Qwen3.7 Plus

qwen/qwen3.7-plus
Featured
VisionToolsJSONReasoning
by Qwen · 2026-06-01

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.

ctx1M tokens
Max output65.5K
Inputtext + image + video
Outputtext
p50 TTFT3.67 s
INPUT$0.35/ 1M tokens
OUTPUT$1.42/ 1M tokens
p50 TTFT3.67 s7d
p95 TTFT10.00 s7d
TRAFFIC3.7Mtokens / 7d

Code samples

Call from any SDK

OpenAI-compatible — keep the SDK you already use

  • OpenAI SDKhttps://api.orcarouter.ai/v1
from 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)

Supported parameters

  • include_reasoning
  • max_tokens
  • presence_penalty
  • reasoning
  • response_format
  • seed
  • structured_outputs
  • temperature
  • tool_choice
  • tools
  • top_p

Pricing

TierInput / 1M tokensOutput / 1M tokensCache read / 1M
256K$0.350$1.42$0.071
$1.06$4.25$0.210
Tier selected by input token count of each request

Cost calculator

Tokens / month10MM
Input share70%%
Estimated / month $6.71 · With prompt caching $5.73

Estimate based on list price

Tiered pricing — this estimate uses base-tier rates.

Token & cost estimator

Input tokens: 20Cost per request: $0.000717

Estimate only — actual token counts depend on the provider's tokenizer.

Performance

p50 TTFT
3.67 s
Output speed
83.6 tok/s
p95 TTFT
10.00 s
Error rate
0%

Public benchmarks

55.7
AA Coding
Better than 77% of models compared
#24 of 106
55.7
AA Intelligence
Better than 75% of models compared
#27 of 110
58.7
AA Math
Better than 40% of models compared
#49 of 81
AndroidWorld
81.0
BFCL-V4
72.9
Deep-Planning
62.3
GPQA Diamond
47.7 index
HLE
34.7
HMMT 2026 Feb
92.9
IFEval
94.6
IMOAnswerBench
86.0
LiveCodeBench
89.6
MathVision
90.3
MCP-Atlas
73.2
MLVU (M-Avg)
87.4
MMLU-Pro
65.7 index
MMMU-Pro
79.0
MRCR-v2 128k
91.7
OCR-Bench-V2(EN)
70.7
OSWorld-Verified
73.3
RealWorldQA
86.9
ScreenSpot Pro
79.0
SpreadSheetBench-v1
86.3
SWE-Pro
57.6
SWE-Verified
77.7
Terminal Bench 2.0-Terminus
70.3
VideoMME (w/ sub.)
88.0
τ²-Bench
42.7 index
Source: artificialanalysis.ai, qwen.ai

How it compares

Qwen3.7 Plusqwen/qwen3-max-previewQwen3.5 397B A17Bqwen/qwen3.5-plus
Input $/M$0.35$0.86$0.17$0.12
Output $/M$1.42$3.44$1.03$0.69
Context1.0M262K33K1.0M
Quality8/108/108/108/10
Compare side-by-sideCompare side-by-sideCompare side-by-sideCompare side-by-side

FAQ

How much does Qwen: Qwen3.7 Plus cost on OrcaRouter?
Qwen: Qwen3.7 Plus is priced at $0.35 per 1M input tokens and $1.42 per 1M output tokens via OrcaRouter. Pricing is pulled live from the routing layer.
What is Qwen: Qwen3.7 Plus's context window?
Qwen: Qwen3.7 Plus supports a context window of 1M tokens. Use long-context features (RAG, summarisation) up to that limit.
How do I call Qwen: Qwen3.7 Plus via the OpenAI SDK?
Set OpenAI base_url to https://api.orcarouter.ai/v1, supply your OrcaRouter API key, and pass model="qwen/qwen3.7-plus" in the chat.completions.create call.
Does OrcaRouter rate-limit Qwen: Qwen3.7 Plus?
Per-model rate limits follow your OrcaRouter plan. Free tiers ship with conservative caps; paid tiers lift them. Check /pricing for current quotas.

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Qwen: Qwen3.7 Plus$0.35/M in3673ms p50via OrcaRouter
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Markdown [![Qwen: Qwen3.7 Plus](https://www.orcarouter.ai/embed/qwen/qwen3.7-plus.svg)](https://www.orcarouter.ai/models/qwen/qwen3.7-plus)

Model card as data

GET /api/public/models/qwen/qwen3.7-plusOpen
Machine-readable:/llms.txt/llms-full.txt