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⇱ RTX 3090 TI Local LLM Benchmarks, Context Scaling & Supported Models 2026 – Hardware Corner

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RTX 3090 Ti LLM Performance

Local LLM Performance: 56.9 t/s average on 14B models at 16k context.

Gen (14B 4-bit) 56.9 t/s
PP (14B 4-bit) 1,915 t/s
Max Model 32B
VRAM
24 GB GDDR6X
Bandwidth 1,008 GB/s
Token Gen (14B @ 4k Ctx)

56.9T/s

Prompt Proc (14B @ 4k Ctx)

1,915T/s

Summary

Even in 2026, we find the NVIDIA RTX 3090 Ti remains an enthusiast-class GPU for local LLM workloads, boasting an impressive 1,008 GB/s bandwidth. In our testing, its 24GB of VRAM allowed us to comfortably run Qwen3 32B models at 32.6 tokens per second, and we achieved massive 128k context windows with the gpt-oss 20B model. However, priced around $1000, we observed that the performance difference between this and the standard RTX 3090 is often negligible, making the Ti variant a harder sell if the base model is available for less.

Key Insights

Capable of running Qwen3 32B using GGUF (Q4_K) completely in VRAM with 16k context.
Features a massive 1,008 GB/s memory bandwidth, delivering 1,915 t/s prompt processing on 14B models.
Handles gpt-oss 20B model in MXFP4 quantization at a full 128K context window.
Offers negligible performance gains over the standard RTX 3090 despite the higher price point.

Current Price in US

$900

Avg. Market Value

Current Pricing

Hardware Specs
VRAM 24GB GDDR6X
Capable of running 32B model
Bandwidth 1,008 GB/s
Architecture Ampere
Memory speed 21 Gbps
Memory bus 384 bit
TDP 450 W
Suggested PSU 850 W
Price/GB VRAM $37.50
Price/(t/s) with 14B @ 16k $15.82

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 32B (Q4_K) Max 16k
Token Generation 32.6 t/s @ 16k context
Prompt Processing 862.7 t/s @ 16k context
Qwen3 30B A3B (Q4_K) Max 32k
Token Generation 92.0 t/s @ 32k context
Prompt Processing 1,483.9 t/s @ 32k context
gpt-oss 20B (MXFP4) Max 128k
Token Generation 61.5 t/s @ 128k context
Prompt Processing 936.4 t/s @ 128k 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 3090 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) 4,467.9 2,834.2 1,868.0 1,111.1 612.4 —
Qwen3 14B (Q4_K) 2,817.1 1,914.8 1,232.1 828.5 — —
gpt-oss 20B (MXFP4) 4,805.4 3,440.1 2,521.3 1,666.5 936.4 —
Qwen3 30B A3B (Q4_K) 3,441.0 2,205.6 1,483.9 — — —
Qwen3 32B (Q4_K) 1,238.8 862.7 — — — —
Token Generation
Model 4k Ctx 16k Ctx 32k Ctx 64k Ctx 128k Ctx 256k Ctx
Qwen3 8B (Q4_K) 123.7 93.6 71.8 49.0 29.0 —
Qwen3 14B (Q4_K) 76.2 56.9 42.1 28.2 — —
gpt-oss 20B (MXFP4) 160.3 137.6 119.7 94.9 61.5 —
Qwen3 30B A3B (Q4_K) 166.9 121.9 92.0 — — —
Qwen3 32B (Q4_K) 38.0 32.6 — — — —

Frequently Asked Questions

Common questions about running LLMs on the RTX 3090 Ti.