| Signal | Gemma 3 12B | Delta | Qwen3.5-Flash |
|---|---|---|---|
Capabilities | 50 | -33 | |
Pricing | 0 | 0 | |
Context window size | 81 | -14 | |
Recency | 63 | -37 | |
Output Capacity | 20 | -60 | |
Benchmarks | 0 | -67 | |
| Overall Result | 0 wins | of 6 | 6 wins |
0
days higher
0
days
30
days higher
Alibaba
Gemma 3 12B saves you $9.00/month
That's $108.00/year compared to Qwen3.5-Flash at your current usage level of 100K calls/month.
| Metric | Gemma 3 12B | Qwen3.5-Flash | Winner |
|---|---|---|---|
| Overall Score | 56 | 79 | Qwen3.5-Flash |
| Rank | #248 | #85 | Qwen3.5-Flash |
| Quality Rank | #248 | #85 | Qwen3.5-Flash |
| Adoption Rank | #248 | #85 | Qwen3.5-Flash |
| Parameters | 12B | -- | -- |
| Context Window | 131K | 1000K | Qwen3.5-Flash |
| Pricing | $0.04/$0.13/M | $0.07/$0.26/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 83 | Qwen3.5-Flash |
| Pricing | 0 | 0 | Qwen3.5-Flash |
| Context window size | 81 | 95 | Qwen3.5-Flash |
| Recency | 63 | 100 | Qwen3.5-Flash |
| Output Capacity | 20 | 80 | Qwen3.5-Flash |
| Benchmarks | -- | 67 | Qwen3.5-Flash |
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 56/100 (rank #248), placing it in the top 15% of all 290 models tracked.
Scores 79/100 (rank #85), placing it in the top 71% of all 290 models tracked.
Qwen3.5-Flash has a 24-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Gemma 3 12B offers 48% better value per quality point. At 1M tokens/day, you'd spend $2.55/month with Gemma 3 12B vs $4.88/month with Qwen3.5-Flash - a $2.32 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 3 12B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1000K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.13/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (79/100) 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
Qwen3.5-Flash clearly outperforms Gemma 3 12B with a significant 23.60000000000001-point lead. For most general use cases, Qwen3.5-Flash is the stronger choice. However, Gemma 3 12B may still excel in niche scenarios.
Best for Quality
Gemma 3 12B
Marginally better benchmark scores; both are excellent
Best for Cost
Gemma 3 12B
48% lower pricing; better value at scale
Best for Reliability
Gemma 3 12B
Higher uptime and faster response speeds
Best for Prototyping
Gemma 3 12B
Stronger community support and better developer experience
Best for Production
Gemma 3 12B
Wider enterprise adoption and proven at scale
by Google
| Capability | Gemma 3 12B | Qwen3.5-Flash |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Alibaba
Gemma 3 12B saves you $0.2010/month
That's 47% cheaper than Qwen3.5-Flash 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 3 12B | Qwen3.5-Flash |
|---|---|---|
| Context Window | 131K | 1M |
| Max Output Tokens | -- | 65,536 |
| Open Source | Yes | No |
| Created | Mar 13, 2025 | Feb 25, 2026 |
Qwen3.5-Flash scores 79/100 (rank #85) compared to Gemma 3 12B's 56/100 (rank #248), giving it a 24-point advantage. Qwen3.5-Flash is the stronger overall choice, though Gemma 3 12B may excel in specific areas like cost efficiency.
Gemma 3 12B is ranked #248 and Qwen3.5-Flash is ranked #85 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 3 12B is cheaper at $0.13/M output tokens vs Qwen3.5-Flash's $0.26/M output tokens - 2.0x more expensive. Input token pricing: Gemma 3 12B at $0.04/M vs Qwen3.5-Flash at $0.07/M.
Qwen3.5-Flash has a larger context window of 1,000,000 tokens compared to Gemma 3 12B's 131,072 tokens. A larger context window means the model can process longer documents and conversations.