| Signal | GPT-4 Turbo | Delta | Qwen3.5 397B A17B |
|---|---|---|---|
Capabilities | 67 | -17 | |
Benchmarks | 70 | -3 | |
Pricing | 70 | -28 | |
Context window size | 81 | -5 | |
Recency | 1 | -99 | |
Output Capacity | 60 | -20 | |
| Overall Result | 0 wins | of 6 | 6 wins |
Score History
70.2
current score
Qwen3.5 397B A17B
right now
74.3
current score
OpenAI
Alibaba
Qwen3.5 397B A17B saves you $2344.00/month
That's $28128.00/year compared to GPT-4 Turbo at your current usage level of 100K calls/month.
| Metric | GPT-4 Turbo | Qwen3.5 397B A17B | Winner |
|---|---|---|---|
| Overall Score | 70 | 74 | Qwen3.5 397B A17B |
| Rank | #62 | #37 | Qwen3.5 397B A17B |
| Quality Rank | #62 | #37 | Qwen3.5 397B A17B |
| Adoption Rank | #62 | #37 | Qwen3.5 397B A17B |
| Parameters | -- | 397B | -- |
| Context Window | 128K | 262K | Qwen3.5 397B A17B |
| Pricing | $10.00/$30.00/M | $0.39/$2.34/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 83 | Qwen3.5 397B A17B |
| Benchmarks | 70 | 73 | Qwen3.5 397B A17B |
| Pricing | 70 | 98 | Qwen3.5 397B A17B |
| Context window size | 81 | 86 | Qwen3.5 397B A17B |
| Recency | 1 | 100 | Qwen3.5 397B A17B |
| Output Capacity | 60 | 80 | Qwen3.5 397B A17B |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Here's what the scores mean for these two models:
Scores 70/100 (rank #62), placing it in the top 79% of all 290 models tracked.
Scores 74/100 (rank #37), placing it in the top 88% of all 290 models tracked.
With only a 4-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 397B A17B offers 93% better value per quality point. At 1M tokens/day, you'd spend $40.95/month with Qwen3.5 397B A17B vs $600.00/month with GPT-4 Turbo - a $559.05 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 397B A17B 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 ($2.34/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (74/100) 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 397B A17B has a moderate advantage with a 4.099999999999994-point lead in composite score. It wins on more signal dimensions, but GPT-4 Turbo has specific strengths that could make it the better choice for certain workflows.
Best for Quality
GPT-4 Turbo
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3.5 397B A17B
93% lower pricing; better value at scale
Best for Reliability
GPT-4 Turbo
Higher uptime and faster response speeds
Best for Prototyping
GPT-4 Turbo
Stronger community support and better developer experience
Best for Production
GPT-4 Turbo
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-4 Turbo | Qwen3.5 397B A17B |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
OpenAI
Alibaba
Qwen3.5 397B A17B saves you $50.49/month
That's 94% cheaper than GPT-4 Turbo 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-4 Turbo | Qwen3.5 397B A17B |
|---|---|---|
| Context Window | 128K | 262K |
| Max Output Tokens | 4,096 | 65,536 |
| Open Source | No | Yes |
| Created | Apr 9, 2024 | Feb 16, 2026 |
Qwen3.5 397B A17B scores 74/100 (rank #37) compared to GPT-4 Turbo's 70/100 (rank #62), giving it a 4-point advantage. Qwen3.5 397B A17B is the stronger overall choice, though GPT-4 Turbo may excel in specific areas like certain benchmarks.
GPT-4 Turbo is ranked #62 and Qwen3.5 397B A17B is ranked #37 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
Qwen3.5 397B A17B is cheaper at $2.34/M output tokens vs GPT-4 Turbo's $30.00/M output tokens - 12.8x more expensive. Input token pricing: GPT-4 Turbo at $10.00/M vs Qwen3.5 397B A17B at $0.39/M.
Qwen3.5 397B A17B has a larger context window of 262,144 tokens compared to GPT-4 Turbo's 128,000 tokens. A larger context window means the model can process longer documents and conversations.