Every model, measured.

Start with a research area, drill into a vendor, or page through the full index. Only models with at least one benchmark score appear — a model without a recorded score can’t be ranked.

Vendor:Areas overview speakleash · 253 OpenAI · 85 Google · 71 Qwen · 52 Alibaba · 47 Anthropic · 44 Microsoft · 35 Meta · 30 Mistral · 30 DeepSeek · 28 google · 19 meta-llama · 19 mistralai · 19 Meta AI · 15 CYFRAGOVPL · 14 Zhipu AI · 13 NVIDIA · 10 SpeakLeash · 10 internlm · 10 xAI · 10 ByteDance · 9 Baidu · 8 PLLuM · 8 ibm-granite · 8 microsoft · 8 Amazon · 7 Google DeepMind · 7 MiniMax · 7 Mistral AI · 7 Remek · 7 Shanghai AI Lab · 7 allenai · 7 utter-project · 7 CohereForAI · 6 Microsoft Research · 6 Salesforce · 6 01-ai · 5 Alibaba Cloud · 5 Cohere · 5 Moonshot AI · 5 NousResearch · 5 THUML · 5 deepseek-ai · 5 DeepMind · 4 Facebook AI · 4 IBM · 4 Meituan · 4 Stanford · 4 THUDM · 4 UC San Diego · 4 VikParuchuri · 4 gguf-iq · 4 nvidia · 4 openchat · 4 tiiuae · 4 Allen AI · 3 BAAI · 3 Du et al. · 3 ForgeCode · 3 Fudan University · 3 IDEA Research · 3 Liao et al. · 3 Moonshot.AI · 3 Nam Tuan Ly / NII · 3 OPI-PG · 3 OpenDataLab · 3 ViCoS Lab Ljubljana · 3 Xiaomi · 3 Zhao et al. · 3 gguf · 3 gguf11bv30 · 3 gguf7bv30 · 3 upstage · 3+ 247 smaller vendors (291 models)

§ 01 · Natural Language Processing models

842 models in Natural Language Processing · page 2 of 17.

#	Model	Vendor	Parameters	Architecture	SOTA	Benchmarks	Results
051	RankLLaMA-7B	Castorini (Waterloo)	7B	LLaMA-2-7B (pointwise reranker)	1	1	1
052	DeepSeek R1	DeepSeek	671B MoE	—	—	13	19
053	Voicelab/trurl-2-13b-academic	Voicelab	13B	—	—	3	18
054	berkeley-nest/Starling-LM-7B-alpha	berkeley-nest	7.24B	—	—	3	18
055	meta-llama/Llama-3.3-70B-Instruct	meta-llama	70.6B	—	—	4	18
056	openchat/openchat-3.5-0106	openchat	7.24B	—	—	3	18
057	speakleash/Bielik-11B-v2.0-Instruct	speakleash	11.2B	—	—	3	18
058	speakleash/Bielik-7B-Instruct-v0.1	speakleash	7.24B	—	—	3	18
059	upstage/SOLAR-10.7B-Instruct-v1.0	upstage	10.7B	—	—	3	18
060	01-ai/Yi-1.5-34B-Chat	01-ai	34.4B	—	—	3	17
061	GPT-3.5-turbo	OpenAI	—	—	—	3	17
062	Mixtral-8x22b	Mistral	—	—	—	3	17
063	Qwen/Qwen1.5-72B-Chat	Qwen	72.3B	—	—	3	17
064	Qwen/Qwen2-72B-Instruct	Qwen	72.7B	—	—	3	17
065	Qwen/Qwen2.5-1.5B-Instruct	Qwen	1.54B	—	—	3	17
066	Qwen/Qwen2.5-32B-Instruct	Qwen	32.8B	—	—	3	17
067	Qwen/Qwen2.5-3B-Instruct	Qwen	3.09B	—	—	3	17
068	Qwen/Qwen2.5-7B-Instruct	Qwen	7.62B	—	—	3	17
069	THUDM/glm-4-9b-chat	THUDM	9.4B	—	—	3	17
070	alpindale/WizardLM-2-8x22B (API)	alpindale	141B	—	—	3	17
071	internlm/internlm2-chat-20b	internlm	19.9B	—	—	3	17
072	meta-llama/Llama-3.2-1B-Instruct	meta-llama	1.24B	—	—	3	17
073	meta-llama/Llama-3.2-3B-Instruct	meta-llama	3.21B	—	—	3	17
074	meta-llama/Meta-Llama-3-70B-Instruct	meta-llama	70.6B	—	—	3	17
075	meta-llama/Meta-Llama-3-8B-Instruct	meta-llama	8.03B	—	—	3	17
076	meta-llama/Meta-Llama-3.1-70B-Instruct	meta-llama	70.6B	—	—	3	17
077	microsoft/Phi-4-mini-instruct	microsoft	3.84B	—	—	3	17
078	mistralai/Mistral-7B-Instruct-v0.3	mistralai	7.25B	—	—	3	17
079	mistralai/Mistral-Nemo-Instruct-2407	mistralai	12.2B	—	—	3	17
080	mistralai/Mistral-Small-24B-Instruct-2501	mistralai	23.6B	—	—	3	17
081	mistralai/Mixtral-8x22B-Instruct-v0.1 (API)	mistralai	141B	—	—	3	17
082	mistralai/Mixtral-8x7B-Instruct-v0.1	mistralai	46.7B	—	—	3	17
083	nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16	nvidia	32B	—	—	3	17
084	openchat/openchat-3.5-0106-gemma	openchat	8.54B	—	—	3	17
085	speakleash/Bielik-11B-v2.1-Instruct	speakleash	11.2B	—	—	3	17
086	speakleash/Bielik-11B-v2.2-Instruct	speakleash	11.2B	—	—	3	17
087	speakleash/Bielik-11B-v2.3-Instruct	speakleash	11.2B	—	—	3	17
088	speakleash/Bielik-11B-v2.6-Instruct	speakleash	11.2B	—	—	3	17
089	speakleash/Bielik-11B-v3.0-Instruct	speakleash	11.2B	—	—	3	17
090	utter-project/EuroLLM-9B-Instruct	utter-project	9B	—	—	3	17
091	Kimi-K2.5	Moonshot.AI	—	—	—	10	16
092	Llama-PLLuM-70B-chat	PLLuM	—	—	—	2	16
093	Llama-PLLuM-8B-chat	PLLuM	—	—	—	2	16
094	Mixtral-8x7b	Mistral	—	—	—	2	16
095	PLLuM-12B-chat	PLLuM	—	—	—	2	16
096	PLLuM-12B-nc-chat	PLLuM	—	—	—	2	16
097	PLLuM-8x7B-chat	PLLuM	—	—	—	2	16
098	PLLuM-8x7B-nc-chat	PLLuM	—	—	—	2	16
099	Qwen3.5-122B-A10B	Alibaba	—	—	—	10	16
100	Qwen3.5-27B	Alibaba	—	—	—	10	16