Qwen: Qwen3.7 Flash
Qwen3.7 Flash is a vision-language reasoning model from Alibaba. It is suited for multimodal agents, visual coding, search, and computer interaction, with strengths in object recognition, spatial understanding, and real-world...
Anyone in the Project can @-mention Qwen: Qwen3.7 Flash with the team's shared context - pooled credits, one chat, one memory.
Starter is free forever - 1 Project, 100 credits/month, 1 MCP. No card.
Verdict
Best for
- Cost-sensitive multimodal analysis
- Long-context document processing under budget
- Video frame extraction and reasoning
- Exploratory visual Q&A workflows
- High-volume text generation at scale
Strengths
The million-token context window supports full-document ingestion without chunking, and multimodal support extends to video—rare at this price point. At $0.03 input and $0.13 output per Mtok, it undercuts most frontier models by 5-10x while maintaining text, image, and video capabilities. The pricing structure makes it viable for high-throughput pipelines where cost per request dominates infrastructure decisions.
Trade-offs
No public benchmark data means you're flying blind on accuracy relative to established models like GPT-4o, Claude Sonnet 4.5, or Gemini 1.5 Pro. Early-stage models often lag on nuanced reasoning, complex instruction-following, and edge-case handling. Video processing quality is unproven in production settings. If your workflow demands verified performance on MMLU, HumanEval, or vision benchmarks, wait for independent evals before committing production traffic.
Specifications
- Provider
- qwen
- Category
- llm
- Context length
- 1,000,000 tokens
- Max output
- 65,536 tokens
- Modalities
- text, image, video
- License
- proprietary
- Released
- 2026-07-27
Pricing
- Input
- $0.03/Mtok
- Output
- $0.13/Mtok
- Model ID
qwen/qwen3.7-flash
Per-token prices show what the model costs upstream. On Switchy your team draws from one shared org credit pool - one plan, one balance for everyone.
Team cost calculator
5 seats · 80 msgs/day
Switchy meters this against your org's shared credit pool - one plan, one balance for everyone.
Providers
Performance
Benchmarks
Works well with
Top MCPs
Compatibility data comes from first-party telemetry; once we have enough co-usage signal, top MCPs for this model will appear here.
How Switchy teams use it
Starter prompts
Extract Video Key Frames
Analyze this video and identify the 5 most important frames that capture key events or transitions. For each frame, provide a timestamp and a one-sentence description of what makes it significant.Open in a Project →
Long Document Q&A
I've uploaded a 200-page technical specification. Answer these questions by referencing specific sections: What are the three main security requirements? Which sections conflict on authentication protocols?Open in a Project →
Batch Image Annotation
I'm providing 20 product images. For each, return: (1) primary object category, (2) background type, (3) any visible defects or quality issues. Format as a numbered list.Open in a Project →
Multimodal Meeting Notes
Here's a meeting transcript and the slide deck shown during the call. Create a structured summary with: key decisions, action items with owners, and unresolved questions. Reference specific slides by number.Open in a Project →
Cost-Optimized Code Review
Review this 5,000-line Python codebase for: security vulnerabilities, performance bottlenecks, and violations of PEP 8 style guidelines. Prioritize findings by severity and provide line numbers.Open in a Project →
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