模型排行

排名	變化	模型	得分	置信區間	投票	價格 $/M
1	—	kimi-k2-thinking-turbo開源Moonshot AI	1,431	±7	9,674	—
2	—	glm-4.6開源Z.ai	1,426	±5	18,980	—
3	▲ 1	deepseek-v3.2-exp開源DeepSeek · 另有 1 個檔位	1,424	±7	9,690	—
4	▼ 1	qwen3-235b-a22b-instruct-2507開源Alibaba	1,421	±4	45,379	—
5	▲ 1	kimi-k2-0905-preview開源Moonshot AI · 另有 1 個檔位	1,418	±7	11,839	—
6	▼ 1	deepseek-r1-0528開源DeepSeek · 另有 1 個檔位	1,418	±6	19,243	—
7	—	deepseek-v3.1開源DeepSeek · 另有 1 個檔位	1,416	±6	15,262	—
8	▲ 1	qwen3-vl-235b-a22b-instruct開源Alibaba	1,415	±7	8,538	—
9	▼ 1	deepseek-v3.1-terminus開源DeepSeek · 另有 1 個檔位	1,415	±10	3,748	—
10	—	glm-4.5開源Z.ai	1,408	±5	24,833	—
11	—	qwen3-next-80b-a3b-instruct開源Alibaba	1,400	±5	23,127	—
12	—	longcat-flash-chat開源Meituan	1,399	±6	11,505	—
13	—	qwen3-235b-a22b-no-thinking開源Alibaba	1,399	±5	39,389	—
14	—	qwen3-235b-a22b-thinking-2507開源Alibaba	1,397	±6	9,346	—
15	—	qwen3-vl-235b-a22b-thinking開源Alibaba	1,393	±7	7,989	—
16	—	deepseek-v3-0324開源DeepSeek · 另有 1 個檔位	1,392	±4	46,802	—
17	—	qwen3-coder-480b-a35b-instruct開源Alibaba	1,385	±5	23,164	—
18	—	qwen3-30b-a3b-instruct-2507開源Alibaba	1,382	±5	24,205	—
19	—	qwen3-235b-a22b開源Alibaba	1,374	±5	27,173	—
20	—	glm-4.5-air開源Z.ai	1,370	±4	31,678	—
21	—	qwen3-next-80b-a3b-thinking開源Alibaba	1,367	±6	13,821	—
22	—	minimax-m1開源MiniMax	1,366	±4	36,891	—
23	—	gemma-3-27b-it開源Google	1,365	±4	49,328	—
24	—	mistral-small-2506開源Mistral	1,354	±5	18,330	—
25	—	gpt-oss-120b開源OpenAI	1,352	±4	31,283	$0.26
26	—	command-a-03-2025開源Cohere	1,352	±3	57,853	—
27	—	glm-4.5v開源Z.ai	1,352	±8	4,978	—
28	▲ 1	ling-flash-2.0開源Ant Group	1,346	±7	7,158	—
29	▼ 1	minimax-m2開源MiniMax	1,346	±8	7,132	—
30	▲ 1	step-3開源StepFun	1,345	±7	6,648	—
31	▼ 1	llama-3.1-nemotron-ultra-253b-v1開源NVIDIA	1,345	±12	2,573	—
32	—	qwen3-32b開源Alibaba	1,344	±9	3,943	—
33	—	gemma-3-12b-it開源Google	1,340	±9	3,866	—
34	—	nvidia-llama-3.3-nemotron-super-49b-v1.5開源NVIDIA	1,340	±10	3,497	—
35	—	llama-3.1-405b-instruct-bf16開源Meta	1,335	±4	41,932	—
36	▲ 1	qwq-32b開源Alibaba · 另有 1 個檔位	1,333	±4	26,279	—
37	▼ 1	llama-3.1-405b-instruct-fp8開源Meta	1,333	±3	60,272	—
38	—	llama-4-maverick-17b-128e-instruct開源Meta	1,327	±4	41,220	—
39	—	qwen3-30b-a3b開源Alibaba	1,326	±5	27,498	—
40	—	llama-3.3-nemotron-49b-super-v1開源NVIDIA	1,325	±12	2,243	—
41	—	llama-4-scout-17b-16e-instruct開源Meta	1,323	±5	31,208	—
42	—	deepseek-v2.5-1210開源DeepSeek · 另有 1 個檔位	1,322	±8	6,877	—
43	—	ring-flash-2.0開源Ant Group	1,320	±7	7,282	—
44	—	llama-3.3-70b-instruct開源Meta	1,319	±3	56,018	—
45	—	gemma-3n-e4b-it開源Google	1,318	±5	23,472	—
46	—	gpt-oss-20b開源OpenAI	1,318	±6	10,854	—
47	—	qwen-max-0919開源Alibaba	1,317	±6	16,598	—
48	—	mistral-large-2407開源Mistral · 另有 1 個檔位	1,313	±4	45,968	—
49	—	athene-v2-chat開源NexusFlow	1,313	±4	24,880	—
50	—	athene-70b-0725開源NexusFlow	1,304	±6	19,796	—
51	—	mistral-small-3.1-24b-instruct-2503開源Mistral	1,303	±4	34,148	—
52	—	gemma-3-4b-it開源Google	1,303	±9	4,195	—
53	—	qwen2.5-72b-instruct開源Alibaba	1,301	±4	39,632	—
54	—	llama-3.1-nemotron-70b-instruct開源NVIDIA	1,297	±8	7,216	—
55	—	llama-3.1-70b-instruct開源Meta	1,293	±4	56,003	—
56	—	jamba-1.5-large開源AI21 Labs	1,288	±7	8,730	—
57	—	gemma-2-27b-it開源Google	1,287	±3	76,195	—
58	—	llama-3.1-nemotron-51b-instruct開源NVIDIA	1,286	±10	3,777	—
59	—	llama-3.1-tulu-3-70b開源Ai2	1,286	±10	2,881	—
60	—	gemma-2-9b-it-simpo開源Princeton	1,278	±7	10,108	—
61	—	nemotron-4-340b-instruct開源NVIDIA	1,278	±5	19,913	—
62	—	command-r-plus-08-2024開源Cohere	1,277	±6	9,931	—
63	—	llama-3-70b-instruct開源Meta	1,276	±3	158,908	—
64	—	mistral-small-24b-instruct-2501開源Mistral	1,273	±6	14,830	—
65	—	qwen2.5-coder-32b-instruct開源Alibaba	1,269	±8	5,452	—
66	—	c4ai-aya-expanse-32b開源Cohere	1,267	±5	27,362	—
67	—	gemma-2-9b-it開源Google	1,264	±4	54,954	—
68	—	deepseek-coder-v2開源DeepSeek	1,263	±6	15,242	—
69	—	command-r-plus開源Cohere	1,263	±4	78,401	—
70	—	qwen2-72b-instruct開源Alibaba	1,262	±5	37,688	—
71	—	phi-4開源Microsoft	1,255	±4	24,354	—
72	—	olmo-2-0325-32b-instruct開源Ai2	1,253	±11	3,377	—
73	—	command-r-08-2024開源Cohere	1,251	±7	10,229	—
74	—	jamba-1.5-mini開源AI21 Labs	1,239	±7	8,918	—
75	—	ministral-8b-2410開源Mistral	1,237	±9	4,833	—
76	—	qwen1.5-110b-chat開源Alibaba	1,234	±5	26,679	—
77	—	qwen1.5-72b-chat開源Alibaba	1,234	±5	39,689	—
78	—	mixtral-8x22b-instruct-v0.1開源Mistral	1,230	±4	52,214	—
79	—	command-r開源Cohere	1,228	±5	54,710	—
80	▲ 1	c4ai-aya-expanse-8b開源Cohere	1,223	±7	9,922	—
81	▼ 1	llama-3-8b-instruct開源Meta	1,223	±4	106,055	—
82	—	llama-3.1-tulu-3-8b開源Ai2	1,222	±11	2,943	—
83	—	zephyr-orpo-141b-A35b-v0.1開源HuggingFace	1,214	±11	4,712	—
84	—	yi-1.5-34b-chat開源01 AI	1,213	±5	24,417	—
85	—	llama-3.1-8b-instruct開源Meta	1,211	±4	50,234	—
86	—	granite-3.1-8b-instruct開源IBM	1,210	±11	3,142	—
87	—	qwen1.5-32b-chat開源Alibaba	1,205	±6	22,068	—
88	—	phi-3-medium-4k-instruct開源Microsoft	1,198	±5	25,301	—
89	—	mixtral-8x7b-instruct-v0.1開源Mistral	1,198	±4	74,303	—
90	—	gemma-2-2b-it開源Google	1,198	±4	46,901	—
91	—	dbrx-instruct-preview開源Databricks	1,196	±6	32,760	—
92	—	qwen1.5-14b-chat開源Alibaba	1,193	±7	18,066	—
93	—	internlm2_5-20b-chat開源InternLM	1,192	±7	10,038	—
94	—	wizardlm-70b開源Microsoft	1,185	±9	8,270	—
95	—	deepseek-llm-67b-chat開源DeepSeek	1,184	±11	4,950	—
96	—	yi-34b-chat開源01 AI	1,184	±7	15,624	—
97	▲ 1	granite-3.0-8b-instruct開源IBM	1,184	±9	6,727	—
98	▼ 1	openchat-3.5-0106開源OpenChat · 另有 1 個檔位	1,183	±8	12,712	—
99	▲ 1	granite-3.1-2b-instruct開源IBM	1,181	±11	3,235	—
100	▼ 1	snowflake-arctic-instruct開源Snowflake	1,180	±6	33,272	—
101	—	gemma-1.1-7b-it開源Google	1,180	±6	24,327	—
102	—	tulu-2-dpo-70b開源AllenAI/UW	1,179	±10	6,579	—
103	—	openhermes-2.5-mistral-7b開源NousResearch	1,176	±10	5,026	—
104	—	vicuna-33b開源LMSYS	1,173	±6	22,613	—
105	—	starling-lm-7b-beta開源Nexusflow	1,173	±7	16,190	—
106	—	phi-3-small-8k-instruct開源Microsoft	1,172	±6	17,983	—
107	—	llama-2-70b-chat開源Meta	1,172	±5	38,767	—
108	—	starling-lm-7b-alpha開源UC Berkeley	1,168	±8	10,267	—
109	—	llama-3.2-3b-instruct開源Meta	1,167	±8	8,043	—
110	—	nous-hermes-2-mixtral-8x7b-dpo開源NousResearch	1,166	±12	3,792	—
111	—	llama2-70b-steerlm-chat開源NVIDIA	1,157	±13	3,605	—
112	—	granite-3.0-2b-instruct開源IBM	1,157	±8	6,922	—
113	—	solar-10.7b-instruct-v1.0開源Upstage AI	1,154	±13	4,187	—
114	—	dolphin-2.2.1-mistral-7b開源Cognitive Computations	1,152	±15	1,685	—
115	▲ 2	mistral-7b-instruct-v0.2開源Mistral	1,151	±7	19,603	—
116	▼ 1	mpt-30b-chat開源MosaicML	1,151	±12	2,606	—
117	▼ 1	wizardlm-13b開源Microsoft	1,150	±9	7,122	—
118	—	falcon-180b-chat開源TII	1,147	±17	1,312	—
119	—	qwen1.5-7b-chat開源Alibaba	1,144	±10	4,782	—
120	▲ 1	phi-3-mini-4k-instruct-june-2024開源Microsoft	1,143	±6	12,415	—
121	▼ 1	llama-2-13b-chat開源Meta	1,142	±7	19,357	—
122	—	vicuna-13b開源LMSYS	1,142	±7	19,539	—
123	—	qwen-14b-chat開源Alibaba	1,139	±11	5,004	—
124	—	codellama-34b-instruct開源Meta	1,137	±9	7,417	—
125	—	gemma-7b-it開源Google	1,135	±9	9,034	—
126	—	zephyr-7b-beta開源HuggingFace	1,132	±9	11,220	—
127	—	phi-3-mini-128k-instruct開源Microsoft	1,131	±7	21,024	—
128	▲ 1	phi-3-mini-4k-instruct開源Microsoft	1,129	±6	20,539	—
129	▲ 1	zephyr-7b-alpha開源HuggingFace	1,128	±16	1,803	—
130	▼ 2	guanaco-33b開源UW	1,128	±12	2,955	—
131	—	stripedhyena-nous-7b開源Together AI	1,121	±11	5,214	—
132	—	codellama-70b-instruct開源Meta	1,119	±18	1,151	—
133	—	smollm2-1.7b-instruct開源HuggingFace	1,119	±14	2,244	—
134	—	vicuna-7b開源LMSYS	1,115	±9	6,972	—
135	—	gemma-1.1-2b-it開源Google	1,114	±8	11,035	—
136	—	llama-3.2-1b-instruct開源Meta	1,113	±8	8,166	—
137	—	mistral-7b-instruct開源Mistral	1,110	±9	9,042	—
138	—	llama-2-7b-chat開源Meta	1,109	±7	14,272	—
139	—	qwen1.5-4b-chat開源Alibaba	1,091	±9	7,662	—
140	—	gemma-2b-it開源Google	1,091	±12	4,817	—
141	—	olmo-7b-instruct開源Ai2	1,075	±11	6,412	—
142	—	koala-13b開源UC Berkeley	1,070	±10	6,998	—
143	—	alpaca-13b開源Stanford	1,066	±11	5,828	—
144	—	gpt4all-13b-snoozy開源Nomic AI	1,064	±15	1,773	—
145	—	mpt-7b-chat開源MosaicML	1,061	±12	3,977	—
146	—	chatglm3-6b開源Tsinghua	1,057	±12	4,692	—
147	—	RWKV-4-Raven-14B開源RWKV	1,041	±11	4,898	—
148	—	chatglm2-6b開源Tsinghua	1,025	±14	2,683	—
149	—	oasst-pythia-12b開源OpenAssistant	1,022	±11	6,343	—
150	—	chatglm-6b開源Tsinghua	995	±13	4,968	—
151	—	fastchat-t5-3b開源LMSYS	991	±12	4,270	—
152	—	dolly-v2-12b開源Databricks	978	±14	3,471	—
153	—	llama-13b開源Meta	970	±16	2,441	—
154	—	stablelm-tuned-alpha-7b開源Stability AI	952	±13	3,325	—

其餘 104 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