| Signal | GPT-3.5 Turbo (older v0613) | Delta | Qwen3.5 Plus 2026-02-15 |
|---|---|---|---|
Capabilities | 50 | -33 | |
Pricing | 2 | +0 | |
Context window size | 57 | -38 | |
Recency | 0 | -100 | |
Output Capacity | 60 | -20 | |
| Overall Result | 1 wins | of 5 | 4 wins |
0
days ranked higher
0
days
30
days ranked higher
OpenAI
Alibaba
Qwen3.5 Plus 2026-02-15 saves you $96.00/month
That's $1152.00/year compared to GPT-3.5 Turbo (older v0613) at your current usage level of 100K calls/month.
| Metric | GPT-3.5 Turbo (older v0613) | Qwen3.5 Plus 2026-02-15 | Winner |
|---|---|---|---|
| Overall Score | 38 | 85 | Qwen3.5 Plus 2026-02-15 |
| Rank | #293 | #30 | Qwen3.5 Plus 2026-02-15 |
| Quality Rank | #293 | #30 | Qwen3.5 Plus 2026-02-15 |
| Adoption Rank | #293 | #30 | Qwen3.5 Plus 2026-02-15 |
| Parameters | -- | -- | -- |
| Context Window | 4K | 1000K | Qwen3.5 Plus 2026-02-15 |
| Pricing | $1.00/$2.00/M | $0.26/$1.56/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 83 | Qwen3.5 Plus 2026-02-15 |
| Pricing | 2 | 2 | GPT-3.5 Turbo (older v0613) |
| Context window size | 57 | 95 | Qwen3.5 Plus 2026-02-15 |
| Recency | 0 | 100 | Qwen3.5 Plus 2026-02-15 |
| Output Capacity | 60 | 80 | Qwen3.5 Plus 2026-02-15 |
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 38/100 (rank #293), placing it in the top -1% of all 290 models tracked.
Scores 85/100 (rank #30), placing it in the top 90% of all 290 models tracked.
Qwen3.5 Plus 2026-02-15 has a 47-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Qwen3.5 Plus 2026-02-15 offers 39% better value per quality point. At 1M tokens/day, you'd spend $27.30/month with Qwen3.5 Plus 2026-02-15 vs $45.00/month with GPT-3.5 Turbo (older v0613) - a $17.70 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 Plus 2026-02-15 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 ($1.56/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (85/100) 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
Qwen3.5 Plus 2026-02-15 clearly outperforms GPT-3.5 Turbo (older v0613) with a significant 47-point lead. For most general use cases, Qwen3.5 Plus 2026-02-15 is the stronger choice. However, GPT-3.5 Turbo (older v0613) may still excel in niche scenarios.
Best for Quality
GPT-3.5 Turbo (older v0613)
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3.5 Plus 2026-02-15
39% lower pricing; better value at scale
Best for Reliability
GPT-3.5 Turbo (older v0613)
Higher uptime and faster response speeds
Best for Prototyping
GPT-3.5 Turbo (older v0613)
Stronger community support and better developer experience
Best for Production
GPT-3.5 Turbo (older v0613)
Wider enterprise adoption and proven at scale
by OpenAI
by Alibaba
| Capability | GPT-3.5 Turbo (older v0613) | Qwen3.5 Plus 2026-02-15 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
OpenAI
Alibaba
Qwen3.5 Plus 2026-02-15 saves you $1.86/month
That's 44% cheaper than GPT-3.5 Turbo (older v0613) 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 | GPT-3.5 Turbo (older v0613) | Qwen3.5 Plus 2026-02-15 |
|---|---|---|
| Context Window | 4K | 1M |
| Max Output Tokens | 4,096 | 65,536 |
| Open Source | No | No |
| Created | Jan 25, 2024 | Feb 16, 2026 |
Qwen3.5 Plus 2026-02-15 scores 85/100 (rank #30) compared to GPT-3.5 Turbo (older v0613)'s 38/100 (rank #293), giving it a 47-point advantage. Qwen3.5 Plus 2026-02-15 is the stronger overall choice, though GPT-3.5 Turbo (older v0613) may excel in specific areas like certain benchmarks.
GPT-3.5 Turbo (older v0613) is ranked #293 and Qwen3.5 Plus 2026-02-15 is ranked #30 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 Plus 2026-02-15 is cheaper at $1.56/M output tokens vs GPT-3.5 Turbo (older v0613)'s $2.00/M output tokens - 1.3x more expensive. Input token pricing: GPT-3.5 Turbo (older v0613) at $1.00/M vs Qwen3.5 Plus 2026-02-15 at $0.26/M.
Qwen3.5 Plus 2026-02-15 has a larger context window of 1,000,000 tokens compared to GPT-3.5 Turbo (older v0613)'s 4,095 tokens. A larger context window means the model can process longer documents and conversations.