| Signal | Gemma 4 31B (free) | Delta | Nemotron Nano 12B 2 VL (free) |
|---|---|---|---|
Capabilities | 83 | +17 | |
Benchmarks | 86 | +86 | |
Pricing | 100 | -- | |
Context window size | 86 | +5 | |
Recency | 100 | +3 | |
Output Capacity | 75 | -10 | |
| Overall Result | 4 wins | of 6 | 1 wins |
Score History
80.5
current score
Gemma 4 31B (free)
right now
40
current score
NVIDIA
| Metric | Gemma 4 31B (free) | Nemotron Nano 12B 2 VL (free) | Winner |
|---|---|---|---|
| Overall Score | 81 | 40 | Gemma 4 31B (free) |
| Rank | #36 | #242 | Gemma 4 31B (free) |
| Quality Rank | #36 | #242 | Gemma 4 31B (free) |
| Adoption Rank | #36 | #242 | Gemma 4 31B (free) |
| Parameters | 31B | 12B | -- |
| Context Window | 262K | 128K | Gemma 4 31B (free) |
| Pricing | Free | Free | -- |
| Signal Scores | |||
| Capabilities | 83 | 67 | Gemma 4 31B (free) |
| Benchmarks | 86 | -- | Gemma 4 31B (free) |
| Pricing | 100 | 100 | Gemma 4 31B (free) |
| Context window size | 86 | 81 | Gemma 4 31B (free) |
| Recency | 100 | 98 | Gemma 4 31B (free) |
| Output Capacity | 75 | 85 | Nemotron Nano 12B 2 VL (free) |
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 81/100 (rank #36), placing it in the top 88% of all 290 models tracked.
Scores 40/100 (rank #242), placing it in the top 17% of all 290 models tracked.
Gemma 4 31B (free) has a 41-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Both models are priced similarly, so the decision comes down to quality and features rather than cost.
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 4 31B (free) also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (262K 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 (81/100) 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
Gemma 4 31B (free) clearly outperforms Nemotron Nano 12B 2 VL (free) with a significant 40.5-point lead. For most general use cases, Gemma 4 31B (free) is the stronger choice. However, Nemotron Nano 12B 2 VL (free) may still excel in niche scenarios.
Best for Quality
Gemma 4 31B (free)
Marginally better benchmark scores; both are excellent
Best for Cost
Gemma 4 31B (free)
0% lower pricing; better value at scale
Best for Reliability
Gemma 4 31B (free)
Higher uptime and faster response speeds
Best for Prototyping
Gemma 4 31B (free)
Stronger community support and better developer experience
Best for Production
Gemma 4 31B (free)
Wider enterprise adoption and proven at scale
by Google
| Capability | Gemma 4 31B (free) | Nemotron Nano 12B 2 VL (free) |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
NVIDIA
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Gemma 4 31B (free) | Nemotron Nano 12B 2 VL (free) |
|---|---|---|
| Context Window | 262K | 128K |
| Max Output Tokens | 32,768 | 128,000 |
| Open Source | Yes | Yes |
| Created | Apr 2, 2026 | Oct 28, 2025 |