LFM2.5 2.6B on NVIDIA GeForce RTX 3050 Ti Laptop GPU
Can the NVIDIA GeForce RTX 3050 Ti Laptop GPU run LFM2.5 2.6B?
Yes, it runs well
Runs well. At Q6_K it needs about 3.1 GB of 4.0 GB usable, with an estimated speed of 60.6 tok/s.
- Best quant
Q6_K- Generation speed
- 60.6 tok/s
- Prompt processing
- 1,413 tok/s
- First token (1K prompt)
- 0.7 s
- Largest safe context
- 58K
Download LFM2.5 2.6B
Recommended for the NVIDIA GeForce RTX 3050 Ti Laptop GPU: 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/LiquidAI/LFM2.5-2.6B-GGUF (opens in a new tab)
ollama run hf.co/LiquidAI/LFM2.5-2.6B-GGUF:Q6_KOriginal weights · Hugging Face
Full-precision files from Liquid AI, for fine-tuning, vLLM, Transformers.
Official repo · GitHub
Reference code, inference scripts and docs from Liquid AI. The weights themselves download from Hugging Face.
github.com/Liquid4All/cookbook (opens in a new tab)
git clone https://github.com/Liquid4All/cookbookHow the A grade is scored
Every result gets up to 100 points from four parts. The points decide the letter grade.
| Model quality | 19.6 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 15.0 / 15 | |
| Memory use | 15.0 / 15 | |
| Total | 74.6 / 100 | 74 ptsGreat (A) · 74 of 100 points: Model quality 19.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 |
Every quantization on the NVIDIA GeForce RTX 3050 Ti Laptop GPU
| Quant | Memory needed | Available | Speed | Fit | Grade · points | Download |
|---|---|---|---|---|---|---|
Q2_K | 2.0 GB | 4.0 GB | 143 tok/s | Runs well | 65 ptsGood (B) · 65 of 100 points: Model quality 13.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.6/15 | GGUF files (opens in a new tab) |
Q3_K_M | 2.3 GB | 4.0 GB | 113 tok/s | Runs well | 69 ptsGood (B) · 69 of 100 points: Model quality 16.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.0/15 | GGUF files (opens in a new tab) |
Q4_K_M | 2.6 GB | 4.0 GB | 87.3 tok/s | Runs well | 73 ptsGreat (A) · 73 of 100 points: Model quality 18.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.9/15 | GGUF (opens in a new tab) |
Q5_K_M | 2.9 GB | 4.0 GB | 72.1 tok/s | Runs well | 74 ptsGreat (A) · 74 of 100 points: Model quality 19.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 | GGUF (opens in a new tab) |
Q6_K | 3.1 GB | 4.0 GB | 60.6 tok/s | Runs well | 74 ptsGreat (A) · 74 of 100 points: Model quality 19.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 | GGUF (opens in a new tab) |
Q8_0 | 3.8 GB | 4.0 GB | 44.4 tok/s | Tight fit | 73 ptsGreat (A) · 73 of 100 points: Model quality 19.8/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 | GGUF (opens in a new tab) |
F16 | 6.3 GB | 4.0 GB | 11.3 tok/s | Heavy offload | 46 ptsUsable (C) · 46 of 100 points: Model quality 19.8/45, Memory fit 4.0/25, Speed 8.0/15, Memory use 15.0/15 | 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
- 72 ptsGreat (A) · 72 of 100 points: Model quality 19.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.0/15 NVIDIA GeForce RTX 4070 SUPER
- 71 ptsGood (B) · 71 of 100 points: Model quality 19.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.5/15 NVIDIA GeForce RTX 4060
- 69 ptsGood (B) · 69 of 100 points: Model quality 19.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.0/15 AMD Radeon RX 9070 XT
- 69 ptsGood (B) · 69 of 100 points: Model quality 19.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.0/15 NVIDIA GeForce RTX 4070 Ti SUPER
- 69 ptsGood (B) · 69 of 100 points: Model quality 19.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.0/15 NVIDIA GeForce RTX 4080 SUPER
- 69 ptsGood (B) · 69 of 100 points: Model quality 19.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.0/15 NVIDIA GeForce RTX 5060 Ti 16GB
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.