AI Models

Perplexity: Sonar Pro

perplexity/sonar-pro

Reasoning

Note: Sonar Pro pricing includes Perplexity search pricing. See [details here](https://docs.perplexity.ai/guides/pricing#detailed-pricing-breakdown-for-sonar-reasoning-pro-and-sonar-pro) For enterprises seeking more advanced capabilities, the Sonar Pro API can handle in-depth, multi-step queries with added extensibility, like...

Input

49 530/M so'm

$3.90

Output

247 650/M so'm

$19.50

data_array 200K context

Perplexity: Sonar Pro Search

perplexity/sonar-pro-search

Reasoning

Exclusively available on the OpenRouter API, Sonar Pro's new Pro Search mode is Perplexity's most advanced agentic search system. It is designed for deeper reasoning and analysis. Pricing is based...

Input

49 530/M so'm

$3.90

Output

247 650/M so'm

$19.50

data_array 200K context

Perplexity: Sonar Reasoning Pro

perplexity/sonar-reasoning-pro

Reasoning

Note: Sonar Pro pricing includes Perplexity search pricing. See [details here](https://docs.perplexity.ai/guides/pricing#detailed-pricing-breakdown-for-sonar-reasoning-pro-and-sonar-pro) Sonar Reasoning Pro is a premier reasoning model powered by DeepSeek R1 with Chain of Thought (CoT). Designed for...

Input

33 020/M so'm

$2.60

Output

132 080/M so'm

$10.40

data_array 128K context

Poolside: Laguna M.1

poolside/laguna-m.1

Reasoning

Laguna M.1 is the flagship coding agent model from [Poolside](https://poolside.ai/), optimized for complex software engineering tasks. Designed for agentic coding workflows, it supports tool calling and reasoning, with a 256K...

Input

3 302/M so'm

$0.26

Output

6 604/M so'm

$0.52

data_array 262K context

Poolside: Laguna M.1 (free)

poolside/laguna-m.1:free

free_breakfast Free Reasoning

Laguna M.1 is the flagship coding agent model from [Poolside](https://poolside.ai/), optimized for complex software engineering tasks. Designed for agentic coding workflows, it supports tool calling and reasoning, with a 256K...

Input

Free

Output

Free

data_array 262K context

Poolside: Laguna XS.2

poolside/laguna-xs.2

Reasoning

Laguna XS.2 is the second-generation model in the XS size class from [Poolside](https://poolside.ai/), their efficient coding agent series. It combines tool calling and reasoning capabilities with a compact footprint, offering...

Input

1 651/M so'm

$0.13

Output

3 302/M so'm

$0.26

data_array 262K context

Poolside: Laguna XS.2 (free)

poolside/laguna-xs.2:free

free_breakfast Free Reasoning

Laguna XS.2 is the second-generation model in the XS size class from [Poolside](https://poolside.ai/), their efficient coding agent series. It combines tool calling and reasoning capabilities with a compact footprint, offering...

Input

Free

Output

Free

data_array 262K context

Prime Intellect: INTELLECT-3

prime-intellect/intellect-3

INTELLECT-3 is a 106B-parameter Mixture-of-Experts model (12B active) post-trained from GLM-4.5-Air-Base using supervised fine-tuning (SFT) followed by large-scale reinforcement learning (RL). It offers state-of-the-art performance for its size across math,...

Input

3 302/M so'm

$0.26

Output

18 161/M so'm

$1.43

data_array 131K context

Qwen2.5 Coder 32B Instruct

qwen/qwen-2.5-coder-32b-instruct

Reasoning

Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen). Qwen2.5-Coder brings the following improvements upon CodeQwen1.5: - Significantly improvements in **code generation**, **code reasoning**...

Input

10 897/M so'm

$0.86

Output

16 510/M so'm

$1.30

data_array 128K context

Qwen: Qwen Plus 0728

qwen/qwen-plus-2025-07-28

Reasoning

Qwen Plus 0728, based on the Qwen3 foundation model, is a 1 million context hybrid reasoning model with a balanced performance, speed, and cost combination.

Input

4 293/M so'm

$0.34

Output

12 878/M so'm

$1.01

data_array 1,000K context

Qwen: Qwen Plus 0728 (thinking)

qwen/qwen-plus-2025-07-28:thinking

Reasoning

Qwen Plus 0728, based on the Qwen3 foundation model, is a 1 million context hybrid reasoning model with a balanced performance, speed, and cost combination.

Input

4 293/M so'm

$0.34

Output

12 878/M so'm

$1.01

data_array 1,000K context

Qwen: Qwen-Plus

qwen/qwen-plus

Qwen-Plus, based on the Qwen2.5 foundation model, is a 131K context model with a balanced performance, speed, and cost combination.

Input

4 293/M so'm

$0.34

Output

12 878/M so'm

$1.01

data_array 1,000K context

Qwen: Qwen2.5 7B Instruct

qwen/qwen-2.5-7b-instruct

Qwen2.5 7B 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...

Input

660/M so'm

$0.05

Output

1 651/M so'm

$0.13

data_array 131K context

Qwen: Qwen2.5 VL 72B Instruct

qwen/qwen2.5-vl-72b-instruct

Vision

Qwen2.5-VL is proficient in recognizing common objects such as flowers, birds, fish, and insects. It is also highly capable of analyzing texts, charts, icons, graphics, and layouts within images.

Input

13 208/M so'm

$1.04

Output

16 510/M so'm

$1.30

data_array 131K context

Qwen: Qwen3 14B

qwen/qwen3-14b

Reasoning

Qwen3-14B is a dense 14.8B parameter causal language model from the Qwen3 series, designed for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for...

Input

1 651/M so'm

$0.13

Output

3 962/M so'm

$0.31

data_array 132K context

Qwen: Qwen3 235B A22B

qwen/qwen3-235b-a22b

Reasoning

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...

Input

7 512/M so'm

$0.59

Output

30 048/M so'm

$2.37

data_array 131K context

Qwen: Qwen3 235B A22B Instruct 2507

qwen/qwen3-235b-a22b-2507

Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following,...

Input

1 486/M so'm

$0.12

Output

1 651/M so'm

$0.13

data_array 262K context

Qwen: Qwen3 235B A22B Thinking 2507

qwen/qwen3-235b-a22b-thinking-2507

Reasoning

Qwen3-235B-A22B-Thinking-2507 is a high-performance, open-weight Mixture-of-Experts (MoE) language model optimized for complex reasoning tasks. It activates 22B of its 235B parameters per forward pass and natively supports up to 262,144...

Input

1 651/M so'm

$0.13

Output

1 651/M so'm

$0.13

data_array 262K context

Qwen: Qwen3 30B A3B

qwen/qwen3-30b-a3b

Reasoning

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...

Input

1 981/M so'm

$0.16

Output

8 255/M so'm

$0.65

data_array 131K context

Qwen: Qwen3 30B A3B Instruct 2507

qwen/qwen3-30b-a3b-instruct-2507

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...

Input

795/M so'm

$0.06

Output

3 187/M so'm

$0.25

data_array 131K context

Qwen: Qwen3 30B A3B Thinking 2507

qwen/qwen3-30b-a3b-thinking-2507

Reasoning

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...

Input

1 321/M so'm

$0.10

Output

6 604/M so'm

$0.52

data_array 131K context

Qwen: Qwen3 32B

qwen/qwen3-32b

Reasoning

Qwen3-32B is a dense 32.8B parameter causal language model from the Qwen3 series, optimized for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for...

Input

1 321/M so'm

$0.10

Output

4 623/M so'm

$0.36

data_array 131K context

Qwen: Qwen3 8B

qwen/qwen3-8b

Reasoning

Qwen3-8B is a dense 8.2B parameter causal language model from the Qwen3 series, designed for both reasoning-heavy tasks and efficient dialogue. It supports seamless switching between "thinking" mode for math,...

Input

826/M so'm

$0.07

Output

6 604/M so'm

$0.52

data_array 131K context

Qwen: Qwen3 Coder 30B A3B Instruct

qwen/qwen3-coder-30b-a3b-instruct

Code

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...

Input

1 156/M so'm

$0.09

Output

4 458/M so'm

$0.35

data_array 160K context