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Ali Qwen CLI free plan discontinued, coding plan increased to $50/month

2026-04-13
Ali Qwen CLI free plan discontinued, coding plan increased to $50/month

The free plan of the Alibaba Cloud Tongyi Qianwen CLI tool will soon be discontinued. The coding plan is being adjusted to a single Pro plan, priced at USD 50 per month. This change reflects the shift of large-model vendors from free trials to commercial monetization, and developers need to reassess their API call costs.

Alibaba Qwen CLI Free Plan Discontinued, Coding Plan Raised to $50/Month

Alibaba Cloud’s Qwen (Tongyi Qianwen) recently announced on its GitHub homepage that its free Qwen CLI plan will be discontinued soon. At the same time, the previously multi-tiered Coding Plan has undergone major changes — now only a single Pro plan remains, priced at $50 per month.

This change significantly affects individual developers and small teams that rely on Qwen’s free quota for development and testing. Since last year, major AI model providers have been tightening their free access policies, and Alibaba’s move marks another milestone — the era of “free lunches” for large models is quickly coming to an end.

Screenshot of Qwen CLI official announcement showing the discontinuation notice

Free Plan Discontinued, Only Pro Coding Plan Remains

According to the announcement on Qwen CLI’s GitHub homepage, the free plan will be discontinued soon. Although no specific date has been given, the tone of the announcement suggests this will occur within the next few weeks. Alibaba Cloud recommends that developers currently using the free quota migrate to paid plans as soon as possible.

More notably, the Coding Plan has been overhauled. Previously, Alibaba Cloud offered multiple tiers, including entry-level low-priced options suitable for individual developers and small projects. Now all those options have been removed, leaving only the $50/month Pro plan (roughly 360 RMB).

This price positions Qwen in the mid-to-high range of China’s AI model API market. In comparison:

  • DeepSeek: Charges by tokens, typically less than $50/month
  • ByteDance Doubao: Offers pay-as-you-go and subscription options, with lower entry-level prices
  • Baidu Wenxin: Includes free quota and multiple paid tiers
  • OpenAI GPT-4: Charges by tokens; monthly cost at moderate usage ranges from $30–$100

Alibaba’s logic is clear: cut low-price and free options, steer users toward higher-value plans. For enterprise clients, $50/month is affordable, but for individuals and small teams, this barrier is relatively high.

Why Tighten Free Access Now?

There are several practical reasons behind providers’ tightening of free usage policies:

1. Inference Costs Remain High

Though inference efficiency is improving, large-scale free calls still represent significant costs. For large-parameter models like Qwen, inference is far more expensive than for smaller models. The more free quotas offered, the heavier the provider’s subsidy burden.

2. Rising Commercialization Pressure

2024 marks a crucial year for AI model commercialization. Free strategies help attract users early but hinder sustainable ecosystems long-term. As a public company, Alibaba Cloud faces financial reporting pressure, making this policy shift inevitable.

3. Clearer User Segmentation

Removing low-priced tiers effectively filters users: those willing to pay $50/month are either businesses with stable budgets or professional developers needing strong model performance. Their higher lifetime value (LTV) makes them better long-term customers.

4. Changing Competitive Landscape

DeepSeek’s rapid rise has intensified domestic AI model competition. With ultra-low inference costs and pay-as-you-go pricing, DeepSeek attracts price-sensitive users. Alibaba Cloud may have decided it’s more strategic to focus on mid-to-high-end customers than to fight DeepSeek in the low-cost segment.

Real Impact on Developers

This adjustment affects different types of developers in different ways:

Individual Developers and Students

Most affected. Previously, they could use free quotas for experimentation, learning, and small projects. Now, they must either pay or migrate to other platforms. $50/month is significant for students, many of whom will move to cheaper options like DeepSeek or Doubao.

Small Startup Teams

They must reassess costs. If projects are at an early stage with low API usage, $50/month is acceptable. But as calls increase, token-based pricing may be more economical. Teams will need to compare pricing across platforms to find the best value.

Enterprise Clients

Impact is minimal. For companies with stable budgets, $50/month is trivial. Businesses care more about service stability, API compatibility, and support quality. Alibaba Cloud has advantages in these areas but must keep proving its worth.

Comparison chart of API pricing across AI models

How to Respond: Migration and Cost Optimization

If you’re using Qwen CLI’s free plan, consider the following options:

1. Migrate to Other Platforms

DeepSeek: Best price-to-performance ratio, charges by tokens, extremely inexpensive; ideal for cost-sensitive developers.

ByteDance Doubao: Offers free quotas and several paid tiers; good API compatibility.

Baidu Wenxin: Has a free quota; suitable for light usage.

OpenAI Hub: Single Key for all major models, supports direct mainland connections, compatible with OpenAI format. Ideal for switching between multiple models without managing separate API keys.

2. Optimize API Call Strategy

If you choose to stay with Qwen, lower costs by:

Using Batch API: Alibaba Cloud offers Batch interfaces for bulk task processing, about 50% cheaper than real-time calls.

import openai

# Use OpenAI Hub to call Qwen Batch API
client = openai.OpenAI(
    api_key="your-openai-hub-key",
    base_url="https://api.openai-hub.com/v1"
)

# Prepare batch tasks
batch_input = [
    {"custom_id": "task-1", "method": "POST", "url": "/v1/chat/completions",
     "body": {"model": "qwen-plus", "messages": [{"role": "user", "content": "Explain quantum computing"}]}},
    {"custom_id": "task-2", "method": "POST", "url": "/v1/chat/completions",
     "body": {"model": "qwen-plus", "messages": [{"role": "user", "content": "Write a poem"}]}}
]

# Upload file and create batch job
with open("batch_input.jsonl", "w") as f:
    for item in batch_input:
        f.write(json.dumps(item) + "\n")

file = client.files.create(file=open("batch_input.jsonl", "rb"), purpose="batch")
batch = client.batches.create(input_file_id=file.id, endpoint="/v1/chat/completions", completion_window="24h")

print(f"Batch ID: {batch.id}")

Cache Common Queries: For frequently repeated requests, cache results at the application level to avoid redundant API calls.

Use Smaller Models: For simpler tasks, switch to Qwen-Turbo or Qwen-Plus instead of Qwen-Max — costs drop 30–50%.

3. Combine Multiple Models

Different models excel in different areas. Choose based on task type:

  • Simple conversations: DeepSeek or Doubao
  • Complex reasoning: Qwen-Max or GPT-4
  • Code generation: Claude or Qwen-Coder

Platforms like OpenAI Hub allow you to call all models with one API key, simplifying integration.

import openai

client = openai.OpenAI(
    api_key="your-openai-hub-key",
    base_url="https://api.openai-hub.com/v1"
)

# Simple task using DeepSeek
response = client.chat.completions.create(
    model="deepseek-chat",
    messages=[{"role": "user", "content": "What’s the weather like today?"}]
)

# Complex task using Qwen-Max
response = client.chat.completions.create(
    model="qwen-max",
    messages=[{"role": "user", "content": "Analyze the time complexity of this code"}]
)

Is the Era of Free AI Models Over?

Alibaba’s recent adjustment reflects the industry’s shift from “burning cash for users” to “commercial monetization.” But this doesn’t mean free access will vanish completely — it will simply become more limited and harder to get.

For developers, this is a clear signal: don’t build your business entirely on one provider’s free quota. A healthier approach is:

  1. Multi-platform backup: Don’t put all your eggs in one basket
  2. Cost monitoring: Track API expenses in real time to avoid overspending
  3. Optimization: Use caching, batching, etc., to reduce call frequency
  4. Model selection: Not every task needs the most powerful model

In the long run, API prices will continue to fall, but free quotas will keep shrinking. Developers must adapt to this trend — learning to balance cost and performance.

References

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