AI Models Directory

OpenRouter-style model index with deep metadata: pricing, context windows, architecture, and parameters.

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Showing 181 - 195 of 235 matching models from 548 total for query "reasoning"

Qwen
Budget tiertext -> text

Qwen3-Coder-480B-A35B-Instruct is a Mixture-of-Experts (MoE) code generation model developed by the Qwen team.

Long contextTool callingBudget input
Context262K
Input$0.22 / 1M
Output$1.00 / 1M
Qwen
Budget tiertext -> text

Qwen3-Coder-480B-A35B-Instruct is a Mixture-of-Experts (MoE) code generation model developed by the Qwen team.

Long contextTool callingBudget input
Context262K
Input$0.22 / 1M
Output$1.80 / 1M
Qwen
Budget tiertext -> text

Qwen3-Coder-480B-A35B-Instruct is a Mixture-of-Experts (MoE) code generation model developed by the Qwen team.

Long contextTool callingBudget input
Context262K
Input$0.00 / 1M
Output$0.00 / 1M
Qwen
Budget tiertext -> text

Qwen: Qwen3 Max

Long context

Qwen3-Max is an updated release built on the Qwen3 series, offering major improvements in reasoning, instruction following, multilingual support, and long-tail knowledge coverage...

Long contextTool callingBudget input
Context262K
Input$0.78 / 1M
Output$3.90 / 1M
Qwen
Budget tiertext -> text

Qwen3-Max-Thinking is the flagship reasoning model in the Qwen3 series, designed for high-stakes cognitive tasks that require deep, multi-step reasoning.

Long contextReasoningTool calling
Context262K
Input$0.78 / 1M
Output$3.90 / 1M
Qwen
Budget tiertext -> text

Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces.

Long contextTool callingBudget input
Context262K
Input$0.09 / 1M
Output$1.10 / 1M
Qwen
Budget tiertext -> text

Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces.

Long contextTool callingBudget input
Context262K
Input$0.00 / 1M
Output$0.00 / 1M
Qwen
Budget tiertext -> text

Qwen3-Next-80B-A3B-Thinking is a reasoning-first chat model in the Qwen3-Next line that outputs structured “thinking” traces by default.

Long contextReasoningTool calling
Context131K
Input$0.10 / 1M
Output$0.78 / 1M
Qwen
Budget tiertext + image -> text

Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video.

Long contextTool callingVision
Context262K
Input$0.20 / 1M
Output$0.88 / 1M
Qwen
Budget tiertext + image -> text

Qwen3-VL-235B-A22B Thinking is a multimodal model that unifies strong text generation with visual understanding across images and video.

Long contextReasoningTool calling
Context131K
Input$0.26 / 1M
Output$2.60 / 1M
Qwen
Budget tiertext + image -> text

Qwen3-VL-30B-A3B-Thinking is a multimodal model that unifies strong text generation with visual understanding for images and videos.

Long contextReasoningTool calling
Context131K
Input$0.13 / 1M
Output$1.56 / 1M
Qwen
Budget tiertext + image -> text

Qwen3-VL-32B-Instruct is a large-scale multimodal vision-language model designed for high-precision understanding and reasoning across text, images, and video.

Long contextTool callingVision
Context131K
Input$0.10 / 1M
Output$0.42 / 1M
Qwen
Budget tiertext + image -> text

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,...

Long contextReasoningTool calling
Context131K
Input$0.12 / 1M
Output$1.36 / 1M
Qwen
Budget tiertext + image + video -> text

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,...

Long contextReasoningTool calling
Context262K
Input$0.39 / 1M
Output$2.34 / 1M
Qwen
Budget tiertext + image + video -> text

The Qwen3.5 native vision-language series Plus models are built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models,...

1M+ contextReasoningTool calling
Context1M
Input$0.26 / 1M
Output$1.56 / 1M