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Can the NVIDIA GeForce RTX 5090 run Ornith 1.5 35B-A3B?

94 ptsExcellent (S) · 94 of 100 points: Model quality 40.1/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, with little memory to spare

Tight fit. At Q6_K it needs about 31.8 GB of 32.0 GB usable, with an estimated speed of 254 tok/s.

Best quant
Q6_K
Generation speed
254 tok/s
Prompt processing
25,152 tok/s
First token (1K prompt)
0.3 s
Largest safe context
15K

Download Ornith 1.5 35B-A3B

Recommended for the NVIDIA GeForce RTX 5090: Q6_K. Every other quantization has its own download link in the table below.

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

Download the Q6_K file (opens in a new tab)

huggingface.co/ornith-ai/Ornith-1.5-35B-A3B-GGUF (opens in a new tab)

ollama run hf.co/ornith-ai/Ornith-1.5-35B-A3B-GGUF:Q6_K

Original weights · Hugging Face

Full-precision files from DeepReinforce, for fine-tuning, vLLM, Transformers.

huggingface.co/ornith-ai/Ornith-1.5-35B-A3B (opens in a new tab)

No sign-in needed.

Links checked 6 days ago against Hugging Face, Ollama and GitHub.

How the S grade is scored

Every result gets up to 100 points from four parts. The points decide the letter grade.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.40.1 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.24.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.15.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.15.0 / 15
Total94.1 / 10094 ptsExcellent (S) · 94 of 100 points: Model quality 40.1/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every quantization on the NVIDIA GeForce RTX 5090

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 16.7 GB 32.0 GB 602 tok/s Runs well 80 ptsGreat (A) · 80 of 100 points: Model quality 28.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.1/15 GGUF files (opens in a new tab)
Q3_K_M 20.0 GB 32.0 GB 474 tok/s Runs well 88 ptsExcellent (S) · 88 of 100 points: Model quality 34.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.4/15 GGUF files (opens in a new tab)
Q4_K_M 24.3 GB 32.0 GB 367 tok/s Runs well 93 ptsExcellent (S) · 93 of 100 points: Model quality 38.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q5_K_M 27.9 GB 32.0 GB 303 tok/s Tight fit 93 ptsExcellent (S) · 93 of 100 points: Model quality 39.3/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q6_K 31.8 GB 32.0 GB 254 tok/s Tight fit 94 ptsExcellent (S) · 94 of 100 points: Model quality 40.1/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q8_0 40.5 GB 32.0 GB 27.6 tok/s Runs with offload 77 ptsGreat (A) · 77 of 100 points: Model quality 40.5/45, Memory fit 10.0/25, Speed 12.5/15, Memory use 15.0/15 GGUF (opens in a new tab)
F16 74.3 GB 32.0 GB — Won't run 12 ptsWon't run (F) · 12 of 100 points: Model quality 12.2/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF (opens in a new tab) Original weights (opens in a new tab)

Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.

Other hardware that runs it

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.