Web-grounded Sonar for multi-step research questions that need cited reasoning
Models
Every model in the catalog with source-linked pricing, context limits, provider availability, and published benchmark results.
MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing it...
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...
Mistral Small 4 is the next major release in the Mistral Small family, unifying the capabilities of several flagship Mistral models into a single system. It combines strong reasoning from...
Mistral Small 4 is the next major release in the Mistral Small family, unifying the capabilities of several flagship Mistral models into a single system. It combines strong reasoning from...
Qwen3-Next-80B-A3B-Thinking is a reasoning-first chat model in the Qwen3-Next line that outputs structured “thinking” traces by default. It’s designed for hard multi-step problems; math proofs, code synthesis/debugging, logic, and agentic...
GLM-4.6V is a large multimodal model designed for high-fidelity visual understanding and long-context reasoning across images, documents, and mixed media. It supports up to 128K tokens, processes complex page layouts...
GLM-4.5-Air is the lightweight variant of our latest flagship model family, also purpose-built for agent-centric applications. Like GLM-4.5, it adopts the Mixture-of-Experts (MoE) architecture but with a more compact parameter...
OpenAI o3-mini-high is the same model as [o3-mini](/openai/o3-mini) with reasoning_effort set to high. o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and...
Reasoning model for deliberate analysis, multi-step problem solving, and tool use
Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents
Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance...
NVIDIA Nemotron™ 3 Nano Omni is a 30B-A3B open multimodal model designed to function as a perception and context sub-agent in enterprise agent systems. It accepts text, image, video, and...
Affordable GPT-4.1 lane for fast coding help and structured extraction
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...
gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for...
North Mini Code is Cohere's first agentic coding model and the debut of its North family. A sparse mixture-of-experts model with 30B total parameters and 3B active, it is optimized...
Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table...
Qwen3-30B-A3B-Thinking-2507 is a 30B parameter Mixture-of-Experts reasoning model optimized for complex tasks requiring extended multi-step thinking. The model is designed specifically for “thinking mode,” where internal reasoning traces are separated...
Qwen3-Coder-30B-A3B-Instruct is a 30.5B parameter Mixture-of-Experts (MoE) model with 128 experts (8 active per forward pass), designed for advanced code generation, repository-scale understanding, and agentic tool use. Built on the...
Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces. It targets complex tasks across reasoning, code generation, knowledge QA, and multilingual...
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...
Qwen3-VL-30B-A3B-Thinking is a multimodal model that unifies strong text generation with visual understanding for images and videos. Its Thinking variant enhances reasoning in STEM, math, and complex tasks. It excels...
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...
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...
Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.
Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.
Amazon Nova Premier is the most capable of Amazon’s multimodal models for complex reasoning tasks and for use as the best teacher for distilling custom models.
Mistral Medium 3.1 is an updated version of Mistral Medium 3, which is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances...
Mistral Medium 3.1 is an updated version of Mistral Medium 3, which is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances...
Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per...
Mistral Medium 3 is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances state-of-the-art reasoning and multimodal performance with 8× lower cost...
Devstral 2 is a state-of-the-art open-source model by Mistral AI specializing in agentic coding. It is a 123B-parameter dense transformer model supporting a 256K context window. Devstral 2 supports exploring...
LFM2.5-2.6B is a compact reasoning model from Liquid AI. It is suited for agent workflows, data extraction, RAG, and long-context processing. Liquid advises against using it for agentic coding or...
LFM2.5-2.6B is a compact reasoning model from Liquid AI. It is suited for agent workflows, data extraction, RAG, and long-context processing. Liquid advises against using it for agentic coding or...
GPT model for general reasoning, writing, coding, and tool-assisted tasks
Qwen3-VL-8B-Thinking is the reasoning-optimized variant of the Qwen3-VL-8B multimodal model, designed for advanced visual and textual reasoning across complex scenes, documents, and temporal sequences. It integrates enhanced multimodal alignment and...
Qwen3-VL-30B-A3B-Instruct is a multimodal model that unifies strong text generation with visual understanding for images and videos. Its Instruct variant optimizes instruction-following for general multimodal tasks. It excels in perception...
Tiny GPT-4.1 option for classification, routing, and very high-volume tasks
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...
Solar Pro 3 is Upstage's powerful Mixture-of-Experts (MoE) language model. With 102B total parameters and 12B active parameters per forward pass, it delivers exceptional performance while maintaining computational efficiency. Optimized...
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...
GPT model for general reasoning, writing, coding, and tool-assisted tasks
Fast web-grounded Sonar for current answers, citations, and lightweight retrieval
Qwen2.5 72B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabilities in coding and...
This is Mistral AI's flagship model, Mistral Large 2 (version mistral-large-2407). It's a proprietary weights-available model and excels at reasoning, code, JSON, chat, and more. Read the launch announcement [here](https://mistral.ai/news/mistral-large-2407/)....
Deeper Sonar search model with broader retrieval and stronger synthesis
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...
GLM-4.5V is a vision-language foundation model for multimodal agent applications. Built on a Mixture-of-Experts (MoE) architecture with 106B parameters and 12B activated parameters, it achieves state-of-the-art results in video understanding,...
Qwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference. It operates in non-thinking mode and is designed for high-quality instruction following, multilingual understanding, and...
| Model | Creator | Score | Inputs | Context | Input | Output | Released | Compare |
|---|---|---|---|---|---|---|---|---|
| Sonar Reasoning Properplexity/sonar-reasoning-pro | 11.8 | 128K | $2 | $8 | 2024-01-01 | |||
| MiniMax: MiniMax M1minimax/minimax-m1 | 11.7 | 1M | $0.55 | $2.2 | — | |||
| OpenAI: gpt-oss-120b (batch)openai/gpt-oss-120b:batch | 11.6 | 131.072K | $0.03 | $0.136 | — | |||
| Mistral: Mistral Small 4mistralai/mistral-small-2603 | 11.3 | 262.144K | $0.15 | $0.6 | — | |||
| Mistral: Mistral Small 4 (batch)mistralai/mistral-small-2603:batch | 11.3 | 262.144K | $0.075 | $0.3 | — | |||
| Qwen: Qwen3 Next 80B A3B Thinkingqwen/qwen3-next-80b-a3b-thinking | 11.2 | 262.144K | $0.15 | $1.2 | — | |||
| Z.ai: GLM 4.6Vz-ai/glm-4.6v | 11.2 | 131.072K | $0.3 | $0.9 | — | |||
| Z.ai: GLM 4.5 Airz-ai/glm-4.5-air | 11.1 | 131.072K | $0.13 | $0.85 | — | |||
| OpenAI: o3 Mini Highopenai/o3-mini-high | 11.0 | 200K | $1.1 | $4.4 | — | |||
| Mercury 2inception/mercury-2 | 10.8 | 128K | $0.25 | $0.75 | 2026-02-24 | |||
| Gemini 2.5 Flash-Litegoogle/gemini-2.5-flash-lite | 10.4 | 1.04858M | $0.1 | $0.4 | 2025-06-17 | |||
| Google: Gemini 2.5 Flash Lite (batch)google/gemini-2.5-flash-lite:batch | 10.4 | 1.04858M | $0.05 | $0.2 | — | |||
| NVIDIA: Nemotron 3 Nano Omni (free)nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free | 10.3 | 256K | Free | Free | — | |||
| GPT-4.1 miniopenai/gpt-4.1-mini | 10.2 | 1.04758M | $0.4 | $1.6 | 2025-04-14 | |||
| OpenAI: GPT-4.1 Mini (batch)openai/gpt-4.1-mini:batch | 10.2 | 1.04758M | $0.2 | $0.8 | — | |||
| OpenAI: gpt-oss-20b (batch)openai/gpt-oss-20b:batch | 10.0 | 131.072K | $0.024 | $0.112 | — | |||
| Cohere: North Mini Code (free)cohere/north-mini-code:free | 9.9 | 256K | Free | Free | — | |||
| Qwen: Qwen3 VL 235B A22B Instructqwen/qwen3-vl-235b-a22b-instruct | 9.9 | 131.072K | $0.21 | $1.9 | — | |||
| Qwen: Qwen3 30B A3B Thinking 2507qwen/qwen3-30b-a3b-thinking-2507 | 9.8 | 81.92K | $0.2 | $2.4 | — | |||
| Qwen: Qwen3 Coder 30B A3B Instructqwen/qwen3-coder-30b-a3b-instruct | 9.6 | 262.144K | $0.07 | $0.28 | — | |||
| Qwen: Qwen3 Next 80B A3B Instructqwen/qwen3-next-80b-a3b-instruct | 9.6 | 262.144K | $0.09 | $1.1 | — | |||
| Qwen: Qwen3 235B A22Bqwen/qwen3-235b-a22b | 9.5 | 131.072K | $0.455 | $1.82 | — | |||
| Qwen: Qwen3 VL 30B A3B Thinkingqwen/qwen3-vl-30b-a3b-thinking | 9.5 | 262.144K | $0.29 | $1 | — | |||
| Meta: Llama 3.3 70B Instruct (free)meta-llama/llama-3.3-70b-instruct:free | 9.4 | 65.536K | Free | Free | — | |||
| Meta: Llama 4 Maverickmeta-llama/llama-4-maverick | 9.3 | 128K | $0.188 | $0.652 | — | |||
| Mistral: Mistral Large 3 2512mistralai/mistral-large-2512 | 9.3 | 262.144K | $0.5 | $1.5 | — | |||
| Mistral: Mistral Large 3 2512 (batch)mistralai/mistral-large-2512:batch | 9.3 | 262.144K | $0.25 | $0.75 | — | |||
| Amazon: Nova Premier 1.0amazon/nova-premier-v1 | 9.2 | 1M | $2.5 | $12.5 | — | |||
| Mistral: Mistral Medium 3.1mistralai/mistral-medium-3.1 | 9.2 | 131.072K | $0.4 | $2 | — | |||
| Mistral: Mistral Medium 3.1 (batch)mistralai/mistral-medium-3.1:batch | 9.2 | 131.072K | $0.2 | $1 | — | |||
| Qwen: Qwen3 Coder Nextqwen/qwen3-coder-next | 9.2 | 262.144K | $0.12 | $0.8 | — | |||
| Mistral: Mistral Medium 3mistralai/mistral-medium-3 | 9.0 | 131.072K | $0.4 | $2 | — | |||
| Mistral: Devstral 2 2512mistralai/devstral-2512 | 8.6 | 262.144K | $0.4 | $2 | — | |||
| LiquidAI: LFM2.5-2.6Bliquid/lfm-2.5-2.6b | 8.4 | 128K | $0.35 | $0.5 | — | |||
| LiquidAI: LFM2.5-2.6B (free)liquid/lfm-2.5-2.6b:free | 8.4 | 65.536K | Free | Free | — | |||
| GPT-4o (2024-11-20)openai/gpt-4o-2024-11-20 | 8.4 | 128K | $2.5 | $10 | 2024-11-20 | |||
| Qwen: Qwen3 VL 8B Thinkingqwen/qwen3-vl-8b-thinking | 8.2 | 131.072K | $0.18 | $2.1 | — | |||
| Qwen: Qwen3 VL 30B A3B Instructqwen/qwen3-vl-30b-a3b-instruct | 7.9 | 262.144K | $0.15 | $0.6 | — | |||
| GPT-4.1 nanoopenai/gpt-4.1-nano | 7.8 | 1.04758M | $0.1 | $0.4 | 2025-04-14 | |||
| OpenAI: GPT-4.1 Nano (batch)openai/gpt-4.1-nano:batch | 7.8 | 1.04758M | $0.05 | $0.2 | — | |||
| Upstage: Solar Pro 3upstage/solar-pro-3 | 7.8 | 131.072K | $0.15 | $0.6 | — | |||
| Meta: Llama 3.3 70B Instructmeta-llama/llama-3.3-70b-instruct | 7.7 | 131.072K | $0.1 | $0.32 | — | |||
| GPT-4o (2024-08-06)openai/gpt-4o-2024-08-06 | 7.7 | 128K | $2.5 | $10 | 2024-08-06 | |||
| Sonarperplexity/sonar | 7.7 | 128K | $1 | $1 | 2024-01-01 | |||
| Qwen2.5 72B Instructqwen/qwen-2.5-72b-instruct | 7.7 | 32.768K | $0.36 | $0.4 | — | |||
| Mistral Large 2407mistralai/mistral-large-2407 | 7.6 | 131.072K | $2 | $6 | — | |||
| Sonar Properplexity/sonar-pro | 7.6 | 200K | $3 | $15 | 2024-01-01 | |||
| Qwen: Qwen3 30B A3Bqwen/qwen3-30b-a3b | 7.6 | 40.96K | $0.12 | $0.5 | — | |||
| Z.ai: GLM 4.5Vz-ai/glm-4.5v | 7.6 | 65.536K | $0.6 | $1.8 | — | |||
| Qwen: Qwen3 30B A3B Instruct 2507qwen/qwen3-30b-a3b-instruct-2507 | 7.5 | 262.144K | $0.09 | $0.3 | — |