| Signal | GPT-3.5 Turbo Instruct | Delta | R1 Distill Qwen 32B |
|---|---|---|---|
Capabilities | 33 | -17 | |
Pricing | 98 | -2 | |
Context window size | 57 | -14 | |
Recency | 0 | -48 | |
Output Capacity | 60 | -15 | |
Benchmarks | 0 | -35 | |
| Overall Result | 0 wins | of 6 | 6 wins |
Score History
35
current score
R1 Distill Qwen 32B
right now
37.3
current score
OpenAI
DeepSeek
R1 Distill Qwen 32B saves you $206.50/month
That's $2478.00/year compared to GPT-3.5 Turbo Instruct at your current usage level of 100K calls/month.
| Metric | GPT-3.5 Turbo Instruct | R1 Distill Qwen 32B | Winner |
|---|---|---|---|
| Overall Score | 35 | 37 | R1 Distill Qwen 32B |
| Rank | #330 | #324 | R1 Distill Qwen 32B |
| Quality Rank | #330 | #324 | R1 Distill Qwen 32B |
| Adoption Rank | #330 | #324 | R1 Distill Qwen 32B |
| Parameters | -- | 32B | -- |
| Context Window | 4K | 33K | R1 Distill Qwen 32B |
| Pricing | $1.50/$2.00/M | $0.29/$0.29/M | -- |
| Signal Scores | |||
| Capabilities | 33 | 50 | R1 Distill Qwen 32B |
| Pricing | 98 | 100 | R1 Distill Qwen 32B |
| Context window size | 57 | 72 | R1 Distill Qwen 32B |
| Recency | 0 | 48 | R1 Distill Qwen 32B |
| Output Capacity | 60 | 75 | R1 Distill Qwen 32B |
| Benchmarks | -- | 35 | R1 Distill Qwen 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%). Learn more about our methodology.
Scores 35/100 (rank #330), placing it in the top -13% of all 290 models tracked.
Scores 37/100 (rank #324), placing it in the top -11% of all 290 models tracked.
With only a 2-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.
R1 Distill Qwen 32B offers 83% better value per quality point. At 1M tokens/day, you'd spend $8.70/month with R1 Distill Qwen 32B vs $52.50/month with GPT-3.5 Turbo Instruct - a $43.80 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
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. R1 Distill Qwen 32B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (33K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.29/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (37/100) correlates with better nuance, coherence, and style in long-form content
GPT-3.5 Turbo Instruct and R1 Distill Qwen 32B are extremely close in overall performance (only 2.299999999999997 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
GPT-3.5 Turbo Instruct
Marginally better benchmark scores; both are excellent
Best for Cost
R1 Distill Qwen 32B
83% lower pricing; better value at scale
Best for Reliability
GPT-3.5 Turbo Instruct
Higher uptime and faster response speeds
Best for Prototyping
GPT-3.5 Turbo Instruct
Stronger community support and better developer experience
Best for Production
GPT-3.5 Turbo Instruct
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-3.5 Turbo Instruct | R1 Distill Qwen 32B |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
OpenAI
DeepSeek
R1 Distill Qwen 32B saves you $4.23/month
That's 83% cheaper than GPT-3.5 Turbo Instruct 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 Instruct | R1 Distill Qwen 32B |
|---|---|---|
| Context Window | 4K | 33K |
| Max Output Tokens | 4,096 | 32,768 |
| Open Source | No | Yes |
| Created | Sep 28, 2023 | Jan 29, 2025 |