InternLM2.5 1.8B Chat on Intel Arc Pro B50

Can the Intel Arc Pro B50 run InternLM2.5 1.8B Chat?

54 pts

Yes, it runs well

Runs well. At Q8_0 it needs about 4.2 GB of 16.0 GB usable, with an estimated speed of 56.6 tok/s.

Best quant: Q8_0
Generation speed: 56.6 tok/s
Prompt processing: 4,045 tok/s
First token (1K prompt): 0.3 s
Largest safe context: 32K

Download InternLM2.5 1.8B Chat

Recommended for the Intel Arc Pro B50: Q8_0. Every other quantization has its own download link in the table below.

Quickest · Ollama

One command downloads a ready-to-run version and starts a chat.

ollama run internlm2:1.8b-chat-v2.5-q8_0

Get Ollama at ollama.com/download (opens in a new tab) · model page (opens in a new tab)

Quantized files · GGUF

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

Download the Q8_0 file (opens in a new tab)

huggingface.co/internlm/internlm2_5-1_8b-chat-gguf (opens in a new tab)

ollama run hf.co/internlm/internlm2_5-1_8b-chat-gguf:Q8_0

Original weights · Hugging Face

Full-precision files from Shanghai AI Lab, for fine-tuning, vLLM, Transformers.

huggingface.co/internlm/internlm2_5-1_8b-chat (opens in a new tab)

No sign-in needed.

Links checked 7 days ago against Hugging Face, Ollama and GitHub.

How the C 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.	8.1 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.	25.0 / 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.	6.1 / 15
Total	54.2 / 100	54 ptsUsable (C) · 54 of 100 points: Model quality 8.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 6.1/15

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

Every quantization on the Intel Arc Pro B50

Quant	Memory needed	Available	Speed	Fit	Grade · points	Download
`Q2_K`	3.0 GB	16.0 GB	183 tok/s	Runs well	49 ptsUsable (C) · 49 of 100 points: Model quality 5.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.3/15	GGUF (opens in a new tab)
`Q3_K_M`	3.1 GB	16.0 GB	144 tok/s	Runs well	51 ptsUsable (C) · 51 of 100 points: Model quality 6.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.5/15	GGUF (opens in a new tab)
`Q4_K_M`	3.4 GB	16.0 GB	111 tok/s	Runs well	52 ptsUsable (C) · 52 of 100 points: Model quality 7.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.8/15	GGUF (opens in a new tab)
`Q5_K_M`	3.5 GB	16.0 GB	91.8 tok/s	Runs well	52 ptsUsable (C) · 52 of 100 points: Model quality 7.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.1/15	GGUF (opens in a new tab)
`Q6_K`	3.8 GB	16.0 GB	77.1 tok/s	Runs well	53 ptsUsable (C) · 53 of 100 points: Model quality 8.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.4/15	GGUF (opens in a new tab)
`Q8_0`	4.2 GB	16.0 GB	56.6 tok/s	Runs well	54 ptsUsable (C) · 54 of 100 points: Model quality 8.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 6.1/15	GGUF (opens in a new tab)
`F16`	6.0 GB	16.0 GB	26.1 tok/s	Runs well	53 ptsUsable (C) · 53 of 100 points: Model quality 8.1/45, Memory fit 25.0/25, Speed 12.1/15, Memory use 8.6/15	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

63 ptsGood (B) · 63 of 100 points: Model quality 8.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4060 F16 · 41.4 tok/s
59 ptsGood (B) · 59 of 100 points: Model quality 8.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.1/15 Intel Arc B580 F16 · 53.1 tok/s
59 ptsGood (B) · 59 of 100 points: Model quality 8.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.1/15 NVIDIA GeForce RTX 3060 12GB F16 · 54.9 tok/s
59 ptsGood (B) · 59 of 100 points: Model quality 8.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.1/15 NVIDIA GeForce RTX 4070 SUPER F16 · 76.8 tok/s
56 ptsUsable (C) · 56 of 100 points: Model quality 8.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.6/15 AMD Radeon RX 9070 XT F16 · 84.0 tok/s
56 ptsUsable (C) · 56 of 100 points: Model quality 8.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.6/15 NVIDIA GeForce RTX 4060 Ti 16GB F16 · 43.9 tok/s

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.