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

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RTX 4070 LLM Performance

Local LLM Performance: 32.7 t/s average on 14B models at 16k context. Updated Benchmarks: March 2026.

Gen (14B 4-bit) 32.7 t/s
PP (14B 4-bit) 1,356 t/s
Max Model 14B
VRAM
12 GB GDDR6X
Bandwidth 504 GB/s
Token Gen (14B @ 4k Ctx)

32.7T/s

Prompt Proc (14B @ 4k Ctx)

1,356T/s

Summary

In our 2026 testing, we found the RTX 4070 occupies a difficult spot for local LLM enthusiasts. While the card demonstrates excellent raw speed—achieving nearly 33 t/s on Qwen3 14B thanks to its GDDR6X memory—the 12GB VRAM limitation restricts usability to smaller models. Despite the performance metrics, we believe the price point makes it less attractive compared to 16GB alternatives like the RTX 4060 Ti or RTX 5060 Ti, which offer similar inference speeds but significantly more room for larger models or longer contexts.

Key Insights

Capable of running Qwen3 14B using GGUF (Q4_K) completely in VRAM.
Achieves generation speeds of 32.7 t/s on 14B models at 16k context.
Delivers prompt processing at 1,356 t/s due to 504 GB/s GDDR6X bandwidth.
Limited to a maximum model size of 14B parameters due to the 12GB VRAM cap.

Current Price in US

$450

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 200 W
Suggested PSU 650 W
Price/GB VRAM $37.50
Price/(t/s) with 14B @ 16k $13.78

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 32.7 t/s @ 16k context
Prompt Processing 1,355.8 t/s @ 16k context
Qwen3 8B (Q4_K) Max 32k
Token Generation 38.1 t/s @ 32k context
Prompt Processing 1,116.7 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 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) 3,564.1 2,064.3 1,116.7 — — —
Qwen3 14B (Q4_K) 2,099.9 1,355.8 — — — —
Token Generation
Model 4k Ctx 16k Ctx 32k Ctx 64k Ctx 128k Ctx 256k Ctx
Qwen3 8B (Q4_K) 71.2 52.1 38.1 — — —
Qwen3 14B (Q4_K) 42.5 32.7 — — — —

Frequently Asked Questions

Common questions about running LLMs on the RTX 4070.