| Signal | o1-pro | Delta | Qwen3.5-Flash |
|---|---|---|---|
Capabilities | 67 | -17 | |
Benchmarks | 82 | +15 | |
Pricing | 100 | +100 | |
Context window size | 84 | -11 | |
Recency | 66 | -34 | |
Output Capacity | 83 | +3 | |
| Overall Result | 3 wins | of 6 | 3 wins |
5
days ranked higher
0
days
25
days ranked higher
OpenAI
Alibaba
Qwen3.5-Flash saves you $44980.50/month
That's $539766.00/year compared to o1-pro at your current usage level of 100K calls/month.
| Metric | o1-pro | Qwen3.5-Flash | Winner |
|---|---|---|---|
| Overall Score | 77 | 79 | Qwen3.5-Flash |
| Rank | #100 | #80 | Qwen3.5-Flash |
| Quality Rank | #100 | #80 | Qwen3.5-Flash |
| Adoption Rank | #100 | #80 | Qwen3.5-Flash |
| Parameters | -- | -- | -- |
| Context Window | 200K | 1000K | Qwen3.5-Flash |
| Pricing | $150.00/$600.00/M | $0.07/$0.26/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 83 | Qwen3.5-Flash |
| Benchmarks | 82 | 67 | o1-pro |
| Pricing | 100 | 0 | o1-pro |
| Context window size | 84 | 95 | Qwen3.5-Flash |
| Recency | 66 | 100 | Qwen3.5-Flash |
| Output Capacity | 83 | 80 | o1-pro |
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 77/100 (rank #100), placing it in the top 66% of all 290 models tracked.
Scores 79/100 (rank #80), placing it in the top 73% of all 290 models tracked.
With only a 3-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Qwen3.5-Flash offers 100% better value per quality point. At 1M tokens/day, you'd spend $4.88/month with Qwen3.5-Flash vs $11250.00/month with o1-pro - a $11245.13 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. Qwen3.5-Flash also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1000K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.26/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (79/100) 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
o1-pro and Qwen3.5-Flash are extremely close in overall performance (only 2.9000000000000057 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
o1-pro
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3.5-Flash
100% lower pricing; better value at scale
Best for Reliability
o1-pro
Higher uptime and faster response speeds
Best for Prototyping
o1-pro
Stronger community support and better developer experience
Best for Production
o1-pro
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | o1-pro | Qwen3.5-Flash |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
Alibaba
Qwen3.5-Flash saves you $989.57/month
That's 100% cheaper than o1-pro 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 | o1-pro | Qwen3.5-Flash |
|---|---|---|
| Context Window | 200K | 1M |
| Max Output Tokens | 100,000 | 65,536 |
| Open Source | No | No |
| Created | Mar 19, 2025 | Feb 25, 2026 |
Qwen3.5-Flash scores 79/100 (rank #80) compared to o1-pro's 77/100 (rank #100), giving it a 3-point advantage. Qwen3.5-Flash is the stronger overall choice, though o1-pro may excel in specific areas like certain benchmarks.
o1-pro is ranked #100 and Qwen3.5-Flash is ranked #80 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.
Qwen3.5-Flash is cheaper at $0.26/M output tokens vs o1-pro's $600.00/M output tokens - 2307.7x more expensive. Input token pricing: o1-pro at $150.00/M vs Qwen3.5-Flash at $0.07/M.
Qwen3.5-Flash has a larger context window of 1,000,000 tokens compared to o1-pro's 200,000 tokens. A larger context window means the model can process longer documents and conversations.