| Signal | GPT-4 Turbo (older v1106) | Delta | QwQ 32B |
|---|---|---|---|
Capabilities | 50 | -- | |
Benchmarks | 66 | +7 | |
Pricing | 70 | -29 | |
Context window size | 81 | 0 | |
Recency | 0 | -61 | |
Output Capacity | 60 | -25 | |
| Overall Result | 1 wins | of 6 | 4 wins |
Score History
59.8
current score
GPT-4 Turbo (older v1106)
right now
58.9
current score
OpenAI
Alibaba
QwQ 32B saves you $2456.00/month
That's $29472.00/year compared to GPT-4 Turbo (older v1106) at your current usage level of 100K calls/month.
| Metric | GPT-4 Turbo (older v1106) | QwQ 32B | Winner |
|---|---|---|---|
| Overall Score | 60 | 59 | GPT-4 Turbo (older v1106) |
| Rank | #98 | #100 | GPT-4 Turbo (older v1106) |
| Quality Rank | #98 | #100 | GPT-4 Turbo (older v1106) |
| Adoption Rank | #98 | #100 | GPT-4 Turbo (older v1106) |
| Parameters | -- | 32B | -- |
| Context Window | 128K | 131K | QwQ 32B |
| Pricing | $10.00/$30.00/M | $0.15/$0.58/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 50 | GPT-4 Turbo (older v1106) |
| Benchmarks | 66 | 58 | GPT-4 Turbo (older v1106) |
| Pricing | 70 | 99 | QwQ 32B |
| Context window size | 81 | 81 | QwQ 32B |
| Recency | 0 | 61 | QwQ 32B |
| Output Capacity | 60 | 85 | QwQ 32B |
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 60/100 (rank #98), placing it in the top 67% of all 290 models tracked.
Scores 59/100 (rank #100), placing it in the top 66% of all 290 models tracked.
With only a 1-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.
QwQ 32B offers 98% better value per quality point. At 1M tokens/day, you'd spend $10.95/month with QwQ 32B vs $600.00/month with GPT-4 Turbo (older v1106) - a $589.05 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. QwQ 32B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (131K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.58/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (60/100) correlates with better nuance, coherence, and style in long-form content
GPT-4 Turbo (older v1106) and QwQ 32B are extremely close in overall performance (only 0.8999999999999986 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
GPT-4 Turbo (older v1106)
Marginally better benchmark scores; both are excellent
Best for Cost
QwQ 32B
98% lower pricing; better value at scale
Best for Reliability
GPT-4 Turbo (older v1106)
Higher uptime and faster response speeds
Best for Prototyping
GPT-4 Turbo (older v1106)
Stronger community support and better developer experience
Best for Production
GPT-4 Turbo (older v1106)
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-4 Turbo (older v1106) | QwQ 32B |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
OpenAI
Alibaba
QwQ 32B saves you $53.03/month
That's 98% cheaper than GPT-4 Turbo (older v1106) 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 (older v1106) | QwQ 32B |
|---|---|---|
| Context Window | 128K | 131K |
| Max Output Tokens | 4,096 | 131,072 |
| Open Source | No | Yes |
| Created | Nov 6, 2023 | Mar 5, 2025 |
GPT-4 Turbo (older v1106) scores 60/100 (rank #98) compared to QwQ 32B's 59/100 (rank #100), giving it a 1-point advantage. GPT-4 Turbo (older v1106) is the stronger overall choice, though QwQ 32B may excel in specific areas like cost efficiency.
GPT-4 Turbo (older v1106) is ranked #98 and QwQ 32B is ranked #100 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.
QwQ 32B is cheaper at $0.58/M output tokens vs GPT-4 Turbo (older v1106)'s $30.00/M output tokens - 51.7x more expensive. Input token pricing: GPT-4 Turbo (older v1106) at $10.00/M vs QwQ 32B at $0.15/M.
QwQ 32B has a larger context window of 131,072 tokens compared to GPT-4 Turbo (older v1106)'s 128,000 tokens. A larger context window means the model can process longer documents and conversations.