| Signal | Gemma 3n 4B | Delta | Qwen2.5 7B Instruct |
|---|---|---|---|
Capabilities | 17 | -33 | |
Pricing | 0 | 0 | |
Context window size | 72 | -- | |
Recency | 76 | +39 | |
Output Capacity | 20 | -55 | |
Benchmarks | 0 | -39 | |
| Overall Result | 1 wins | of 6 | 4 wins |
13
days higher
2
days
15
days higher
Alibaba
Gemma 3n 4B saves you $5.00/month
That's $60.00/year compared to Qwen2.5 7B Instruct at your current usage level of 100K calls/month.
| Metric | Gemma 3n 4B | Qwen2.5 7B Instruct | Winner |
|---|---|---|---|
| Overall Score | 46 | 45 | Gemma 3n 4B |
| Rank | #278 | #279 | Gemma 3n 4B |
| Quality Rank | #278 | #279 | Gemma 3n 4B |
| Adoption Rank | #278 | #279 | Gemma 3n 4B |
| Parameters | 4B | 7B | -- |
| Context Window | 33K | 33K | -- |
| Pricing | $0.02/$0.04/M | $0.04/$0.10/M | -- |
| Signal Scores | |||
| Capabilities | 17 | 50 | Qwen2.5 7B Instruct |
| Pricing | 0 | 0 | Qwen2.5 7B Instruct |
| Context window size | 72 | 72 | Gemma 3n 4B |
| Recency | 76 | 36 | Gemma 3n 4B |
| Output Capacity | 20 | 75 | Qwen2.5 7B Instruct |
| Benchmarks | -- | 39 | Qwen2.5 7B Instruct |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 46/100 (rank #278), placing it in the top 4% of all 290 models tracked.
Scores 45/100 (rank #279), placing it in the top 4% 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.
Gemma 3n 4B offers 57% better value per quality point. At 1M tokens/day, you'd spend $0.90/month with Gemma 3n 4B vs $2.10/month with Qwen2.5 7B Instruct - a $1.20 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. Gemma 3n 4B 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 ($0.04/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (46/100) correlates with better nuance, coherence, and style in long-form content
Gemma 3n 4B and Qwen2.5 7B Instruct are extremely close in overall performance (only 0.6000000000000014 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Gemma 3n 4B
Marginally better benchmark scores; both are excellent
Best for Cost
Gemma 3n 4B
57% lower pricing; better value at scale
Best for Reliability
Gemma 3n 4B
Higher uptime and faster response speeds
Best for Prototyping
Gemma 3n 4B
Stronger community support and better developer experience
Best for Production
Gemma 3n 4B
Wider enterprise adoption and proven at scale
by Google
| Capability | Gemma 3n 4B | Qwen2.5 7B Instruct |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Alibaba
Gemma 3n 4B saves you $0.1080/month
That's 56% cheaper than Qwen2.5 7B 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 | Gemma 3n 4B | Qwen2.5 7B Instruct |
|---|---|---|
| Context Window | 33K | 33K |
| Max Output Tokens | -- | 32,768 |
| Open Source | Yes | Yes |
| Created | May 20, 2025 | Oct 16, 2024 |
Gemma 3n 4B scores 46/100 (rank #278) compared to Qwen2.5 7B Instruct's 45/100 (rank #279), giving it a 1-point advantage. Gemma 3n 4B is the stronger overall choice, though Qwen2.5 7B Instruct may excel in specific areas like certain benchmarks.
Gemma 3n 4B is ranked #278 and Qwen2.5 7B Instruct is ranked #279 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
Gemma 3n 4B is cheaper at $0.04/M output tokens vs Qwen2.5 7B Instruct's $0.10/M output tokens - 2.5x more expensive. Input token pricing: Gemma 3n 4B at $0.02/M vs Qwen2.5 7B Instruct at $0.04/M.
Gemma 3n 4B has a larger context window of 32,768 tokens compared to Qwen2.5 7B Instruct's 32,768 tokens. A larger context window means the model can process longer documents and conversations.