RTX 3090 LLM benchmark

Community folklore on RTX 3090

181 unverified claims extracted from Reddit/HN comments. Lower trust than signed runs above; every row links to the source.

• communityconfidence 85%

  10.00tok/s — qwen-2.5-32B on RTX 3090 via ollama Q8

  our signed data: RTX 3090 · qwen-2.5-32B

  “a beast! 28 tok/sec at 32K context is more than usable for a lot of coding situations. * The P40s continue to surprise. A single P40 can do 10 tok/sec, which is perfectly usable. * 3xP40 fits 120K context at Q8 comfortably. * performance doesn't scale with more P40s. Using `-sm r…”

  source: Reddit · u/No-Statement-0001 · 2024-11-11

• communityconfidence 85%

  28.00tok/s — qwen-2.5-32B on RTX 3090 via ollama Q8

  our signed data: RTX 3090 · qwen-2.5-32B

  “ase of qwen-2.5-32B today. I bench marked the Q4 and Q8 quants on my local rig (3xP40, 1x3090). Some observations: * the 3090 is a beast! 28 tok/sec at 32K context is more than usable for a lot of coding situations. * The P40s continue to surprise. A single P40 can do 10 tok/se…”

  source: Reddit · u/No-Statement-0001 · 2024-11-11

• communityconfidence 85%

  65.00tok/s — Qwen3-Coder-Next on RTX 3090 via vllm FP8

  our signed data: RTX 3090 · Qwen3-Coder-Next

  “Next-FP8-Dynamic quant with vLLM v0.16.0 over 4 RTX 3090s with a 200k context window. I get around 71tps at low context, dropping to around 65tps at the 100k context point. Something to note, I'm seeing pretty bad issues with vLLM nightly, affecting this model especially, that c…”

  source: Reddit · u/rmhubbert · 2026-03-04

• communityconfidence 85%

  71.00tok/s — Qwen3-Coder-Next on RTX 3090 via vllm FP8

  our signed data: RTX 3090 · Qwen3-Coder-Next

  “sted. I'm running Unsloth's Qwen3-Coder-Next-FP8-Dynamic quant with vLLM v0.16.0 over 4 RTX 3090s with a 200k context window. I get around 71tps at low context, dropping to around 65tps at the 100k context point. Something to note, I'm seeing pretty bad issues with vLLM nightly…”

  source: Reddit · u/rmhubbert · 2026-03-04

• communityconfidence 85%

  150.0tok/s — Qwen3-Coder on RTX 3090 via vllm FP16

  our signed data: RTX 3090 · Qwen3-Coder

  “addition vRAM for a large enough context window for it to be useful for coding. For reference I’m able to run Qwen3-Coder-30B-A3B at Q8 at 150tok/s with a context window of 128k (FP16 KV) on dual 3090s. When using extensions like Cline you really need a large context window to b…”

  source: Reddit · u/Tyme4Trouble · 2025-08-05

• communityconfidence 75%

  12.88tok/s — Llama 3.1 8B on RTX 3090 via vllm fp16

  our signed data: RTX 3090 · Llama 3.1 8B

  “rve Llama 3 to thousands of users Benchmarking Llama 3.1 8B (fp16) with vLLM at 100 concurrent requests gets a worst case (p99) latency of 12.88 tokens/s. That's an effective total of over 1300 tokens/s. Note that this used a low token prompt. See more details in the Backprop v…”

  source: Reddit · u/ojasaar · 2024-08-16

• communityconfidence 75%

  21.00tok/s — llama 3 70b on RTX 3090 via vllm q4

  our signed data: RTX 3090 · llama 3 70b

  “ut 16.95 t/s With **vLLM** I get Avg generation throughput: 21.2 tokens/s so I'm super happy. I managed to run **MLC** and get about 20-21t/s so for me not worth the hassle. Since I'm from Europe where electricity prices are high I love 25% increase in performance vLLM over…”

  source: Reddit · u/koibKop4 · 2024-06-01

• communityconfidence 75%

  23.80tok/s — mistral-large on RTX 3090 via sglang AWQ

  our signed data: RTX 3090 · mistral-large

  “|vLLM (baseline)|Q4 AWQ|Gemma 12B|1×2000 Ada|70W|20–21 tok/s|Baseline| |SGLang (AWQ + Torch.compile)|Q4 AWQ|Gemma 12B|1×2000 Ada|70W|**23.4–23.8 tok/s**|\+15–18%| my 4x3090 Config: sglang serve /models/mistral-large-awq \ --tensor-parallel-size 4 \ --enable-cuda…”

  source: Reddit · u/darkmaniac7 · 2025-10-15

• communityconfidence 75%

  21.00tok/s — mistral-large on RTX 3090 via sglang AWQ

  our signed data: RTX 3090 · mistral-large

  “(NVLink + Torch.compile)|8-bit|KAT-Dev 32B|4×3090|300W|**61.5 tok/s**|\+66% vs Mistral| |vLLM (baseline)|Q4 AWQ|Gemma 12B|1×2000 Ada|70W|20–21 tok/s|Baseline| |SGLang (AWQ + Torch.compile)|Q4 AWQ|Gemma 12B|1×2000 Ada|70W|**23.4–23.8 tok/s**|\+15–18%| my 4x3090 Config: sglan…”

  source: Reddit · u/darkmaniac7 · 2025-10-15

• communityconfidence 75%

  61.50tok/s — mistral-large on RTX 3090 via vllm AWQ

  our signed data: RTX 3090 · mistral-large

  “NVLink + Torch.compile)|Q4 AWQ|Mistral 123B|4×3090|320W|37.1 tok/s|\+209%| |SGLang (NVLink + Torch.compile)|8-bit|KAT-Dev 32B|4×3090|300W|**61.5 tok/s**|\+66% vs Mistral| |vLLM (baseline)|Q4 AWQ|Gemma 12B|1×2000 Ada|70W|20–21 tok/s|Baseline| |SGLang (AWQ + Torch.compile)|Q4 AWQ|G…”

  source: Reddit · u/darkmaniac7 · 2025-10-15

See all 181 claims for RTX 3090 →

Which models can an RTX 3090 run?

Fastest decode speed for each model on this hardware, from llm-speed's own runs and community-submitted runs. Each page lists every quant and runtime and labels which runs llm-speed measured.

• gpt-oss-20b · 207.2 tok/s
• Qwen3-Coder 30B-A3B · 199.7 tok/s
• glm-4.7-flash 29.9B · 134.6 tok/s
• Flint 40B-A2.5B · 130.8 tok/s at 8K context
• Qwen3.8 27B · 38.8 tok/s at 8K context
• Qwen3 32B · 38.5 tok/s
• DeepSeek-Coder-V2-Lite 16B · 189.5 tok/s
• Llama-3.1 8B · 136.2 tok/s
• Nemotron 3.5 Bolt 74B-A9B · 87.8 tok/s at 4K context
• Gemma 3 12B · 78.7 tok/s

Models measured on RTX 3090

• Qwen3.8-27B-ctx8k benchmarks
• Qwen3.8-27B-ctx16k benchmarks
• Qwen3.8-27B-ctx4k benchmarks
• Flint-40B-A2.5B-UD-cpumoe6-ctx8k benchmarks
• Flint-40B-A2.5B-UD-ctx16k benchmarks
• Flint-40B-A2.5B-UD-ctx8k benchmarks
• Qwen2.5-Coder-14B-Instruct benchmarks
• Qwen3-Coder-30B-A3B-Instruct benchmarks
• gpt-oss-20b benchmarks
• Qwen3.6-27B benchmarks
• Qwen3-32B benchmarks
• gemma3 benchmarks
• glm-4.7-flash benchmarks
• Nemotron-3.5-Bolt-74B-A9B-24GB-ctx8k benchmarks
• Nemotron-3.5-Bolt-74B-A9B-24GB benchmarks
• Qwen3.8-27B benchmarks
• coder-v2 benchmarks
• qwen2.5-coder benchmarks
• llama3.1 benchmarks

Compare RTX 3090 head-to-head

• RTX 5090 vs RTX 3090
• RTX 4090 vs RTX 3090