165 models
Ranked by Design Arena: codecategories
1006.0

Qwen3-235B-A22B is a 235B parameter mixture-of-experts (MoE) model developed by Qwen, activating 22B parameters per forward pass. It supports seamless switching between a "thinking" mode for complex reasoning, math, and...

qwen/qwen3-235b-a22b 131.072K context $0.455/M input $1.82/M output
1005.0

gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized...

openai/gpt-oss-120b:free 131.072K context Free input Free output
Tools JSON 992.0

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
28 providers
992.0

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
Reasoning Tools JSON 974.0

Fast o-series model for compact reasoning, coding, and tool use

openai/o4-mini 2025-04-16 200K context $1.1/M input $4.4/M output
22 providers
974.0

OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities. It supports tool use and demonstrates competitive reasoning...

openai/o4-mini:batch 200K context $0.55/M input $2.2/M output
Tools JSON 961.0

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
22 providers
961.0

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
961.0

gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized...

openai/gpt-oss-120b:batch 131.072K context $0.03/M input $0.136/M output
940.0

Qwen3, the latest generation in the Qwen large language model series, features both dense and mixture-of-experts (MoE) architectures to excel in reasoning, multilingual support, and advanced agent tasks. Its unique...

qwen/qwen3-30b-a3b 40.96K context $0.12/M input $0.5/M output
905.0

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
878.0

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 $0.188/M input $0.652/M output
Tools JSON 859.0

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
26 providers
859.0

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
788.0

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