40 models
Ranked by Intelligence Index
53.4

Qwen3.8 Max (0803) is the August 3, 2026 checkpoint of Qwen3.8 Max, the flagship model in Alibaba's Qwen3.8 series and the general-availability successor to the Qwen3.8 Max Preview. It is...

qwen/qwen3.8-max 1M context $2/M input $6/M output
43.8

Kimi K3 is a 2.8T parameter open-weight multimodal reasoning model from Moonshot AI. It is suited for complex coding, knowledge work, and long-horizon agentic workflows, and is particularly strong at...

moonshotai/kimi-k3:batch 1.04858M context $3/M input $15/M output
41.9

GLM-5.3-Flash is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while...

z-ai/glm-5.3-flash 1.04858M context $0.15/M input $0.5/M output
41.9

GLM-5.3-Flash is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while...

z-ai/glm-5.3-flash:batch 1.04858M context $0.075/M input $0.25/M output
41.2

Gemini 3.8 Flash is Google's most intelligent Flash model with significant gains from 3.7 Flash across software engineering, agentic tasks, and multi-step reasoning.

google/gemini-3.8-flash:batch 1.04858M context $0.375/M input $1.875/M output
Reasoning Tools JSON 41.2

Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows

google/gemini-3.8-flash 2026-09-02 1.04858M context $0.75/M input $3.75/M output
17 providers
40.5

Qwen 3.6 Plus builds on a hybrid architecture that combines efficient linear attention with sparse mixture-of-experts routing, enabling strong scalability and high-performance inference. Compared to the 3.5 series, it delivers...

qwen/qwen3.6-plus 1M context $0.325/M input $1.95/M output
40.3

Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team. It is a 2.4-trillion-parameter mixture-of-experts model that accepts text, image, and video input and returns text,...

qwen/qwen3.8-max-0902 1M context $2/M input $6/M output
Reasoning Tools JSON 39.8

Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.

meta/muse-spark-1.2 2026-08-05 1.04858M context $1.25/M input $4.25/M output
14 providers
39.4

Gemini 3.7 Flash is a multimodal model from Google for fast agentic workflows, coding, and complex multi-step reasoning. It is designed for tasks that require responsive performance and reliable multi-step...

google/gemini-3.7-flash:batch 1.04858M context $0.375/M input $1.875/M output
Reasoning Tools JSON 39.4

High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning

google/gemini-3.7-flash 2026-08-13 1.04858M context $0.75/M input $3.75/M output
23 providers
35.7

MiniMax-M3 is a multimodal foundation model from MiniMax. It supports text, image, and video inputs with text output, a 1M-token context window, and is suited for long-horizon agentic work, coding,...

minimax/minimax-m3:free 1.04858M context Free input Free output
Reasoning Tools JSON 34.3

Fast Gemini model balancing multimodal reasoning, tool use, and cost

google/gemini-3.6-flash 2026-07-21 1.04858M context $0.75/M input $3.75/M output
24 providers
Reasoning 34.3

Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.

meta/muse-spark-1.1 2026-04-08 1.04858M context $1.25/M input $4.25/M output
12 providers
34.3

Gemini 3.6 Flash is a high-efficiency model from Google for coding, agentic workflows, and web and app development. It is designed to produce polished outputs with fewer unnecessary edits and...

google/gemini-3.6-flash:batch 1.04858M context $0.375/M input $1.875/M output
33.9

Qwen3.8 27B is an open-weight dense vision-language model from Qwen. It is suited for coding, professional workflows, research, multimodal interaction, and long-running agent tasks, with flexible thinking that can be...

qwen/qwen3.8-27b 1M context $0.42/M input $3/M output
Reasoning Tools JSON 33.0

Fast Gemini model balancing multimodal reasoning, tool use, and cost

google/gemini-3.5-flash 2026-05-19 1.04858M context $1.5/M input $9/M output
31 providers
33.0

Gemini 3.5 Flash is Google's high-efficiency multimodal model, bringing near-Pro level coding and reasoning at Flash-tier cost and speed. It is highly optimized for coding proficiency and parallel agentic execution...

google/gemini-3.5-flash:batch 1.04858M context $0.75/M input $4.5/M output
Reasoning Tools JSON 30.4

Reasoning-first Gemini preview for agentic coding and complex problem solving

google/gemini-3.1-pro-preview 2026-02-19 1.04858M context $2/M input $12/M output
31 providers
30.4

Gemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Building on the multimodal foundation...

google/gemini-3.1-pro-preview:batch 1.04858M context $1/M input $6/M output
29.6

MiniMax-M3 is a multimodal foundation model from MiniMax. It supports text, image, and video inputs with text output, a 1M-token context window, and is suited for long-horizon agentic work, coding,...

minimax/minimax-m3 524.288K context $0.3/M input $1.2/M output
29.6

MiniMax-M3 is a multimodal foundation model from MiniMax. It supports text, image, and video inputs with text output, a 1M-token context window, and is suited for long-horizon agentic work, coding,...

minimax/minimax-m3:batch 524.288K context $0.3/M input $1.2/M output
26.1

Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...

google/gemma-4-26b-a4b-it:free 262.144K context Free input Free output
24.8

Ling 3.0 Flash VL builds on Ling 3.0 Flash (124B total / 5.5B active MoE from InclusionAI), further strengthening its language capabilities while adding native visual perception and advanced visual...

inclusionai/ling-3.0-flash-vl 131.072K context $0.06/M input $0.18/M output
24.8

Ling 3.0 Flash VL builds on Ling 3.0 Flash (124B total / 5.5B active MoE from InclusionAI), further strengthening its language capabilities while adding native visual perception and advanced visual...

inclusionai/ling-3.0-flash-vl:free 262.144K context Free input Free output
24.3

The Qwen3.5 Series 35B-A3B is a native vision-language model designed with a hybrid architecture that integrates linear attention mechanisms and a sparse mixture-of-experts model, achieving higher inference efficiency. Its overall...

qwen/qwen3.5-35b-a3b 256K context $0.312/M input $1.25/M output
22.7

Gemini 3.5 Flash Lite is a high-efficiency model from Google with upgraded agentic capabilities. It is suited for subagents that execute focused tasks within complex, multi-agent workflows.

google/gemini-3.5-flash-lite:batch 1.04858M context $0.15/M input $1.25/M output
Reasoning Tools JSON 22.7

Fast Gemini model balancing multimodal reasoning, tool use, and cost

google/gemini-3.5-flash-lite 2026-07-21 1.04858M context $0.3/M input $2.5/M output
23 providers
21.9

Qwen3.6 27B is a dense 27-billion-parameter language model from the Qwen Team at Alibaba, released in April 2026. It features hybrid multimodal capabilities — accepting text, image, and video inputs...

qwen/qwen3.6-27b 262.144K context $0.3/M input $2/M output
21.8

Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architecture. It uses a unified vision-language design...

qwen/qwen3.5-9b 262.144K context $0.1/M input $0.15/M output
21.8

Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architecture. It uses a unified vision-language design...

qwen/qwen3.5-9b:batch 262.144K context $0.17/M input $0.25/M output
19.1

The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers...

qwen/qwen3.5-397b-a17b 262.144K context $0.55/M input $3.5/M output
18.8

Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. It uses a hybrid sparse mixture-of-experts architecture combining Gated...

qwen/qwen3.6-35b-a3b 262.144K context $0.1/M input $0.9/M output
18.4

Nova 2 Lite is a fast, cost-effective reasoning model for everyday workloads that can process text, images, and videos to generate text. Nova 2 Lite demonstrates standout capabilities in processing...

amazon/nova-2-lite-v1 1M context $0.3/M input $2.5/M output
16.7

Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy...

google/gemini-2.5-pro:batch 1.04858M context $0.625/M input $5/M output
Reasoning Tools JSON 16.7

Google's proven reasoning model for coding, math, and multimodal analysis

google/gemini-2.5-pro 2025-06-17 1.04858M context $1.25/M input $10/M output
29 providers
16.2

The Qwen3.5 122B-A10B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. In terms of...

qwen/qwen3.5-122b-a10b 262.144K context $0.26/M input $2.08/M output
Reasoning Tools JSON 16.0

Low-latency Gemini model for high-volume multimodal and agent workloads

google/gemini-3.1-flash-lite-preview 2026-03-03 1.04858M context $0.25/M input $1.5/M output
13 providers
15.4

Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...

google/gemma-4-31b-it:batch 262.144K context $0.39/M input $0.97/M output
15.4

Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...

google/gemma-4-31b-it:free 262.144K context Free input Free output