| Signal | Gemma 3n 4B (free) | Delta | R1 Distill Qwen 32B |
|---|---|---|---|
Capabilities | 33 | -17 | |
Pricing | 30 | +30 | |
Context window size | 62 | -10 | |
Recency | 78 | +20 | |
Output Capacity | 55 | -20 | |
| Overall Result | 2 wins | of 5 | 3 wins |
0
days ranked higher
0
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DeepSeek
Gemma 3n 4B (free) saves you $43.50/month
That's $522.00/year compared to R1 Distill Qwen 32B at your current usage level of 100K calls/month.
| Metric | Gemma 3n 4B (free) | R1 Distill Qwen 32B | Winner |
|---|---|---|---|
| Overall Score | 51 | 60 | R1 Distill Qwen 32B |
| Rank | #246 | #206 | R1 Distill Qwen 32B |
| Quality Rank | #246 | #206 | R1 Distill Qwen 32B |
| Adoption Rank | #246 | #206 | R1 Distill Qwen 32B |
| Parameters | 4B | 32B | -- |
| Context Window | 8K | 33K | R1 Distill Qwen 32B |
| Pricing | Free | $0.29/$0.29/M | -- |
| Signal Scores | |||
| Capabilities | 33 | 50 | R1 Distill Qwen 32B |
| Pricing | 30 | 0 | Gemma 3n 4B (free) |
| Context window size | 62 | 72 | R1 Distill Qwen 32B |
| Recency | 78 | 58 | Gemma 3n 4B (free) |
| Output Capacity | 55 | 75 | R1 Distill Qwen 32B |
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 51/100 (rank #246), placing it in the top 16% of all 290 models tracked.
Scores 60/100 (rank #206), placing it in the top 29% of all 290 models tracked.
R1 Distill Qwen 32B has a 8-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
Compare the cost per quality point to find the best value for your specific workload.
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 (free) 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 ($0.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (60/100) correlates with better nuance, coherence, and style in long-form content
R1 Distill Qwen 32B has a moderate advantage with a 8.399999999999999-point lead in composite score. It wins on more signal dimensions, but Gemma 3n 4B (free) has specific strengths that could make it the better choice for certain workflows.
Best for Quality
Gemma 3n 4B (free)
Marginally better benchmark scores; both are excellent
Best for Cost
Gemma 3n 4B (free)
100% lower pricing; better value at scale
Best for Reliability
Gemma 3n 4B (free)
Higher uptime and faster response speeds
Best for Prototyping
Gemma 3n 4B (free)
Stronger community support and better developer experience
Best for Production
Gemma 3n 4B (free)
Wider enterprise adoption and proven at scale
by Google
| Capability | Gemma 3n 4B (free) | R1 Distill Qwen 32B |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
DeepSeek
Gemma 3n 4B (free) saves you $0.8700/month
That's 100% 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 (free) | R1 Distill Qwen 32B |
|---|---|---|
| Context Window | 8K | 33K |
| Max Output Tokens | 2,048 | 32,768 |
| Open Source | Yes | Yes |
| Created | May 20, 2025 | Jan 29, 2025 |
R1 Distill Qwen 32B scores 60/100 (rank #206) compared to Gemma 3n 4B (free)'s 51/100 (rank #246), giving it a 8-point advantage. R1 Distill Qwen 32B is the stronger overall choice, though Gemma 3n 4B (free) may excel in specific areas like cost efficiency.
Gemma 3n 4B (free) is ranked #246 and R1 Distill Qwen 32B is ranked #206 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 (free) is cheaper at $0.00/M output tokens vs R1 Distill Qwen 32B's $0.29/M output tokens — 290.0x more expensive. Input token pricing: Gemma 3n 4B (free) at $0.00/M vs R1 Distill Qwen 32B at $0.29/M.
R1 Distill Qwen 32B has a larger context window of 32,768 tokens compared to Gemma 3n 4B (free)'s 8,192 tokens. A larger context window means the model can process longer documents and conversations.