| Signal | Qwen3 14B | Delta | Qwen3 32B |
|---|---|---|---|
Capabilities | 67 | -- | |
Pricing | 100 | +0 | |
Context window size | 73 | -- | |
Recency | 56 | -- | |
Output Capacity | 77 | +7 | |
| Overall Result | 2 wins | of 5 | 0 wins |
Score History
40
current score
Tied
right now
40
current score
Alibaba
Alibaba
| Metric | Qwen3 14B | Qwen3 32B | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #261 | #262 | Qwen3 14B |
| Quality Rank | #261 | #262 | Qwen3 14B |
| Adoption Rank | #261 | #262 | Qwen3 14B |
| Parameters | 14B | 32B | -- |
| Context Window | 132K | 131K | Qwen3 14B |
| Pricing | $0.10/$0.24/M | $0.08/$0.28/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 67 | Qwen3 14B |
| Pricing | 100 | 100 | Qwen3 14B |
| Context window size | 73 | 73 | Qwen3 14B |
| Recency | 56 | 56 | Qwen3 14B |
| Output Capacity | 77 | 70 | Qwen3 14B |
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 #261), placing it in the top 10% of all 290 models tracked.
Scores 40/100 (rank #262), placing it in the top 10% 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 14B offers 6% better value per quality point. At 1M tokens/day, you'd spend $5.10/month with Qwen3 14B vs $5.40/month with Qwen3 32B - a $0.30 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. Qwen3 14B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (132K 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
Qwen3 14B 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
Qwen3 14B
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3 14B
6% lower pricing; better value at scale
Best for Reliability
Qwen3 14B
Higher uptime and faster response speeds
Best for Prototyping
Qwen3 14B
Stronger community support and better developer experience
Best for Production
Qwen3 14B
Wider enterprise adoption and proven at scale
by Alibaba
| Capability | Qwen3 14B | Qwen3 32B |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Alibaba
Alibaba
Qwen3 14B saves you $0.0120/month
That's 3% cheaper than Qwen3 32B 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 | Qwen3 14B | Qwen3 32B |
|---|---|---|
| Context Window | 132K | 131K |
| Max Output Tokens | 40,960 | 16,384 |
| Open Source | Yes | Yes |
| Created | Apr 28, 2025 | Apr 28, 2025 |