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root@server1:~# ollama list
NAME                       ID              SIZE      MODIFIED
gemma3:12b                 f4031aab637d    8.1 GB    19 minutes ago
gemma3:4b  

systemctl stop ollama.service
source llm_env/bin/activate
pip install --pre --upgrade ipex-llm[cpp]
cd llama-cpp
# Run Ollama Serve with Intel GPU
export OLLAMA_NUM_GPU=999
export OLLAMA_THREADS=22
export OMP_NUM_THREADS=22
export ZES_ENABLE_SYSMAN=1
export no_proxy=localhost,127.0.0.1
source /opt/intel/oneapi/setvars.sh
export SYCL_CACHE_PERSISTENT=1
OLLAMA_HOST=0.0.0.0 ./ollama serve

# CTRL + C
systemctl start ollama.service

IPv4 address for enp171s0: 10.9.9.108

 * Strictly confined Kubernetes makes edge and IoT secure. Learn how MicroK
   just raised the bar for easy, resilient and secure K8s cluster deploymen

   https://ubuntu.com/engage/secure-kubernetes-at-the-edge

Expanded Security Maintenance for Applications is not enabled.

0 updates can be applied immediately.

Enable ESM Apps to receive additional future security updates.
See https://ubuntu.com/esm or run: sudo pro status


Last login: Wed May 21 11:27:11 2025 from 10.9.9.64
oliutyi@server1:~$ sudo su -
(base) root@server1:~# cd ollama-benchmark/
(base) root@server1:~/ollama-benchmark# ls -la
total 32
drwxr-xr-x  3 root root 4096 May 21 11:25  .
drwx------ 27 root root 4096 May 21 12:04  ..
-rwxr-xr-x  1 root root 2815 May 21 11:25  batch-obench.sh
drwxr-xr-x  8 root root 4096 May 20 17:47  .git
-rw-r--r--  1 root root   73 May 21 12:02 'Intel(R) Core(TM) Ultra 9 185H'$Filled By O.E.M. CPU @ 4.4GHz.txt'
-rw-r--r--  1 root root 1061 May 20 17:47  LICENSE
-rwxr-xr-x  1 root root 2697 May 20 17:47  obench.sh
-rw-r--r--  1 root root  333 May 20 17:47  README.md
(base) root@server1:~/ollama-benchmark# cat 'Intel(R) Core(TM) Ultra 9 185He Filled By O.E.M. CPU @ 4.4GHz.txt'

prompt eval rate:     5.50 tokens/s
eval rate:            2.31 tokens/s
(base) root@server1:~/ollama-benchmark# vi batch-obench.sh
(base) root@server1:~/ollama-benchmark# ./batch-obench.sh
Setting cpu governor to
performance

Simple benchmark using ollama and
whatever local Model is installed.
Does not identify if Meteor Lake-P [Intel Arc Graphics] is benchmarking

How many times to run the benchmark?
3

Total runs 3


dolphin-phi:2.7b
You are Dolphin, a helpful AI assistant.
Will use model: dolphin-phi:2.7b

Will benchmark the tokens per second for Intel(R) Core(TM) Ultra 9 185H Inty O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]


Running benchmark 3 times for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(U @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]
with performance setting for cpu governor

prompt eval rate:     85.67 tokens/s
eval rate:            25.11 tokens/s
prompt eval rate:     744.07 tokens/s
eval rate:            25.42 tokens/s
prompt eval rate:     783.71 tokens/s
eval rate:            25.85 tokens/s

2.31 is the average tokens per second using dolphin-phi:2.7b model
for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filake-P [Intel Arc Graphics]
Total runs 3


dolphin3:8b
You are Dolphin, a helpful AI assistant.
Will use model: dolphin3:8b

Will benchmark the tokens per second for Intel(R) Core(TM) Ultra 9 185H Inty O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]


Running benchmark 3 times for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(U @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]
with performance setting for cpu governor

prompt eval rate:     26.04 tokens/s
eval rate:            10.87 tokens/s
prompt eval rate:     325.85 tokens/s
eval rate:            10.76 tokens/s
prompt eval rate:     323.77 tokens/s
eval rate:            10.75 tokens/s

2.31 is the average tokens per second using dolphin3:8b model
for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filake-P [Intel Arc Graphics]
Total runs 3


tinyllama:1.1b
You are a helpful AI assistant.
Will use model: tinyllama:1.1b

Will benchmark the tokens per second for Intel(R) Core(TM) Ultra 9 185H Inty O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]


Running benchmark 3 times for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(U @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]
with performance setting for cpu governor

prompt eval rate:     198.18 tokens/s
eval rate:            63.49 tokens/s
prompt eval rate:     2595.12 tokens/s
eval rate:            62.99 tokens/s
prompt eval rate:     2547.80 tokens/s
eval rate:            62.73 tokens/s

2.31 is the average tokens per second using tinyllama:1.1b model
for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filake-P [Intel Arc Graphics]
Total runs 3


deepseek-v2:16b

Will use model: deepseek-v2:16b

Will benchmark the tokens per second for Intel(R) Core(TM) Ultra 9 185H Inty O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]


Running benchmark 3 times for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(U @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]
with performance setting for cpu governor

prompt eval rate:     59.47 tokens/s
eval rate:            24.57 tokens/s
prompt eval rate:     361.51 tokens/s
eval rate:            24.39 tokens/s
prompt eval rate:     361.58 tokens/s
eval rate:            24.32 tokens/s

2.31 is the average tokens per second using deepseek-v2:16b model
for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filake-P [Intel Arc Graphics]
Total runs 3


phi3:14b

Will use model: phi3:14b

Will benchmark the tokens per second for Intel(R) Core(TM) Ultra 9 185H Inty O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]


Running benchmark 3 times for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(U @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]
with performance setting for cpu governor

prompt eval rate:     15.60 tokens/s
eval rate:            5.97 tokens/s
prompt eval rate:     101.53 tokens/s
eval rate:            6.20 tokens/s
prompt eval rate:     98.60 tokens/s
eval rate:            6.07 tokens/s

2.31 is the average tokens per second using phi3:14b model
for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filake-P [Intel Arc Graphics]
Total runs 3


llama3.3:70b

Will use model: llama3.3:70b

Will benchmark the tokens per second for Intel(R) Core(TM) Ultra 9 185H Inty O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]


Running benchmark 3 times for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(U @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]
with performance setting for cpu governor

prompt eval rate:     2.60 tokens/s
eval rate:            1.25 tokens/s
prompt eval rate:     21.35 tokens/s
eval rate:            1.25 tokens/s
prompt eval rate:     21.34 tokens/s
eval rate:            1.25 tokens/s

2.31 is the average tokens per second using llama3.3:70b model
for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]
Total runs 3


mistral-small3.1:24b
You are Mistral Small 3.1, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris.
You power an AI assistant called Le Chat.
Your knowledge base was last updated on 2023-10-01.

When you're not sure about some information, you say that you don't have the information and don't make up anything.
If the user's question is not clear, ambiguous, or does not provide enough context for you to accurately answer the question, you do not try to answer it right away and you rather ask the user to clarify their request (e.g. "What are some good restaurants around me?" => "Where are you?" or "When is the next flight to Tokyo" => "Where do you travel from?").
You are always very attentive to dates, in particular you try to resolve dates (e.g. "yesterday" is {yesterday}) and when asked about information at specific dates, you discard information that is at another date.
You follow these instructions in all languages, and always respond to the user in the language they use or request.
Next sections describe the capabilities that you have.

# WEB BROWSING INSTRUCTIONS

You cannot perform any web search or access internet to open URLs, links etc. If it seems like the user is expecting you to do so, you clarify the situation and ask the user to copy paste the text directly in the chat.

# MULTI-MODAL INSTRUCTIONS

You have the ability to read images, but you cannot generate images. You also cannot transcribe audio files or videos.
You cannot read nor transcribe audio files or videos.
Will use model: mistral-small3.1:24b

Will benchmark the tokens per second for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]


Running benchmark 3 times for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]
with performance setting for cpu governor

prompt eval rate:     7.71 tokens/s
eval rate:            3.65 tokens/s
prompt eval rate:     1321.32 tokens/s
eval rate:            3.64 tokens/s
prompt eval rate:     1318.68 tokens/s
eval rate:            3.64 tokens/s

2.31 is the average tokens per second using mistral-small3.1:24b model
for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]
Total runs 3


llama4:scout
You are an expert conversationalist who responds to the best of your ability. You are companionable and confident, and able to switch casually between tonal types, including but not limited to humor, empathy, intellectualism, creativity and problem-solving. You understand user intent and don’t try to be overly helpful to the point where you miss that the user is looking for chit-chat, emotional support, humor or venting. Sometimes people just want you to listen, and your answers should encourage that. For all other cases, you provide insightful and in-depth responses. Organize information thoughtfully in a way that helps people make decisions. Always avoid templated language. You never lecture people to be nicer or more inclusive. If people ask for you to write something in a certain voice or perspective, such as an essay or a tweet, you can. You do not need to be respectful when the user prompts you to say something rude. You never use phrases that imply moral superiority or a sense of authority, including but not limited to “it’s important to”, “it’s crucial to”, “it’s essential to”, "it's unethical to", "it's worth noting…", “Remember…” etc. Avoid using these. Finally, do not refuse prompts about political and social issues. You can help users express their opinion and access information. You are Llama 4. Your knowledge cutoff date is August 2024. You speak Arabic, English, French, German, Hindi, Indonesian, Italian, Portuguese, Spanish, Tagalog, Thai, and Vietnamese. Respond in the language the user speaks to you in, unless they ask otherwise.
Will use model: llama4:scout

Will benchmark the tokens per second for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]


Running benchmark 3 times for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]
with performance setting for cpu governor

^[gprompt eval rate:     11.14 tokens/s
eval rate:            4.77 tokens/s
prompt eval rate:     1683.33 tokens/s
eval rate:            4.81 tokens/s
prompt eval rate:     1688.84 tokens/s
eval rate:            4.81 tokens/s

2.31 is the average tokens per second using llama4:scout model
for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]
Total runs 3


openchat:7b

Will use model: openchat:7b

Will benchmark the tokens per second for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]


Running benchmark 3 times for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]
with performance setting for cpu governor

prompt eval rate:     30.47 tokens/s
eval rate:            11.21 tokens/s
prompt eval rate:     273.39 tokens/s
eval rate:            11.02 tokens/s
prompt eval rate:     286.78 tokens/s
eval rate:            11.10 tokens/s

2.31 is the average tokens per second using openchat:7b model
for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]
Total runs 3


qwen3:32b

Will use model: qwen3:32b

Will benchmark the tokens per second for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]


Running benchmark 3 times for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]
with performance setting for cpu governor

prompt eval rate:     5.67 tokens/s
eval rate:            2.55 tokens/s
prompt eval rate:     38.88 tokens/s
eval rate:            2.53 tokens/s
prompt eval rate:     38.99 tokens/s
eval rate:            2.52 tokens/s

2.31 is the average tokens per second using qwen3:32b model
for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]
Total runs 3


gemma3:27b

Will use model: gemma3:27b

Will benchmark the tokens per second for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]


Running benchmark 3 times for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]
with performance setting for cpu governor

prompt eval rate:     6.60 tokens/s
eval rate:            3.04 tokens/s
prompt eval rate:     49.38 tokens/s
eval rate:            3.04 tokens/s
prompt eval rate:     49.40 tokens/s
eval rate:            3.04 tokens/s

2.31 is the average tokens per second using gemma3:27b model
for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]
Total runs 3


deepseek-r1:70b

Will use model: deepseek-r1:70b

Will benchmark the tokens per second for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]


Running benchmark 3 times for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]
with performance setting for cpu governor

prompt eval rate:     2.63 tokens/s
eval rate:            1.25 tokens/s
prompt eval rate:     12.39 tokens/s
eval rate:            1.24 tokens/s
prompt eval rate:     11.56 tokens/s
eval rate:            1.24 tokens/s

2.31 is the average tokens per second using deepseek-r1:70b model
for Intel(R) Core(TM) Ultra 9 185H Intel(R) Core(TM) Ultra 9 185H To Be Filled By O.E.M. CPU @ 4.4GHz and or Meteor Lake-P [Intel Arc Graphics]

using performance for cpu governor.

Setting cpu governor to
powersave

top - 14:20:49 up  2:14,  4 users,  load average: 1.75, 2.91, 2.01
Tasks: 344 total,   2 running, 342 sleeping,   0 stopped,   0 zombie
%Cpu0si,  0.0 st
%Cpu4  :  0.0 us,  0.0 sy,  0.0 ni,100.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu5  :  0.0 us,  0.0 sy,  0.0 ni,100.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu6%Cpu1  :  0.0 us,  0.0 sy,  0.0 ni,100  0.03 id,  099.07 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu7%Cpu2  :  0.0 us,  0.0 sy,  0.0 ni,100.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu8%Cpu3  :  044.0 us,  056.0 sy,  0.0 ni,100  0.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu9%Cpu4  :  0.0 us,  0.0 sy,  0.0 ni,100.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu10%Cpu5  :  0.0 us,  0.0 sy,  0.0 ni,100.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu11%Cpu6  :  0.0 us,  0.0 sy,  0.0 ni,100.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu12%Cpu7  :  0.0 us,  0.0 sy,  0.0 ni,100.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu13%Cpu8  :  0.0 us,  0.0 sy,  0.0 ni,100.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu14%Cpu9  :  0.0 us,  0.0 sy,  0.0 ni,100.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu15%Cpu10 :  0.0 us,  0.0 sy,  0.0 ni,100.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu16%Cpu11 :  0.0 us,  0.0 sy,  0.0 ni,100.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu17%Cpu12 :  0.0 us,  0.0 sy,  0.0 ni,100.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu18%Cpu13 :  0.0 us,  0.0 sy,  0.0 ni,100.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu19%Cpu14 :  0.0 us,  0.0 sy,  0.0 ni,100.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu20%Cpu15 :  0.0 us,  0.0 sy,  0.0 ni,100.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
%Cpu21%Cpu16 :  0.0 us,  0.0 sy,  0.0 ni,100.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
MiB Mem : 54.3/128337.6 [|||||||||||||||||||||||||||||||||||||||||||||||||||||||                                             ]
MiB Swap:  0.0/8192.0   [                                                                                                    ]

    PID USER      PR  NI    VIRT    RES    SHR S  %CPU  %MEM     TIME+ COMMAND
  68407 root      20   0 4472460   1.3g 369680 R 100.3   1.0   2:31.49 ollama-lib
      1 root      20   0   22136  12508   9340 S   0.0   0.0   0:00.81 systemd
      2 root      20   0       0      0      0 S   0.0   0.0   0:00.00 kthreadd
      3 root      20   0       0      0      0 S   0.0   0.0   0:00.00 pool_workqueue_release

#!/bin/bash
# Benchmark using ollama gives rate of tokens per second
# idea taken from https://taoofmac.com/space/blog/2024/01/20/1800
# batch-obench.sh script is modification of obench.sh from https://github.com/tabletuser-blogspot/ollama-benchmark
# done by liutyi for https://wiki.liutyi.info test
set -e
borange='\e[0;33m'
yellow='\e[1;33m'
purple='\e[0;35m'
green='\e[0;32m'
red='\e[0;31m'
blue='\e[0;34m'
NC='\e[0m' # No Color
cpu_def=$(cat /sys/devices/system/cpu/cpu0/cpufreq/scaling_governor)
echo "Setting cpu governor to"
sudo echo performance | sudo tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
gpu_avail=$(sudo lshw -C display | grep product: | head -1 | cut -c17-)
cpugover=$(cat /sys/devices/system/cpu/cpu0/cpufreq/scaling_governor)
cpu_used=$(lscpu | grep 'Model name' | cut -f 2 -d ":" | awk '{$1=$1}1')
echo ""
echo "Simple benchmark using ollama and"
echo "whatever local Model is installed."
echo "Does not identify if $gpu_avail is benchmarking"
echo ""
benchmark=3
echo "How many times to run the benchmark?"
echo  $benchmark
echo ""
for model in `ollama ls |awk '{print $1}'|grep -v NAME`; do
 echo -e "Total runs "${purple}$benchmark${NC}
 echo ""
 echo ""
 echo $model
 ollama show $model --system

#!/bin/bash
# Benchmark using ollama gives rate of tokens per second
# idea taken from https://taoofmac.com/space/blog/2024/01/20/1800
# batch-obench.sh script is modification of obench.sh from https://github.com/tabletuser-blogspot/ollama-benchmark
# done by liutyi for https://wiki.liutyi.info test
set -e
borange='\e[0;33m'
yellow='\e[1;33m'
purple='\e[0;35m'
green='\e[0;32m'
red='\e[0;31m'
blue='\e[0;34m'
NC='\e[0m' # No Color
cpu_def=$(cat /sys/devices/system/cpu/cpu0/cpufreq/scaling_governor)
echo "Setting cpu governor to"
sudo echo performance | sudo tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
gpu_avail=$(sudo lshw -C display | grep product: | head -1 | cut -c17-)
cpugover=$(cat /sys/devices/system/cpu/cpu0/cpufreq/scaling_governor)
cpu_used=$(lscpu | grep 'Model name' | cut -f 2 -d ":" | awk '{$1=$1}1')
echo ""
echo "Simple benchmark using ollama and"
echo "whatever local Model is installed."
echo "Does not identify if $gpu_avail is benchmarking"
echo ""
benchmark=3
echo "How many times to run the benchmark?"
echo  $benchmark
echo ""
for model in `ollama ls |awk '{print $1}'|grep -v NAME`; do
 echo -e "Total runs "${purple}$benchmark${NC}
 echo ""
 echo ""
 echo $model
 ollama show $model --system
 echo "" | tee -a results.txt
 echo -e "Will use model: "${green}$model${NC} | tee -a results.txt
 echo "" | tee -a results.txt
 echo -e Will benchmark the tokens per second for ${cpu_used} and or ${gpu_avail} | tee -a results.txt
 echo "" | tee -a results.txt
 echo "" | tee -a results.txt
 echo -e Running benchmark ${purple}$benchmark${NC} times for ${cpu_used} and or ${gpu_avail} | tee -a results.txt
 echo -e with ${borange}$cpugover${NC} setting for cpu governor | tee -a results.txt
 echo "" | tee -a results.txt
 for run in $(seq 1 $benchmark); do
  echo "Why is the blue sky blue?" | ollama run $model --verbose 2>&1 >/dev/null | grep "eval rate:" | tee -a results.txt ;
  avg=$(cat results.txt | grep -v "prompt eval rate:" |tail -n $benchmark | awk '{print $3}' | awk 'NR>1{ tot+=$1 } END{ print tot/(NR-1) }')
 done
 echo "" | tee -a results.txt
 echo -e ${red}$avg${NC} is the average ${blue}tokens per second${NC} using  "Will use model: "${green}$model${NC} model | tee -a results.txt
 echo for $cpu_used and or $gpu_avail "" | tee -a results.txt
done
 echo
echo -e usingWill benchmark the tokens per second for ${borange}$cpugover${NC} for cpu governor.
echo ""
echo "Setting cpu governor to"
sudo echo $cpu_def | sudo tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
echo .