Qwen3.5-27B Hits 207 Tokens/s on RTX 3090 Benchmark

Qwen3.5-27B RTX 3090 benchmark hits 207 tokens/s using 4-bit quantization. This $700 used GPU enables gamers and pros to run 27B AI models locally, slashing cloud costs.

Qwen3.5-27B RTX 3090 hits 207 tokens/s with 4-bit quantization.
Used RTX 3090 at $700 USD fits 27B models in 24GB VRAM.
Outperforms cloud AI costs by 90% for gamers and pros.

Qwen3.5-27B RTX 3090 Benchmark

Qwen3.5-27B RTX 3090 setup delivers 207 tokens per second on a single NVIDIA RTX 3090 GPU using 4-bit quantization and vLLM engine. Alibaba's open-source model fits 24GB GDDR6X VRAM. NVIDIA Developer Blog states Ampere GPUs accelerate inference up to 6x. PCNewsDigest verified results against QwenLM GitHub reports.

Gamers deploy local AI for mods. IT professionals cut cloud bills by 90%. Qwen3.5-27B excels in coding and chat benchmarks.

Detailed Benchmark Methodology

QwenLM GitHub community quantizes Qwen3.5-27B to 4-bit to fit RTX 3090's 24GB VRAM. vLLM serves efficiently. Test rig: Intel Core i9-13900K, 64GB DDR5-6000 RAM, Windows 11 Pro. Prompts average 2048 tokens, batch size 32.

RTX 3090 draws 350W TDP under load. ASUS TUF cooler hits 72°C max. No overclock yields 207 tokens/s. Hugging Face users report 1.2 seconds per 100 tokens for Python code. Chat latency under 500ms.

RTX 3090 Price-Performance vs. Newer GPUs

Qwen3.5-27B RTX 3090 delivers 207 tokens/s. RTX 4090 reaches 350 tokens/s per vLLM docs. RTX 5090 projections exceed 500 tokens/s on 32GB GDDR7.

Used RTX 3090 averages $700 USD on eBay (October 2024), down from $1500 MSRP. RTX 4090: $1600 USD. RTX 5090: near $2000 USD. 24GB VRAM edges 27B models.

GPU Model: RTX 3090 · VRAM: 24GB · Tokens/s (Qwen3.5-27B): 207 · TDP (W): 350 · Used Price (USD): 700
GPU Model: RTX 4090 · VRAM: 24GB · Tokens/s (Qwen3.5-27B): 350 · TDP (W): 450 · Used Price (USD): 1600
GPU Model: RTX 5090 · VRAM: 32GB · Tokens/s (Qwen3.5-27B): 500+ (est.) · TDP (W): 600 · Used Price (USD): 2000+ (est.)

Table aggregates Hugging Face benchmarks and vLLM GitHub issues. NVIDIA Ampere sales boost Q4 2024 revenue 15%, per Jon Peddie Research.

Financial Analysis: NVIDIA and Used GPU Market

RTX 3090 AI demand surges 40% year-over-year, per eBay Terapeak data. NVIDIA (NVDA) gains from consumer repurposing amid datacenter shortages. Alibaba Qwen undercuts OpenAI by 80% locally.

TSMC 5nm yields aid 3090 efficiency. AMD RX 7900 XTX: 150 tokens/s, lacks CUDA. Intel Arc A770: 120 tokens/s max.

RTX 3090: $3.38 per tokens/s vs. $4.57 for 4090 (used prices).

Gaming Applications and Real-World Gains

Gamers use Qwen3.5-27B RTX 3090 for Cyberpunk 2077 and Starfield mods. 207 tokens/s enables real-time NPC dialogue at 1440p 120 FPS with DLSS 3.

Esports teams analyze replays offline. Ollama deploys fast. Reddit r/MachineLearning confirms 99% uptime over 48 hours.

Local saves $50/month vs. Grok API (5 cents/1K tokens).

Professional Workloads and Cost Savings

Developers prototype with Qwen3.5-27B RTX 3090, skip AWS fees. IT automates scripting; costs drop to 0.1 cents/million tokens.

NVLink two 3090s: 400+ tokens/s per vLLM docs. Windows Copilot+ aids enterprise AI.

Enterprises favor local for security, per Krebs on Security breach reports.

Step-by-Step Setup for Qwen3.5-27B RTX 3090

1. Download from Hugging Face repo. 2. Install CUDA 12.4 from NVIDIA. 3. `pip install vllm`. 4. Quantize Q4_K_M: `vllm serve Qwen/Qwen3.5-27B --quantization q4 --gpu-memory-utilization 0.95`. 5. Batch 32, monitor via MSI Afterburner.

Ubuntu 24.04 loads 5% faster than Windows. 128GB RAM for 8192 tokens.

Future Outlook for Qwen3.5-27B RTX 3090

RTX 3090 viable to 2027 with Qwen optimizations. RTX 5090 Blackwell doubles speeds for 4K AI-gaming.

Four 3090s ($2800) rival A100 rentals ($2/hour). Local AI boosts NVIDIA's $3T cap. Qwen3.5-27B RTX 3090 proves value.

Frequently Asked Questions

What is Qwen3.5-27B RTX 3090 benchmark speed?

Benchmark reaches 207 tokens/s on RTX 3090. 4-bit quantization fits the 27B model in 24GB VRAM. vLLM framework enables this rate.

How to run Qwen3.5-27B on RTX 3090?

Install CUDA 12.4 and vLLM. Quantize to Q4 and serve with batch size 32. Pairs with Core i9 CPU and 64GB RAM.

Can gamers use RTX 3090 for AI inference?

RTX 3090 supports local LLMs at 207 tokens/s for mods and upscaling. Handles 1440p gaming alongside inference without issues.

Does Qwen3.5-27B RTX 3090 beat cloud AI?

Local runs avoid latency and costs. 27B model rivals GPT-4 in tasks. Edge deployment suits pros and gamers.

Qwen3.5-27B RTX 3090 Delivers 207 Tokens/s in Local AI Inference Benchmarks