OpenAI vs Qwen (Alibaba) Pricing
Qwen (Alibaba) is cheaper than OpenAI at the entry level: Qwen2.5 Coder 7B Instruct costs $0.090 per 1M output tokens against $0.140 for gpt-oss-20b — 1.6× the price. On current flagships, OpenAI's Daybreak Red costs $75.00/1M output against $6.40/1M for Qwen (Alibaba)'s Qwen-Max. Prices are USD, current as of September 28, 2026.
Per-million-token pricing for OpenAI and Qwen (Alibaba), with side-by-side flagship models, cheapest tiers, and context windows. Pricing data syncs weekly from a continuously-updated model catalog — last updated September 28, 2026.
Who wins on what
Cheapest input tokens
$0.03/1MOpenAI
gpt-oss-20b — $0.03/1M input
Cheapest output tokens
$0.09/1MQwen (Alibaba)
Qwen2.5 Coder 7B Instruct — $0.09/1M output
Longest context window
2.0MOpenAI
gpt-5.4 (>272K context length) — 2.0M input tokens
Lowest average output cost
$1.17/1MQwen (Alibaba)
Provider-wide average across 39 models
Largest model catalog
133 modelsOpenAI
More options to match cost vs capability
Most reasoning models
17 modelsOpenAI
Models with dedicated reasoning / thinking support
Most vision models
18 modelsOpenAI
Models that accept image input
Side-by-side
OpenAI
Full OpenAI pricing →Cheapest input
$0.030
gpt-oss-20b
Cheapest output
$0.140
gpt-oss-20b
Longest context
2.0M
gpt-5.4 (>272K context length)
Avg output / 1M
$30.98
Across catalog
Cheapest cached input
$0.010
GPT-6 Luna
| Model | In/1M | Out/1M | Ctx |
|---|---|---|---|
| GPT-6 Sol VisionReasoningToolsCache | $2.00 | $10.00 | 1.1M |
| GPT-6 Luna VisionReasoningToolsCache | $0.100 | $0.500 | 1.1M |
| GPT-6 Astra VisionReasoningToolsCache | $10.00 | $50.00 | 1.1M |
| Daybreak Red VisionReasoningToolsCache | $12.50 | $75.00 | 400K |
| Daybreak Blue VisionReasoningToolsCache | $4.00 | $20.00 | 1.1M |
| gpt-oss-20b | $0.030 | $0.140 | 131K |
Qwen (Alibaba)
Full Qwen (Alibaba) pricing →Cheapest input
$0.030
Qwen2.5 Coder 7B Instruct
Cheapest output
$0.090
Qwen2.5 Coder 7B Instruct
Longest context
1.0M
Qwen Plus 0728
Avg output / 1M
$1.17
Across catalog
| Model | In/1M | Out/1M | Ctx |
|---|---|---|---|
| Qwen-Max | $1.60 | $6.40 | 33K |
| Qwen3 Max | $1.20 | $6.00 | 256K |
| Qwen3 Coder Plus | $1.00 | $5.00 | 128K |
| Qwen Plus 0728 (thinking) | $0.400 | $4.00 | 1.0M |
| Qwen VL Max | $0.800 | $3.20 | 131K |
| Qwen2.5 Coder 7B Instruct | $0.030 | $0.090 | 33K |
All prices in USD per 1 million tokens. Showing top 6 models per provider, sorted by output cost.
Frequently asked questions
Is OpenAI or Qwen (Alibaba) cheaper?
Qwen (Alibaba) has the cheaper entry point at $0.09/1M output (Qwen2.5 Coder 7B Instruct — $0.09/1M output). Provider-wide, OpenAI averages $30.98/1M output against $1.17/1M for Qwen (Alibaba). Which is cheaper for you depends on which model tier your workload actually needs.
How much do OpenAI and Qwen (Alibaba) cost per 1M tokens?
OpenAI starts at $0.140 per 1M output tokens (gpt-oss-20b), with its current flagship Daybreak Red at $75.00. Qwen (Alibaba) starts at $0.090 (Qwen2.5 Coder 7B Instruct), with Qwen-Max at $6.40. Input tokens cost less than output on both.
Which has the larger context window, OpenAI or Qwen (Alibaba)?
OpenAI — gpt-5.4 (>272K context length) — 2.0M input tokens. For comparison, OpenAI's largest is 2.0M tokens (gpt-5.4 (>272K context length)) and Qwen (Alibaba)'s is 1.0M tokens (Qwen Plus 0728).
Which has more reasoning models, OpenAI or Qwen (Alibaba)?
OpenAI lists 17 reasoning models and Qwen (Alibaba) lists 0. Reasoning models bill their internal thinking as output tokens, so a reasoning call costs several times a standard completion of the same visible length — compare them on total tokens billed, not headline rate.
Should I switch from OpenAI to Qwen (Alibaba) to save money?
Only if the cheaper model still meets your quality bar. Token price is one input; the ones that decide your bill are prompt size, response length, retries and how much conversation history you resend each turn. Model the switch against your real traffic before committing. Prices here are current as of September 28, 2026.
Related comparisons
Run the numbers for your workload.
Calcaas multiplies per-token costs by your real usage patterns — inputs, outputs, retries, and conversation history — across both providers in one model.