Trinity Large Thinking (high) vs Ling 3.0 Flash (high)

Modeli zilizolinganishwa

Nafasi: #304
Jumla ya tokeni za matokeo: 717,762
Muda wa majibu (wastani): 74.52s
Jumla ya gharama: $0.794

Nafasi: #302
Jumla ya tokeni za matokeo: 275,014
Muda wa majibu (wastani): 13.08s
Jumla ya gharama: $0.021

Muundo unaopendekezwa Ling 3.0 Flash (high)

It has the best score here (5.8), while costing about 39.5x less than Trinity Large Thinking (high).

Ulinganisho wa kina

Kipimo	Trinity Large Thinking Trinity Large Thinking high Toleo: 2026-07-28	Ling 3.0 Flash Ling 3.0 Flash high Toleo: 2026-07-24

Kipimo	Trinity Large Thinking Trinity Large Thinking high Toleo: 2026-07-28	Ling 3.0 Flash Ling 3.0 Flash high Toleo: 2026-07-24
Alama	5.7	5.8
Nafasi	#304	#302
Uaminifu	10.0	9.8
Uthabiti	7.3	8.6
Majaribio	69/69	69/69
Majaribio sahihi
Kiwango cha kupita kwa kila jaribio	42.0%	60.9%
Majaribio yasiyo thabiti	8	4
Jumla ya uendeshaji	69	69
Gharama kwa matokeo	11.289	0.000
Jumla ya gharama	$0.794	$0.021
Bei ya ingizo	$0.250 / 1M	$0.021 / 1M
Bei ya toleo	$0.800 / 1M	$0.063 / 1M
Bei ya kusoma akiba	$0.060 / 1M	$0.005 / 1M
Bei ya kuandika akiba	Haipo	Haipo
Jumla ya tokeni za ingizo	283,116	132,044
Tokeni za matokeo	277,920	92,135
Tokeni za hoja	665,124	207,321
Muda wa majibu (wastani)	74.52s	13.08s
Muda wa majibu (upeo)	510.21s	75.27s
Muda wa majibu (jumla)	1713.90s	287.79s
Vigezo	398B jumla (13B vinavyotumika)	124B jumla (5.1B vinavyotumika)
Upatikanaji	Uzani unapatikana	Chanzo huria

Bei za akiba zinahusu tokeni za ingizo. Kusoma hutumia tena maelekezo yaliyohifadhiwa; kuandika huyahifadhi na kunaweza kuongeza gharama. Tokeni za matokeo hutumia bei ya matokeo.

Onyesho la kizazi cha modeli

Hamster playing table tennis

Prompt: Create a detailed SVG illustration of a hamster playing table tennis.

#304 Trinity Large Thinking

high

Gharama: $0.028
Muda: 130.1s
Tokeni: 34,387 tok

#302 Ling 3.0 Flash

high

Gharama: $0.000
Muda: 30.7s
Tokeni: 10,576 tok

Modeli bora kwa alama

Alama dhidi ya gharama ya jumla

Muda wa majibu (wastani)

Alama vs Muda wa majibu (wastani)

Jumla ya tokeni za matokeo

Alama vs Jumla ya tokeni za matokeo

Mgawanyo wa kategoria

Kategoria:

Kazi za mawakala	Alama	Uthabiti	Kiwango cha kupita kwa kila jaribio	Majaribio yasiyo thabiti	Majaribio sahihi	Muda wa majibu (wastani)	Tokeni za ingizo	Tokeni za matokeo	Tokeni za hoja
Trinity Large Thinking	10.0	10.0	100.0%	0		44.97s	181,340	1,553	8,872
Ling 3.0 Flash	3.0	10.0	0.0%	0		42ms	0	0	0

Mbinu za kupinga AI	Alama	Uthabiti	Kiwango cha kupita kwa kila jaribio	Majaribio yasiyo thabiti	Majaribio sahihi	Muda wa majibu (wastani)	Tokeni za ingizo	Tokeni za matokeo	Tokeni za hoja
Trinity Large Thinking	6.7	8.1	58.3%	1		4.13s	663	3,108	7,565
Ling 3.0 Flash	10.0	10.0	100.0%	0		4.26s	750	1,127	3,129

Uandishi wa msimbo	Alama	Uthabiti	Kiwango cha kupita kwa kila jaribio	Majaribio yasiyo thabiti	Majaribio sahihi	Muda wa majibu (wastani)	Tokeni za ingizo	Tokeni za matokeo	Tokeni za hoja
Trinity Large Thinking	3.7	4.7	33.3%	2		245.04s	7,204	83,616	266,836
Ling 3.0 Flash	6.7	5.0	66.7%	2		14.85s	8,298	15,602	32,152

Mchanganyiko	Alama	Uthabiti	Kiwango cha kupita kwa kila jaribio	Majaribio yasiyo thabiti	Majaribio sahihi	Muda wa majibu (wastani)	Tokeni za ingizo	Tokeni za matokeo	Tokeni za hoja
Trinity Large Thinking	3.0	10.0	0.0%	0		262.39s	76,626	14,706	149,243
Ling 3.0 Flash	2.9	6.0	16.7%	1		50.41s	103,841	28,377	80,872

Uchanganuzi na uchimbaji wa data	Alama	Uthabiti	Kiwango cha kupita kwa kila jaribio	Majaribio yasiyo thabiti	Majaribio sahihi	Muda wa majibu (wastani)	Tokeni za ingizo	Tokeni za matokeo	Tokeni za hoja
Trinity Large Thinking	6.3	5.8	66.7%	1		13.98s	6,906	580	9,338
Ling 3.0 Flash	7.3	5.8	83.3%	1		7.15s	8,016	3,455	9,048

Mahususi kwa domeni	Alama	Uthabiti	Kiwango cha kupita kwa kila jaribio	Majaribio yasiyo thabiti	Majaribio sahihi	Muda wa majibu (wastani)	Tokeni za ingizo	Tokeni za matokeo	Tokeni za hoja
Trinity Large Thinking	2.9	7.2	11.1%	1		66.94s	756	163,364	166,091
Ling 3.0 Flash	3.0	10.0	0.0%	0		30.29s	648	37,633	61,104

Akili ya jumla	Alama	Uthabiti	Kiwango cha kupita kwa kila jaribio	Majaribio yasiyo thabiti	Majaribio sahihi	Muda wa majibu (wastani)	Tokeni za ingizo	Tokeni za matokeo	Tokeni za hoja
Trinity Large Thinking	6.5	3.4	66.7%	1		12.90s	501	5,700	5,942
Ling 3.0 Flash	5.0	10.0	0.0%	0		2.98s	546	63	344

Ufuataji wa maagizo	Alama	Uthabiti	Kiwango cha kupita kwa kila jaribio	Majaribio yasiyo thabiti	Majaribio sahihi	Muda wa majibu (wastani)	Tokeni za ingizo	Tokeni za matokeo	Tokeni za hoja
Trinity Large Thinking	6.3	10.0	50.0%	0		4.12s	684	88	2,853
Ling 3.0 Flash	10.0	10.0	100.0%	0		1.85s	744	402	2,031

Utatuzi wa mafumbo	Alama	Uthabiti	Kiwango cha kupita kwa kila jaribio	Majaribio yasiyo thabiti	Majaribio sahihi	Muda wa majibu (wastani)	Tokeni za ingizo	Tokeni za matokeo	Tokeni za hoja
Trinity Large Thinking	4.7	5.2	33.3%	2		3.84s	678	2,566	3,368
Ling 3.0 Flash	10.0	10.0	100.0%	0		4.33s	747	753	4,623

Mwito wa zana	Alama	Uthabiti	Kiwango cha kupita kwa kila jaribio	Majaribio yasiyo thabiti	Majaribio sahihi	Muda wa majibu (wastani)	Tokeni za ingizo	Tokeni za matokeo	Tokeni za hoja
Trinity Large Thinking	10.0	10.0	100.0%	0		5.96s	7,551	282	1,440
Ling 3.0 Flash	10.0	10.0	100.0%	0		6.47s	8,226	322	527

Maarifa ya jumla	Alama	Uthabiti	Kiwango cha kupita kwa kila jaribio	Majaribio yasiyo thabiti	Majaribio sahihi	Muda wa majibu (wastani)	Tokeni za ingizo	Tokeni za matokeo	Tokeni za hoja
Trinity Large Thinking	3.0	10.0	0.0%	0		125.13s	207	2,357	43,576
Ling 3.0 Flash	3.0	10.0	0.0%	0		24.35s	228	4,401	13,491

Badilisha jozi ya ulinganisho

Trinity Large ThinkinghighvsRing 2.6 1tmedium Trinity Large ThinkinghighvsGPT-5 Nanomedium DeepSeek V4.1 FlashnonevsLing 3.0 Flashhigh Trinity Large ThinkinghighvsGPT-5.4 Mininone Trinity Large ThinkinghighvsMistral Large 4none Trinity Large ThinkinghighvsSeed 2.1 Turbonone Ling 3.0 FlashhighvsGPT-5.6 Terranone Trinity Large ThinkinghighvsDots 3 Note PreviewmediumInapatikana bure Ling 3.0 FlashhighvsGPT-5 Nanomedium Trinity Large ThinkinghighvsDeepSeek V4.1 Flashnone Ling 3.0 FlashhighvsGPT-5.4 Mininone Ling 3.0 FlashhighvsMistral Large 4none