OpenAI vs Qwen (Alibaba)
OpenAI (100 models) vs Qwen (Alibaba) (43 models) - compared across composite scores, pricing, capabilities, and context windows.
OpenAI
View all modelsQwen (Alibaba)
View all modelsHead-to-Head: OpenAI vs Qwen (Alibaba) Model Matchups
Capability Comparison
| Capability | OpenAI | Qwen (Alibaba) | Leader |
|---|---|---|---|
Vision | 87/100 | 26/43 | OpenAI |
Reasoning | 76/100 | 28/43 | OpenAI |
Function Calling | 95/100 | 41/43 | OpenAI |
JSON Mode | 98/100 | 42/43 | OpenAI |
Web Search | 82/100 | 0/43 | OpenAI |
Streaming | 98/100 | 43/43 | OpenAI |
Image Output | 4/100 | 0/43 | OpenAI |
Pricing Comparison
| Metric | OpenAI | Qwen (Alibaba) |
|---|---|---|
| Cheapest Input (per 1M tokens) | $0.012 gpt-oss-120b | $0.030 Qwen3.7 Flash |
| Cheapest Output (per 1M tokens) | $0.045 | $0.130 |
| Most Expensive Input (per 1M tokens) | $30.00 GPT-5.5 Pro | $4.00 Qwen3.8 Max Prime |
| Most Expensive Output (per 1M tokens) | $180.00 | $12.00 |
| Free Models | 0 | 0 |
| Max Context Window | 1.1M | 1.0M |
All OpenAI Models (100)
| Model | Score | Input $/M | Output $/M |
|---|---|---|---|
| GPT-5.5 Pro | 93 | $30.00 | $180.00 |
| GPT-5.5 Pro (batch) | 93 | $15.00 | $90.00 |
| GPT-5.5 | 93 | $5.00 | $30.00 |
| GPT-5.4 Pro | 92 | $30.00 | $180.00 |
| GPT-5.4 Pro (batch) | 92 | $15.00 | $90.00 |
| GPT-5.4 | 92 | $2.50 | $15.00 |
| GPT-5.3-Codex | 91 | $1.75 | $14.00 |
| GPT-5.2-Codex | 91 | $1.75 | $14.00 |
| GPT-5.2 Chat | 91 | $1.75 | $14.00 |
| GPT-5.2 Pro | 91 | $21.00 | $168.00 |
| GPT-5.2 Pro (batch) | 91 | $10.50 | $84.00 |
| GPT-5.2 | 91 | $1.75 | $14.00 |
| GPT-5.6 Luna Pro | 89 | $0.200 | $1.20 |
| GPT-5.6 Luna Pro (batch) | 89 | $0.100 | $0.600 |
| GPT-5.6 Luna | 89 | $0.200 | $1.20 |
| GPT-5.6 Luna (batch) | 89 | $0.100 | $0.600 |
| GPT-5.6 Terra Pro | 89 | $2.00 | $12.00 |
| GPT-5.6 Terra Pro (batch) | 89 | $1.00 | $6.00 |
| GPT-5.6 Terra | 89 | $2.00 | $12.00 |
| GPT-5.6 Terra (batch) | 89 | $1.00 | $6.00 |
All Qwen (Alibaba) Models (43)
| Model | Score | Input $/M | Output $/M |
|---|---|---|---|
| Qwen3.5 397B A17B | 71 | $0.500 | $3.60 |
| Qwen3.5-122B-A10B | 70 | $0.260 | $2.08 |
| Qwen3.5-27B | 69 | $0.260 | $2.60 |
| Qwen3.5-35B-A3B | 69 | $0.140 | $1.00 |
| Qwen3.5-9B | 67 | $0.170 | $0.250 |
| Qwen3 235B A22B Thinking 2507 | 65 | $0.450 | $3.50 |
| Qwen3 235B A22B Instruct 2507 | 65 | $0.140 | $0.800 |
| Qwen3.8 Max Prime | 40 | $4.00 | $12.00 |
| Qwen3.8 Omni Flash | 40 | $0.150 | $0.470 |
| Qwen3.8 Max (0902) | 40 | $2.00 | $6.00 |
| Qwen3.8 Flash | 40 | $0.150 | $0.470 |
| Qwen3.8 27B | 40 | $0.150 | $1.88 |
| Qwen3.8 27B (batch) | 40 | $0.160 | $2.00 |
| Qwen3.8 2.4T A95B | 40 | $2.00 | $6.00 |
| Qwen3.7 Flash | 40 | $0.030 | $0.130 |
| Qwen3.7 Plus | 40 | $0.320 | $1.28 |
| Qwen3.7 Plus (batch) | 40 | $0.230 | $0.920 |
| Qwen3.7 Max | 40 | $1.48 | $4.42 |
| Qwen3.5 Plus 2026-04-20 | 40 | $0.300 | $1.80 |
| Qwen3.6 Flash | 40 | $0.188 | $1.13 |
More Provider Comparisons
Compare any two AI providers side-by-side.
OpenAI's premium pricing targets enterprise deployments requiring maximum capability, with their top GPT-5.4 scoring 67/100 versus Qwen3.5-Flash's 60/100. The 144x price difference reflects OpenAI's focus on performance over accessibility, maintaining 57/64 models with function calling versus Qwen's 45/50, plus exclusive web search capabilities in 31 of their 64 models.
Qwen offers 72% of their portfolio as open source compared to OpenAI's 7.8%, making them the clear choice for on-premise deployment and customization. This strategy enables Qwen's $0.090 per 1M token floor (18% cheaper than OpenAI's $0.110) while still achieving competitive average scores of 45/100 versus OpenAI's 49/100.
OpenAI dominates multimodal coverage with 42/64 vision-capable models (65.6%) versus Qwen's 19/50 (38%), plus stronger reasoning support in 34/64 models versus 24/50. The capability gap is most pronounced in combined vision-reasoning tasks where OpenAI's broader portfolio and 7-point top model advantage (67 vs 60) translate to more reliable performance.
For RAG applications requiring real-time data, OpenAI's 48.4% web search coverage across 31 models provides a critical capability Qwen entirely lacks. However, Qwen compensates with stronger open source offerings (36 vs 5 models) and competitive function calling support in 90% of their portfolio versus OpenAI's 89%, making them viable for applications with static knowledge bases.
The 100K token difference represents only a 10% advantage for OpenAI, translating to roughly 40 additional pages of text processing capability. Both providers offer sufficient context for most enterprise use cases, with the real differentiator being OpenAI's superior average model performance (49/100 vs 45/100) and broader capability coverage across their 64-model portfolio.
Both providers offer 2 free models, but Qwen provides a more gradual cost scaling path with their lowest paid tier at $0.090 versus OpenAI's $0.110 per 1M tokens. OpenAI counters with superior model quality (average score 49 vs 45) and comprehensive capabilities, making Qwen ideal for cost-sensitive prototyping while OpenAI suits production deployments requiring their exclusive web search functionality and 65.6% vision model coverage.