| Signal | Gemma 3n 4B | Delta | R1 Distill Qwen 32B |
|---|---|---|---|
Capabilities | 17 | -33 | |
Pricing | 100 | +0 | |
Context window size | 72 | -- | |
Recency | 68 | +20 | |
Output Capacity | 20 | -55 | |
Benchmarks | 0 | -35 | |
| Overall Result | 2 wins | of 6 | 3 wins |
Score History
40
current score
Gemma 3n 4B
right now
37.3
current score
DeepSeek
Gemma 3n 4B saves you $31.50/month
That's $378.00/year compared to R1 Distill Qwen 32B at your current usage level of 100K calls/month.
| Metric | Gemma 3n 4B | R1 Distill Qwen 32B | Winner |
|---|---|---|---|
| Overall Score | 40 | 37 | Gemma 3n 4B |
| Rank | #271 | #324 | Gemma 3n 4B |
| Quality Rank | #271 | #324 | Gemma 3n 4B |
| Adoption Rank | #271 | #324 | Gemma 3n 4B |
| Parameters | 4B | 32B | -- |
| Context Window | 33K | 33K | -- |
| Pricing | $0.06/$0.12/M | $0.29/$0.29/M | -- |
| Signal Scores | |||
| Capabilities | 17 | 50 | R1 Distill Qwen 32B |
| Pricing | 100 | 100 | Gemma 3n 4B |
| Context window size | 72 | 72 | Gemma 3n 4B |
| Recency | 68 | 48 | Gemma 3n 4B |
| Output Capacity | 20 | 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 40/100 (rank #271), placing it in the top 7% of all 290 models tracked.
Scores 37/100 (rank #324), placing it in the top -11% of all 290 models tracked.
With only a 3-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 69% better value per quality point. At 1M tokens/day, you'd spend $2.70/month with Gemma 3n 4B vs $8.70/month with R1 Distill Qwen 32B - a $6.00 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. 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 ($0.12/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
Gemma 3n 4B and R1 Distill Qwen 32B are extremely close in overall performance (only 2.700000000000003 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
69% 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 | R1 Distill Qwen 32B |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
DeepSeek
Gemma 3n 4B saves you $0.6180/month
That's 71% cheaper than R1 Distill Qwen 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 | Gemma 3n 4B | R1 Distill Qwen 32B |
|---|---|---|
| Context Window | 33K | 33K |
| Max Output Tokens | -- | 32,768 |
| Open Source | Yes | Yes |
| Created | May 20, 2025 | Jan 29, 2025 |