Qwen 3.7 Max
Alibaba's agent-frontier text model with 1M context, tool use, and code-optimized reasoning for long-horizon autonomous workflows.
Overview
What is Qwen 3.7 Max
Qwen 3.7 Max is Alibaba's flagship proprietary text model, released in May 2026 for long-horizon agent workflows. It offers a 1 million-token context window, tool use, reasoning, web search, and code optimization, designed to sustain autonomous execution across thousands of steps without losing coherence.
Running it privately on Venice
On Venice, Qwen 3.7 Max runs under an anonymized privacy tier — your prompts are not stored, profiled, or used for training. You get the same agent-grade capabilities — function calling, reasoning, web search, and code generation — without linking usage to a personal Alibaba Cloud account. It is permissionless access to a frontier coding and automation model with zero retention.
Assessment
Strengths and limitations
- Built for long-horizon agents: sustains coherent reasoning and planning across thousands of tool calls and very long sessions.
- Code-optimized with native support for function calling, reasoning, and web search — ideal for autonomous coding and automation pipelines.
- 1 million-token context window enables large codebase analysis and multi-document RAG without chunking.
- Cross-scaffold generalization: performs consistently across Claude Code, OpenClaw, Qwen Code, and other agent frameworks.
- Competitive price-to-performance for frontier agentic tasks compared to other proprietary APIs.
- Closed proprietary weights: no open-source release, so self-hosting and fine-tuning are impossible.
- Text-only modality: no vision or image input support.
- Benchmark improvements partly reflect increased verbosity and abstention rather than pure reasoning leaps.
- Proprietary to Alibaba Cloud; native integrations outside the Chinese ecosystem may require extra tooling.
- Not an uncensored variant: follows standard alignment and safety policies.
Capabilities
What it supports
- Tool use / function calling
- Vision (image input)
- Reasoning
- Web search
- Code-optimized
- Structured output (JSON schema)
- Audio input
- Video input
- Multiple image inputs
- Log probabilities
Specifications
Datasheet
- Maker
- Alibaba (Qwen Team)
- Released
- May 2026
- Modality
- Text input, text output
- Architecture
- Proprietary (not disclosed)
- Parameters
- Not disclosed
- Open weights
- No — proprietary
- Context window
- 1,000K tokens
- Max output
- 65.536K tokens
- Capabilities
- Function calling, Reasoning, Web search, Code-optimized
- Privacy on Venice
- Anonymized — prompts not stored
- Available on Venice since
- May 2026
API
Call it from your code
Venice exposes an OpenAI-compatible API. Point your base URL at Venice and pass the model id.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen-3-7-max",
"messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
}'Pricing
What it costs on Venice
Billed per token on Venice: $2.70 per 1M input tokens and $8.05 per 1M output tokens.
New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.
Alternatives
How it compares
| Model | Best for | Open weights | Price (Venice) | Context window |
|---|---|---|---|---|
| Qwen 3.7 Max | Long-horizon agents | No | $2.70 / $8.05 | 1M tokens |
| Claude Opus 4.7 | Frontier coding | No | $6 / $30 | 1M tokens |
| DeepSeek V3.2 | Open-weight agentics | Yes | $0.33 / $0.48 | 160K tokens |
| Kimi K2.6 | Open-weight reasoning | Yes | $0.85 / $4.66 | 256K tokens |
| Grok 4.3 | Real-time & web search | No | $1.42 / $2.83 | 1M tokens |
Alibaba's agent-frontier flagship with 1M context, tool use, and code-optimized reasoning.
Use cases
What it is good for
- 01Overnight autonomous coding agents that write, test, and iterate across multi-file projects.
- 02Long-document analysis and retrieval-augmented generation using the full 1M-token context.
- 03Office workflow automation via MCP integrations and multi-agent orchestration.
- 04Research agents that perform deep multi-step analysis over extended sessions.
Prompting
Getting better results
Frame requests as explicit agent tasks with step-by-step tool use for best results.
Feed large codebases or document batches directly into the 1M-token context instead of chunking.
For long-horizon runs, use higher temperature and top_p settings (e.g., temp=1.0, top_p=0.95) to sustain exploration.
Version history
Preceding flagship in the Qwen 3.6 series.
Current — agent-optimized with 1M context and tool-use support.
FAQ
Frequently asked questions
Qwen 3.7 Max is Alibaba's flagship proprietary text model, released in May 2026. It is built for long-horizon agent workflows, offering a 1M-token context, tool use, reasoning, web search, and code optimization.
On Venice it costs $2.70 per 1M input tokens and $8.05 per 1M output tokens, with cached input at $0.27 per 1M. You pay per token as you go with no subscription required.
New Venice accounts receive free credits to try it. Beyond the trial, usage is billed per token; there is no free tier for unlimited use.
No. Qwen 3.7 Max is a proprietary closed-weights model from Alibaba and is not available for self-hosting or fine-tuning. It is also not an uncensored variant. If you need open weights, DeepSeek V3.2 or Kimi K2.6 are alternatives on Venice.
Yes. On Venice it supports function calling, reasoning, web search, and code generation, making it suitable for agent frameworks that require chained tool execution.
Claude Opus 4.7 still leads on raw coding-agent leaderboards and editorial fidelity, while Qwen 3.7 Max offers a larger context window and lower per-token cost for long-horizon agent runs. Choose Opus for one-shot quality and Qwen for sustained autonomous execution.
1,000,000 tokens (1M), with a maximum output of 65,536 tokens per generation.
No. It is a text-only model. It does not process images, charts, or other visual inputs.
Venice runs Qwen 3.7 Max under an anonymized privacy tier: prompts are not stored, profiled, or used for training. You can access it via the Venice app or API without linking to an Alibaba Cloud identity.
Run Qwen 3.7 Max privately
No prompt logging. No data used for training.