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 · Computer Code models

152 models in Computer Code · page 2 of 4.

#	Model	Vendor	Parameters	Architecture	SOTA	Benchmarks	Results
051	Qwen3-VL-235B-A22B-Thinking	Qwen	—	—	—	12	12
052	Qwen3-VL-8B-Instruct	Qwen	—	—	—	12	12
053	o1	OpenAI	—	—	—	10	12
054	DeepSeek-V3.2-Speciale	DeepSeek	—	—	—	5	11
055	Gemma-3-27b	Google	27B	transformer	—	5	11
056	Llama 3 70B	Meta	—	LLM	—	11	11
057	MiniCPM-o 4.5-Instruct	—	—	—	—	11	11
058	MiniMax-M2.5	MiniMaxAI	—	—	—	5	11
059	Claude 3.7 Sonnet	Anthropic	—	—	—	10	10
060	DeepSeek-R1-0528	DeepSeek	—	—	—	4	10
061	GPT-5	OpenAI	—	—	—	9	10
062	SmoLM2 (1.7B)	—	—	—	—	10	10
063	Step-3.5-Flash Base	—	—	—	—	10	10
064	DeepSeek-Coder-V2-Instruct	DeepSeek	Unknown	MoE Transformer	—	7	9
065	DeepSeek-v3-0324	DeepSeek	—	—	—	3	9
066	GPT-4.1	OpenAI	—	—	—	9	9
067	Gemini 2.5 Flash	—	—	—	—	9	9
068	Llama-4-Scout	Meta	109B total / 17B active (16 experts)	Mixture-of-Experts Transformer	—	3	9
069	Qwen2.5-Coder 32B	Alibaba	32B	Dense Transformer	—	8	9
070	GPT-4o mini	OpenAI	—	Multimodal LLM	—	7	8
071	Gemini 3 Flash	Google	Undisclosed	—	—	7	8
072	Kimi-K2	Moonshot.AI	—	—	—	2	8
073	o1-preview	OpenAI	Undisclosed	Reasoning LLM	—	8	8
074	o3-mini	OpenAI	—	—	—	8	8
075	Apertus-70B-Instruct	—	—	—	—	7	7
076	Aria	—	—	—	—	7	7
077	NVIDIA-Nemotron-3-Super-120B-A12B-BF16	—	—	—	—	6	6
078	Qwen3-Coder-Next	Qwen	—	—	—	6	6
079	Step-3.5-Flash	—	—	—	—	6	6
080	DeepSeek-V4-Flash Max	DeepSeek	—	—	—	5	5
081	GPT-4.1 mini	OpenAI	—	transformer	—	5	5
082	GPT-4.5 Preview	OpenAI	—	—	—	5	5
083	Gemini 2.5 Flash	Google	—	—	—	4	5
084	Gemini 2.5 Pro	Google	—	—	—	4	5
085	Gemma 3 (27B, IT)	—	—	—	—	5	5
086	Kimi K2.5	Moonshot AI	Undisclosed	—	—	4	5
087	MiniMax M2.5	MiniMax	229B	—	—	3	5
088	Qwen2.5-Plus	—	—	—	—	5	5
089	StarCoder2 15B	BigCode	15B	Dense Transformer	—	5	5
090	BLT-Entropy 8B	—	—	—	—	4	4
091	Claude Opus 4.6	Anthropic	Undisclosed	—	—	3	4
092	Claude Sonnet 4.5	Anthropic	Undisclosed	—	—	2	4
093	Claude Sonnet 4.5	Anthropic	—	—	—	4	4
094	Codestral 22B	Mistral	Unknown	Dense Transformer	—	4	4
095	GPT-4.5	OpenAI	Undisclosed	—	—	3	4
096	Gemma 4 31B	Google	—	—	—	4	4
097	Grok 2	xAI	—	—	—	4	4
098	Llama 3.1 70B	Meta	—	—	—	4	4
099	MiMo-V2.5-Pro	—	—	—	—	4	4
100	NVIDIA-Nemotron-3-Nano-30B-A3B-BF16	—	—	—	—	4	4