模型排行

排名	變化	模型	得分	置信區間	投票	價格 $/M
1	—	deepseek-r1開源DeepSeek	1,320	±7	6,581	—
2	—	deepseek-v3開源DeepSeek	1,276	±4	19,461	—
3	—	llama-3.1-405b-instruct-bf16開源Meta	1,254	±4	31,499	—
4	—	llama-3.1-405b-instruct-fp8開源Meta	1,253	±2	63,157	—
5	—	deepseek-v2.5-1210開源DeepSeek · 另有 1 個檔位	1,240	±6	7,245	—
6	—	llama-3.3-70b-instruct開源Meta	1,234	±4	25,878	—
7	—	mistral-large-2407開源Mistral · 另有 1 個檔位	1,232	±3	48,201	—
8	—	qwen-max-0919開源Alibaba	1,231	±5	17,428	—
9	—	athene-v2-chat開源NexusFlow	1,231	±3	26,092	—
10	—	athene-70b-0725開源NexusFlow	1,223	±3	20,604	—
11	—	qwen2.5-72b-instruct開源Alibaba	1,222	±3	41,543	—
12	—	llama-3.1-nemotron-70b-instruct開源NVIDIA	1,216	±6	7,601	—
13	—	llama-3.1-70b-instruct開源Meta	1,214	±3	58,750	—
14	—	llama-3.1-tulu-3-70b開源Ai2	1,209	±9	3,014	—
15	—	gemma-2-27b-it開源Google	1,208	±3	77,543	—
16	—	jamba-1.5-large開源AI21 Labs	1,205	±5	9,120	—
17	—	llama-3.1-nemotron-51b-instruct開源NVIDIA	1,204	±8	3,891	—
18	—	gemma-2-9b-it-simpo開源Princeton	1,200	±6	10,549	—
19	—	command-r-plus-08-2024開源Cohere	1,197	±5	10,539	—
20	—	nemotron-4-340b-instruct開源NVIDIA	1,196	±4	20,608	—
21	—	llama-3-70b-instruct開源Meta	1,195	±2	163,745	—
22	▲ 1	qwen2.5-coder-32b-instruct開源Alibaba	1,190	±7	5,724	—
23	▲ 1	c4ai-aya-expanse-32b開源Cohere	1,185	±3	28,750	—
24	▼ 2	mistral-small-24b-instruct-2501開源Mistral	1,184	±7	6,280	—
25	—	command-r-plus開源Cohere	1,183	±2	80,868	—
26	—	deepseek-coder-v2開源DeepSeek	1,182	±4	15,749	—
27	—	qwen2-72b-instruct開源Alibaba	1,181	±3	38,875	—
28	—	gemma-2-9b-it開源Google	1,180	±3	55,285	—
29	—	phi-4開源Microsoft	1,176	±6	13,156	—
30	—	command-r-08-2024開源Cohere	1,176	±5	10,845	—
31	—	jamba-1.5-mini開源AI21 Labs	1,160	±6	9,271	—
32	—	ministral-8b-2410開源Mistral	1,160	±7	5,108	—
33	—	qwen1.5-110b-chat開源Alibaba	1,155	±4	27,453	—
34	—	c4ai-aya-expanse-8b開源Cohere	1,151	±6	10,404	—
35	—	mixtral-8x22b-instruct-v0.1開源Mistral	1,149	±3	53,773	—
36	—	qwen1.5-72b-chat開源Alibaba	1,148	±3	40,638	—
37	—	command-r開源Cohere	1,148	±3	56,356	—
38	—	llama-3.1-tulu-3-8b開源Ai2	1,147	±9	3,073	—
39	—	llama-3-8b-instruct開源Meta	1,143	±2	109,218	—
40	—	granite-3.1-8b-instruct開源IBM	1,135	±10	3,302	—
41	—	yi-1.5-34b-chat開源01 AI	1,133	±4	25,121	—
42	—	llama-3.1-8b-instruct開源Meta	1,133	±3	52,633	—
43	—	zephyr-orpo-141b-A35b-v0.1開源HuggingFace	1,130	±8	4,859	—
44	—	qwen1.5-32b-chat開源Alibaba	1,126	±5	22,766	—
45	—	phi-3-medium-4k-instruct開源Microsoft	1,118	±4	26,092	—
46	—	gemma-2-2b-it開源Google	1,118	±3	47,032	—
47	—	internlm2_5-20b-chat開源InternLM	1,116	±5	10,595	—
48	—	mixtral-8x7b-instruct-v0.1開源Mistral	1,114	±0	76,103	—
49	—	dbrx-instruct-preview開源Databricks	1,113	±3	33,720	—
50	—	granite-3.0-8b-instruct開源IBM	1,109	±8	7,003	—
51	—	qwen1.5-14b-chat開源Alibaba	1,107	±5	18,667	—
52	—	wizardlm-70b開源Microsoft	1,105	±6	8,380	—
53	—	granite-3.1-2b-instruct開源IBM	1,104	±9	3,385	—
54	—	snowflake-arctic-instruct開源Snowflake	1,102	±3	34,176	—
55	—	yi-34b-chat開源01 AI	1,101	±5	15,924	—
56	—	openchat-3.5-0106開源OpenChat · 另有 1 個檔位	1,100	±5	12,981	—
57	—	gemma-1.1-7b-it開源Google	1,099	±3	25,071	—
58	—	phi-3-small-8k-instruct開源Microsoft	1,098	±4	18,479	—
59	—	llama-3.2-3b-instruct開源Meta	1,093	±5	8,405	—
60	—	tulu-2-dpo-70b開源AllenAI/UW	1,092	±7	6,656	—
61	—	starling-lm-7b-beta開源Nexusflow	1,092	±5	16,668	—
62	—	vicuna-33b開源LMSYS	1,091	±4	22,944	—
63	—	deepseek-llm-67b-chat開源DeepSeek	1,091	±9	4,984	—
64	—	openhermes-2.5-mistral-7b開源NousResearch	1,090	±8	5,088	—
65	—	qwq-32b-preview開源Alibaba	1,088	±9	3,413	—
66	—	starling-lm-7b-alpha開源UC Berkeley	1,083	±6	10,415	—
67	—	llama-2-70b-chat開源Meta	1,082	±3	39,614	—
68	—	granite-3.0-2b-instruct開源IBM	1,082	±8	7,185	—
69	—	llama2-70b-steerlm-chat開源NVIDIA	1,074	±9	3,637	—
70	—	nous-hermes-2-mixtral-8x7b-dpo開源NousResearch	1,072	±8	3,834	—
71	—	dolphin-2.2.1-mistral-7b開源Cognitive Computations	1,069	±14	1,714	—
72	—	phi-3-mini-4k-instruct-june-2024開源Microsoft	1,068	±5	12,807	—
73	—	mistral-7b-instruct-v0.2開源Mistral	1,067	±5	20,050	—
74	—	solar-10.7b-instruct-v1.0開源Upstage AI	1,066	±9	4,288	—
75	—	qwen1.5-7b-chat開源Alibaba	1,065	±9	4,863	—
76	—	wizardlm-13b開源Microsoft	1,063	±7	7,174	—
77	—	mpt-30b-chat開源MosaicML	1,060	±11	2,645	—
78	—	falcon-180b-chat開源TII	1,059	±15	1,327	—
79	—	vicuna-13b開源LMSYS	1,058	±4	19,788	—
80	—	qwen-14b-chat開源Alibaba	1,056	±8	5,064	—
81	—	phi-3-mini-4k-instruct開源Microsoft	1,056	±4	21,094	—
82	—	llama-2-13b-chat開源Meta	1,054	±6	19,730	—
83	—	smollm2-1.7b-instruct開源HuggingFace	1,051	±12	2,368	—
84	—	zephyr-7b-beta開源HuggingFace	1,049	±6	11,327	—
85	—	phi-3-mini-128k-instruct開源Microsoft	1,049	±4	21,614	—
86	—	gemma-7b-it開源Google	1,048	±6	9,182	—
87	—	codellama-34b-instruct開源Meta	1,047	±7	7,509	—
88	—	zephyr-7b-alpha開源HuggingFace	1,046	±11	1,814	—
89	—	llama-3.2-1b-instruct開源Meta	1,045	±6	8,529	—
90	—	gemma-1.1-2b-it開源Google	1,040	±5	11,348	—
91	—	guanaco-33b開源UW	1,040	±10	2,995	—
92	—	codellama-70b-instruct開源Meta	1,038	±18	1,193	—
93	—	stripedhyena-nous-7b開源Together AI	1,034	±8	5,272	—
94	—	mistral-7b-instruct開源Mistral	1,027	±6	9,141	—
95	—	llama-2-7b-chat開源Meta	1,025	±5	14,548	—
96	—	vicuna-7b開源LMSYS	1,021	±7	7,016	—
97	—	qwen1.5-4b-chat開源Alibaba	1,014	±7	7,812	—
98	—	gemma-2b-it開源Google	1,008	±8	4,921	—
99	—	olmo-7b-instruct開源Ai2	994	±8	6,499	—
100	—	koala-13b開源UC Berkeley	979	±7	7,032	—
101	—	chatglm3-6b開源Tsinghua	974	±11	4,760	—
102	—	gpt4all-13b-snoozy開源Nomic AI	972	±14	1,787	—
103	—	mpt-7b-chat開源MosaicML	967	±9	4,013	—
104	—	alpaca-13b開源Stanford	967	±9	5,877	—
105	—	RWKV-4-Raven-14B開源RWKV	949	±9	4,932	—
106	—	chatglm2-6b開源Tsinghua	942	±12	2,707	—
107	—	oasst-pythia-12b開源OpenAssistant	931	±9	6,380	—
108	—	fastchat-t5-3b開源LMSYS	896	±10	4,297	—
109	—	chatglm-6b開源Tsinghua	888	±9	4,989	—
110	—	dolly-v2-12b開源Databricks	881	±11	3,486	—
111	—	llama-13b開源Meta	867	±14	2,444	—
112	—	stablelm-tuned-alpha-7b開源Stability AI	859	±13	3,339	—

其餘 62 個模型

智力進步

每家廠商當時最強的模型在 Artificial Analysis 智力指數上的分數，按模型釋出的月份畫。

漲得最多 · Anthropic +57.2目前最高 · Anthropic 64.6最高與最低相差 18.1 分時間範圍 2025年11月 – 2026年11月

64.6Anthropic60.0Google56.9OpenAI50.1Meta46.5Kimi