模型排行

排名	變化	模型	得分	置信區間	投票	價格 $/M
1	▲ 2	deepseek-v3-0324開源DeepSeek · 另有 1 個檔位	1,319	±9	2,840	—
2	▼ 1	deepseek-r1開源DeepSeek	1,315	±5	13,836	—
3	▼ 1	gemma-3-27b-it開源Google	1,279	±7	7,989	—
4	—	command-a-03-2025開源Cohere	1,268	±8	4,621	—
5	▲ 2	qwq-32b開源Alibaba · 另有 1 個檔位	1,257	±8	5,167	—
6	▼ 1	llama-3.1-405b-instruct-bf16開源Meta	1,253	±3	40,941	—
7	▼ 1	llama-3.1-405b-instruct-fp8開源Meta	1,253	±3	63,065	—
8	—	llama-3.3-nemotron-49b-super-v1開源NVIDIA	1,246	±10	2,373	—
9	—	deepseek-v2.5-1210開源DeepSeek · 另有 1 個檔位	1,240	±5	7,248	—
10	—	llama-3.3-70b-instruct開源Meta	1,235	±4	35,306	—
11	—	mistral-large-2407開源Mistral · 另有 1 個檔位	1,231	±3	48,225	—
12	—	qwen-max-0919開源Alibaba	1,231	±4	17,430	—
13	—	athene-v2-chat開源NexusFlow	1,230	±4	26,109	—
14	—	athene-70b-0725開源NexusFlow	1,223	±4	20,591	—
15	—	qwen2.5-72b-instruct開源Alibaba	1,222	±3	41,538	—
16	—	llama-3.1-nemotron-70b-instruct開源NVIDIA	1,216	±7	7,577	—
17	—	llama-3.1-70b-instruct開源Meta	1,214	±3	58,675	—
18	—	llama-3.1-tulu-3-70b開源Ai2	1,208	±10	3,016	—
19	—	gemma-2-27b-it開源Google	1,207	±3	79,541	—
20	—	jamba-1.5-large開源AI21 Labs	1,205	±6	9,128	—
21	—	llama-3.1-nemotron-51b-instruct開源NVIDIA	1,204	±9	3,887	—
22	—	gemma-2-9b-it-simpo開源Princeton	1,200	±7	10,550	—
23	—	command-r-plus-08-2024開源Cohere	1,197	±6	10,540	—
24	—	nemotron-4-340b-instruct開源NVIDIA	1,196	±4	20,610	—
25	—	llama-3-70b-instruct開源Meta	1,195	±3	163,673	—
26	—	qwen2.5-coder-32b-instruct開源Alibaba	1,189	±7	5,731	—
27	—	mistral-small-24b-instruct-2501開源Mistral	1,188	±6	13,036	—
28	—	c4ai-aya-expanse-32b開源Cohere	1,185	±4	28,760	—
29	—	command-r-plus開源Cohere	1,183	±3	80,853	—
30	—	deepseek-coder-v2開源DeepSeek	1,182	±4	15,752	—
31	—	qwen2-72b-instruct開源Alibaba	1,180	±3	38,893	—
32	—	gemma-2-9b-it開源Google	1,180	±3	57,202	—
33	—	command-r-08-2024開源Cohere	1,176	±5	10,846	—
34	—	phi-4開源Microsoft	1,175	±4	22,826	—
35	—	jamba-1.5-mini開源AI21 Labs	1,160	±5	9,272	—
36	—	ministral-8b-2410開源Mistral	1,159	±8	5,113	—
37	—	qwen1.5-110b-chat開源Alibaba	1,155	±4	27,436	—
38	—	c4ai-aya-expanse-8b開源Cohere	1,151	±7	10,393	—
39	—	mixtral-8x22b-instruct-v0.1開源Mistral	1,149	±3	53,772	—
40	—	qwen1.5-72b-chat開源Alibaba	1,148	±3	40,667	—
41	—	command-r開源Cohere	1,148	±3	56,391	—
42	—	llama-3.1-tulu-3-8b開源Ai2	1,147	±10	3,073	—
43	—	llama-3-8b-instruct開源Meta	1,142	±3	109,092	—
44	—	granite-3.1-8b-instruct開源IBM	1,134	±11	3,296	—
45	—	yi-1.5-34b-chat開源01 AI	1,133	±4	25,137	—
46	—	llama-3.1-8b-instruct開源Meta	1,133	±3	52,617	—
47	—	zephyr-orpo-141b-A35b-v0.1開源HuggingFace	1,130	±8	4,862	—
48	—	qwen1.5-32b-chat開源Alibaba	1,126	±4	22,772	—
49	▲ 1	phi-3-medium-4k-instruct開源Microsoft	1,118	±4	26,109	—
50	▼ 1	gemma-2-2b-it開源Google	1,117	±4	48,901	—
51	—	internlm2_5-20b-chat開源InternLM	1,116	±5	10,597	—
52	—	mixtral-8x7b-instruct-v0.1開源Mistral	1,114	±0	76,137	—
53	—	dbrx-instruct-preview開源Databricks	1,113	±3	33,752	—
54	—	granite-3.0-8b-instruct開源IBM	1,109	±8	7,002	—
55	—	qwen1.5-14b-chat開源Alibaba	1,107	±4	18,691	—
56	—	wizardlm-70b開源Microsoft	1,105	±5	8,385	—
57	—	granite-3.1-2b-instruct開源IBM	1,104	±11	3,383	—
58	—	snowflake-arctic-instruct開源Snowflake	1,102	±3	34,182	—
59	—	yi-34b-chat開源01 AI	1,101	±4	15,919	—
60	—	openchat-3.5-0106開源OpenChat · 另有 1 個檔位	1,100	±5	12,992	—
61	—	gemma-1.1-7b-it開源Google	1,099	±4	25,072	—
62	—	phi-3-small-8k-instruct開源Microsoft	1,098	±4	18,470	—
63	—	llama-3.2-3b-instruct開源Meta	1,093	±8	8,396	—
64	—	tulu-2-dpo-70b開源AllenAI/UW	1,092	±7	6,659	—
65	—	starling-lm-7b-beta開源Nexusflow	1,092	±5	16,674	—
66	—	vicuna-33b開源LMSYS	1,091	±4	22,946	—
67	—	deepseek-llm-67b-chat開源DeepSeek	1,091	±9	4,988	—
68	—	openhermes-2.5-mistral-7b開源NousResearch	1,090	±7	5,089	—
69	—	starling-lm-7b-alpha開源UC Berkeley	1,083	±6	10,417	—
70	—	granite-3.0-2b-instruct開源IBM	1,082	±7	7,185	—
71	—	llama-2-70b-chat開源Meta	1,082	±4	39,616	—
72	—	llama2-70b-steerlm-chat開源NVIDIA	1,074	±10	3,635	—
73	—	nous-hermes-2-mixtral-8x7b-dpo開源NousResearch	1,072	±9	3,836	—
74	—	dolphin-2.2.1-mistral-7b開源Cognitive Computations	1,069	±13	1,713	—
75	—	phi-3-mini-4k-instruct-june-2024開源Microsoft	1,068	±4	12,811	—
76	—	mistral-7b-instruct-v0.2開源Mistral	1,067	±5	20,070	—
77	—	solar-10.7b-instruct-v1.0開源Upstage AI	1,066	±10	4,287	—
78	—	qwen1.5-7b-chat開源Alibaba	1,065	±7	4,871	—
79	—	wizardlm-13b開源Microsoft	1,063	±7	7,177	—
80	—	mpt-30b-chat開源MosaicML	1,060	±11	2,645	—
81	—	falcon-180b-chat開源TII	1,059	±15	1,328	—
82	—	vicuna-13b開源LMSYS	1,058	±4	19,775	—
83	—	qwen-14b-chat開源Alibaba	1,056	±8	5,067	—
84	—	phi-3-mini-4k-instruct開源Microsoft	1,056	±4	21,098	—
85	—	llama-2-13b-chat開源Meta	1,054	±5	19,729	—
86	—	smollm2-1.7b-instruct開源HuggingFace	1,050	±14	2,377	—
87	—	zephyr-7b-beta開源HuggingFace	1,049	±6	11,322	—
88	—	phi-3-mini-128k-instruct開源Microsoft	1,049	±4	21,637	—
89	—	gemma-7b-it開源Google	1,048	±5	9,175	—
90	—	codellama-34b-instruct開源Meta	1,047	±7	7,510	—
91	—	zephyr-7b-alpha開源HuggingFace	1,046	±13	1,813	—
92	—	llama-3.2-1b-instruct開源Meta	1,044	±7	8,521	—
93	—	gemma-1.1-2b-it開源Google	1,040	±5	11,349	—
94	—	guanaco-33b開源UW	1,040	±10	3,001	—
95	—	codellama-70b-instruct開源Meta	1,038	±16	1,192	—
96	—	stripedhyena-nous-7b開源Together AI	1,034	±7	5,277	—
97	—	mistral-7b-instruct開源Mistral	1,026	±7	9,144	—
98	—	llama-2-7b-chat開源Meta	1,025	±5	14,531	—
99	—	vicuna-7b開源LMSYS	1,021	±7	7,014	—
100	—	qwen1.5-4b-chat開源Alibaba	1,015	±7	7,825	—
101	—	gemma-2b-it開源Google	1,008	±8	4,920	—
102	—	olmo-7b-instruct開源Ai2	993	±8	6,507	—
103	—	koala-13b開源UC Berkeley	980	±7	7,022	—
104	—	chatglm3-6b開源Tsinghua	974	±8	4,762	—
105	—	gpt4all-13b-snoozy開源Nomic AI	973	±14	1,788	—
106	—	mpt-7b-chat開源MosaicML	967	±9	3,997	—
107	—	alpaca-13b開源Stanford	967	±9	5,864	—
108	—	RWKV-4-Raven-14B開源RWKV	949	±9	4,919	—
109	—	chatglm2-6b開源Tsinghua	943	±11	2,710	—
110	—	oasst-pythia-12b開源OpenAssistant	931	±8	6,370	—
111	—	fastchat-t5-3b開源LMSYS	896	±8	4,287	—
112	—	chatglm-6b開源Tsinghua	888	±11	4,985	—
113	—	dolly-v2-12b開源Databricks	882	±11	3,482	—
114	—	llama-13b開源Meta	868	±10	2,446	—
115	—	stablelm-tuned-alpha-7b開源Stability AI	860	±10	3,336	—

其餘 65 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