Qwen3.7-Plus is Alibaba's most capable multimodal agent model, unifying vision and language into a single, versatile agent foundation. Built on the Qwen3.7 text backbone, it delivers a comprehensive upgrade in vision-language understanding while retaining full agentic strength in coding, tool use, and productivity workflows. It accepts text, image, and video inputs with text output, and serves a 1M-token context window with up to 65K output tokens - enough to keep long documents, large codebases, screen recordings, and multi-turn agent sessions coherent without truncation. What sets it apart is its ability to operate as a multimodal interactive hybrid agent: it perceives real-world scenes, reads screens and operates GUIs, writes code from visual references, navigates mobile apps end-to-end, and answers visual questions grounded in web knowledge - blending GUI and CLI interactions within a single agent loop. It generalizes across agent scaffolds, performing consistently whether driven through Claude Code, OpenClaw, Qwen Code, or other frameworks, with native function calling, structured outputs, and controllable reasoning depth. This makes it a dependable default for AI coding assistants, computer-use and browser agents, visual QA pipelines, and long-running automation where perception, reasoning, and execution must stay aligned.
OpenAI-compatible — keep the SDK you already use
https://api.orcarouter.ai/v1from openai import OpenAI
client = OpenAI(
base_url="https://api.orcarouter.ai/v1",
api_key="$ORCAROUTER_API_KEY",
)
response = client.chat.completions.create(
model="qwen/qwen3.7-plus",
messages=[{"role": "user", "content": "Hello"}],
)
print(response.choices[0].message.content)include_reasoningmax_tokenspresence_penaltyreasoningresponse_formatseedstructured_outputstemperaturetool_choicetoolstop_p| Tier | Input / 1M tokens | Output / 1M tokens | Cache read / 1M |
|---|---|---|---|
| ≤ 256K | $0.350 | $1.42 | $0.071 |
| ≤ ∞ | $1.06 | $4.25 | $0.210 |
| Tier selected by input token count of each request | |||
Estimate based on list price
Tiered pricing — this estimate uses base-tier rates.
Estimate only — actual token counts depend on the provider's tokenizer.
GET /api/public/models/qwen/qwen3.7-plusOpen @misc{orcarouter_qwen3_7_plus,
title = {Qwen3.7 Plus API},
author = {Qwen},
year = {2026},
howpublished = {OrcaRouter},
url = {https://www.orcarouter.ai/models/qwen/qwen3.7-plus}
}Qwen. (2026). Qwen3.7 Plus API. OrcaRouter. https://www.orcarouter.ai/models/qwen/qwen3.7-plus