 Ti.