| Signal | o3 Deep Research | Delta | Qwen3 Max Thinking |
|---|---|---|---|
Capabilities | 100 | +33 | |
Benchmarks | 88 | +88 | |
Pricing | 40 | +36 | |
Context window size | 84 | -2 | |
Recency | 100 | -- | |
Output Capacity | 83 | +8 | |
| Overall Result | 4 wins | of 6 | 1 wins |
30
days ranked higher
0
days
0
days ranked higher
OpenAI
Alibaba
Qwen3 Max Thinking saves you $2727.00/month
That's $32724.00/year compared to o3 Deep Research at your current usage level of 100K calls/month.
| Metric | o3 Deep Research | Qwen3 Max Thinking | Winner |
|---|---|---|---|
| Overall Score | 92 | 82 | o3 Deep Research |
| Rank | #8 | #66 | o3 Deep Research |
| Quality Rank | #8 | #66 | o3 Deep Research |
| Adoption Rank | #8 | #66 | o3 Deep Research |
| Parameters | -- | -- | -- |
| Context Window | 200K | 262K | Qwen3 Max Thinking |
| Pricing | $10.00/$40.00/M | $0.78/$3.90/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 67 | o3 Deep Research |
| Benchmarks | 88 | -- | o3 Deep Research |
| Pricing | 40 | 4 | o3 Deep Research |
| Context window size | 84 | 86 | Qwen3 Max Thinking |
| Recency | 100 | 100 | o3 Deep Research |
| Output Capacity | 83 | 75 | o3 Deep Research |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 92/100 (rank #8), placing it in the top 98% of all 290 models tracked.
Scores 82/100 (rank #66), placing it in the top 78% of all 290 models tracked.
o3 Deep Research has a 10-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
Qwen3 Max Thinking offers 91% better value per quality point. At 1M tokens/day, you'd spend $70.20/month with Qwen3 Max Thinking vs $750.00/month with o3 Deep Research - a $679.80 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Qwen3 Max Thinking also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (262K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($3.90/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (92/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
o3 Deep Research has a moderate advantage with a 9.700000000000003-point lead in composite score. It wins on more signal dimensions, but Qwen3 Max Thinking has specific strengths that could make it the better choice for certain workflows.
Best for Quality
o3 Deep Research
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3 Max Thinking
91% lower pricing; better value at scale
Best for Reliability
o3 Deep Research
Higher uptime and faster response speeds
Best for Prototyping
o3 Deep Research
Stronger community support and better developer experience
Best for Production
o3 Deep Research
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | o3 Deep Research | Qwen3 Max Thinking |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Alibaba
Qwen3 Max Thinking saves you $59.92/month
That's 91% cheaper than o3 Deep Research at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | o3 Deep Research | Qwen3 Max Thinking |
|---|---|---|
| Context Window | 200K | 262K |
| Max Output Tokens | 100,000 | 32,768 |
| Open Source | No | No |
| Created | Oct 10, 2025 | Feb 9, 2026 |
o3 Deep Research scores 92/100 (rank #8) compared to Qwen3 Max Thinking's 82/100 (rank #66), giving it a 10-point advantage. o3 Deep Research is the stronger overall choice, though Qwen3 Max Thinking may excel in specific areas like cost efficiency.
o3 Deep Research is ranked #8 and Qwen3 Max Thinking is ranked #66 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
Qwen3 Max Thinking is cheaper at $3.90/M output tokens vs o3 Deep Research's $40.00/M output tokens - 10.3x more expensive. Input token pricing: o3 Deep Research at $10.00/M vs Qwen3 Max Thinking at $0.78/M.
Qwen3 Max Thinking has a larger context window of 262,144 tokens compared to o3 Deep Research's 200,000 tokens. A larger context window means the model can process longer documents and conversations.