109 models
Ranked by Design Arena: uicomponent
976.0

GPT-4.1 Mini is a mid-sized model delivering performance competitive with GPT-4o at substantially lower latency and cost. It retains a 1 million token context window and scores 45.1% on hard...

openai/gpt-4.1-mini:batch 1.04758M context $0.2/M input $0.8/M output
976.0

Affordable GPT-4.1 lane for fast coding help and structured extraction

openai/gpt-4.1-mini 2025-04-14 1.04758M context $0.4/M input $1.6/M output
25 providers
931.0

For tasks that demand low latency, GPT‑4.1 nano is the fastest and cheapest model in the GPT-4.1 series. It delivers exceptional performance at a small size with its 1 million...

openai/gpt-4.1-nano:batch 1.04758M context $0.05/M input $0.2/M output
931.0

Tiny GPT-4.1 option for classification, routing, and very high-volume tasks

openai/gpt-4.1-nano 2025-04-14 1.04758M context $0.1/M input $0.4/M output
20 providers
921.0

Mistral-Small-3.2-24B-Instruct-2506 is an updated 24B parameter model from Mistral optimized for instruction following, repetition reduction, and improved function calling. Compared to the 3.1 release, version 3.2 significantly improves accuracy on...

mistralai/mistral-small-3.2-24b-instruct 128K context $0.075/M input $0.2/M output
914.0

Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward...

meta-llama/llama-4-maverick 128K context $0.2/M input $0.696/M output
900.0

GPT-4o ("o" for "omni") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as...

openai/gpt-4o:batch 128K context $1.25/M input $5/M output
Tools 900.0

Omni-era GPT for multimodal chat, practical coding, and general assistants

openai/gpt-4o 2024-05-13 128K context $2.5/M input $10/M output
23 providers
782.0

Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...

meta-llama/llama-4-scout 327.68K context $0.1/M input $0.3/M output