| Signal | Qwen2.5 VL 32B Instruct | Delta | Qwen3 32B |
|---|---|---|---|
Capabilities | 50 | -17 | |
Pricing | 99 | 0 | |
Context window size | 81 | +8 | |
Recency | 64 | -6 | |
Output Capacity | 20 | -57 | |
| Overall Result | 1 wins | of 5 | 4 wins |
Score History
40
current score
Tied
right now
40
current score
Alibaba
Alibaba
Qwen3 32B saves you $30.00/month
That's $360.00/year compared to Qwen2.5 VL 32B Instruct at your current usage level of 100K calls/month.
| Metric | Qwen2.5 VL 32B Instruct | Qwen3 32B | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #252 | #250 | Qwen3 32B |
| Quality Rank | #252 | #250 | Qwen3 32B |
| Adoption Rank | #252 | #250 | Qwen3 32B |
| Parameters | 32B | 32B | -- |
| Context Window | 128K | 41K | Qwen2.5 VL 32B Instruct |
| Pricing | $0.20/$0.60/M | $0.08/$0.24/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 67 | Qwen3 32B |
| Pricing | 99 | 100 | Qwen3 32B |
| Context window size | 81 | 73 | Qwen2.5 VL 32B Instruct |
| Recency | 64 | 70 | Qwen3 32B |
| Output Capacity | 20 | 77 | Qwen3 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 40/100 (rank #252), placing it in the top 13% of all 290 models tracked.
Scores 40/100 (rank #250), placing it in the top 14% of all 290 models tracked.
With only a 0-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 32B offers 60% better value per quality point. At 1M tokens/day, you'd spend $4.80/month with Qwen3 32B vs $12.00/month with Qwen2.5 VL 32B Instruct - a $7.20 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 32B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (128K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.24/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (40/100) 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
Qwen2.5 VL 32B Instruct and Qwen3 32B are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Qwen2.5 VL 32B Instruct
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3 32B
60% lower pricing; better value at scale
Best for Reliability
Qwen2.5 VL 32B Instruct
Higher uptime and faster response speeds
Best for Prototyping
Qwen2.5 VL 32B Instruct
Stronger community support and better developer experience
Best for Production
Qwen2.5 VL 32B Instruct
Wider enterprise adoption and proven at scale
by Alibaba
| Capability | Qwen2.5 VL 32B Instruct | Qwen3 32B |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Alibaba
Alibaba
Qwen3 32B saves you $0.6480/month
That's 60% cheaper than Qwen2.5 VL 32B 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 | Qwen2.5 VL 32B Instruct | Qwen3 32B |
|---|---|---|
| Context Window | 128K | 41K |
| Max Output Tokens | -- | 40,960 |
| Open Source | Yes | Yes |
| Created | Mar 24, 2025 | Apr 28, 2025 |
Both Qwen2.5 VL 32B Instruct and Qwen3 32B score 40/100, making them extremely close competitors. Choose based on pricing, provider ecosystem, or specific capability requirements.
Qwen2.5 VL 32B Instruct is ranked #252 and Qwen3 32B is ranked #250 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 32B is cheaper at $0.24/M output tokens vs Qwen2.5 VL 32B Instruct's $0.60/M output tokens - 2.5x more expensive. Input token pricing: Qwen2.5 VL 32B Instruct at $0.20/M vs Qwen3 32B at $0.08/M.
Qwen2.5 VL 32B Instruct has a larger context window of 128,000 tokens compared to Qwen3 32B's 40,960 tokens. A larger context window means the model can process longer documents and conversations.