| Signal | GPT-5 Nano | Delta | Qwen3 30B A3B Instruct 2507 |
|---|---|---|---|
Capabilities | 100 | +50 | |
Benchmarks | 58 | +58 | |
Pricing | 0 | +0 | |
Context window size | 89 | +3 | |
Recency | 90 | +2 | |
Output Capacity | 85 | -5 | |
| Overall Result | 5 wins | of 6 | 1 wins |
30
days higher
0
days
0
days higher
OpenAI
Alibaba
Qwen3 30B A3B Instruct 2507 saves you $1.00/month
That's $12.00/year compared to GPT-5 Nano at your current usage level of 100K calls/month.
| Metric | GPT-5 Nano | Qwen3 30B A3B Instruct 2507 | Winner |
|---|---|---|---|
| Overall Score | 62 | 40 | GPT-5 Nano |
| Rank | #91 | #214 | GPT-5 Nano |
| Quality Rank | #91 | #214 | GPT-5 Nano |
| Adoption Rank | #91 | #214 | GPT-5 Nano |
| Parameters | -- | 30B | -- |
| Context Window | 400K | 262K | GPT-5 Nano |
| Pricing | $0.05/$0.40/M | $0.09/$0.30/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 50 | GPT-5 Nano |
| Benchmarks | 58 | -- | GPT-5 Nano |
| Pricing | 0 | 0 | GPT-5 Nano |
| Context window size | 89 | 86 | GPT-5 Nano |
| Recency | 90 | 88 | GPT-5 Nano |
| Output Capacity | 85 | 90 | Qwen3 30B A3B Instruct 2507 |
Our score (0-100) is driven by benchmark performance (90%) from LMArena Elo, 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 62/100 (rank #91), placing it in the top 69% of all 290 models tracked.
Scores 40/100 (rank #214), placing it in the top 27% of all 290 models tracked.
GPT-5 Nano has a 22-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
GPT-5 Nano offers 13% better value per quality point. At 1M tokens/day, you'd spend $5.85/month with Qwen3 30B A3B Instruct 2507 vs $6.75/month with GPT-5 Nano - a $0.90 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 30B A3B Instruct 2507 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (400K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.30/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (62/100) 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
GPT-5 Nano clearly outperforms Qwen3 30B A3B Instruct 2507 with a significant 21.9-point lead. For most general use cases, GPT-5 Nano is the stronger choice. However, Qwen3 30B A3B Instruct 2507 may still excel in niche scenarios.
Best for Quality
GPT-5 Nano
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3 30B A3B Instruct 2507
13% lower pricing; better value at scale
Best for Reliability
GPT-5 Nano
Higher uptime and faster response speeds
Best for Prototyping
GPT-5 Nano
Stronger community support and better developer experience
Best for Production
GPT-5 Nano
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5 Nano | Qwen3 30B A3B Instruct 2507 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Alibaba
Qwen3 30B A3B Instruct 2507 saves you $0.0480/month
That's 8% cheaper than GPT-5 Nano 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-5 Nano | Qwen3 30B A3B Instruct 2507 |
|---|---|---|
| Context Window | 400K | 262K |
| Max Output Tokens | 128,000 | 262,144 |
| Open Source | No | Yes |
| Created | Aug 7, 2025 | Jul 29, 2025 |
GPT-5 Nano scores 62/100 (rank #91) compared to Qwen3 30B A3B Instruct 2507's 40/100 (rank #214), giving it a 22-point advantage. GPT-5 Nano is the stronger overall choice, though Qwen3 30B A3B Instruct 2507 may excel in specific areas like cost efficiency.
GPT-5 Nano is ranked #91 and Qwen3 30B A3B Instruct 2507 is ranked #214 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from LMArena, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
Qwen3 30B A3B Instruct 2507 is cheaper at $0.30/M output tokens vs GPT-5 Nano's $0.40/M output tokens - 1.3x more expensive. Input token pricing: GPT-5 Nano at $0.05/M vs Qwen3 30B A3B Instruct 2507 at $0.09/M.
GPT-5 Nano has a larger context window of 400,000 tokens compared to Qwen3 30B A3B Instruct 2507's 262,144 tokens. A larger context window means the model can process longer documents and conversations.