Gemma 4 12B vs NVIDIA Nemotron 3 Nano 30B A3B BF16
At a Glance
| Compare |  Gemma 4 12BGoogle DeepMind | |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $0.050Openrouter ↗ · Aug 29, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $0.20Openrouter ↗ · Aug 29, 2026 |
| Context windowMaximum documented tokens | 262K | 262K |
| Model facts checked | Sep 3, 2026View model evidence → | Aug 28, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
Side-by-Side Facts
| Field | Gemma 4 12B | NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 |
|---|---|---|
| Developer | Google DeepMind | NVIDIA |
| Family | Gemma 4 | Nvidia Nemotron 3 Nano 30b A3b Bf16 |
| Model | Gemma 4 12B | NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 |
| Version | Gemma 4 12B | NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 |
| Lifecycle | active | active |
| Released | 2026-05-23 | 2025-12-15 |
| Knowledge cutoff | Unknown | 2025-11-28 |
| Input modalities | Text, Image, Video, Audio | Text |
| Output modalities | Text | Text |
| Context window | 262K | 262K |
| Total parameters | 12B | 31.6B |
| Active parameters | Unknown | 3.5B |
| License | apache-2.0 | other |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Together Ai (Standard) | Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | chat, generation, reasoning, tools |
Gemma 4 12B Capabilities
NVIDIA Nemotron 3 Nano 30B A3B BF16 Capabilities
Related Comparisons
All text comparisons →| A | Pair | B | Context |
|---|---|---|---|
Gemma 4 12BGoogle DeepMind | vs |  GPT-6 AstraOpenAI | cross-developer peersimage, text |
Claude Fable 5.1Anthropic | vs | Gemma 4 12BGoogle DeepMind | cross-developer peersimage, text |
Gemini 3.1 ProGoogle DeepMind | vs | Gemma 4 12BGoogle DeepMind | developer peerstext |
 DeepSeek-V4.1-FlashDeepSeek | vs | Gemma 4 12BGoogle DeepMind | cross-developer peersimage, text |
Gemma 4 12BGoogle DeepMind | vs | Grok 4.6xAI | cross-developer peersimage, text |
Gemma 4 12BGoogle DeepMind | vs |  Qwen3.8-MaxQwen | cross-developer peersimage, text, video |
Gemma 4 12BGoogle DeepMind | vs |  Kimi-K3Moonshot AI | cross-developer peersimage, text |
 MiniMax-M3MiniMax | vs | Gemma 4 12BGoogle DeepMind | cross-developer peersimage, text |
Gemma 4 12BGoogle DeepMind | vs |  GLM-5.3Z.ai | cross-developer peerstext |
Gemma 4 12BGoogle DeepMind | vs |  Hy4 previewTencent | cross-developer peerstext |
Seed 2.1 ProByteDance Seed | vs | Gemma 4 12BGoogle DeepMind | cross-developer peersimage, text, video |
Gemma 4 12BGoogle DeepMind | vs |  Mistral Large 3Mistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Gemma 4 12B vs NVIDIA Nemotron 3 Nano 30B A3B BF16 FAQs
Is Gemma 4 12B or NVIDIA Nemotron 3 Nano 30B A3B BF16 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Gemma 4 12B and NVIDIA Nemotron 3 Nano 30B A3B BF16, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Gemma 4 12B or NVIDIA Nemotron 3 Nano 30B A3B BF16?+
Only NVIDIA Nemotron 3 Nano 30B A3B BF16 has a directly sourced input price: $0.050 per million tokens. Only NVIDIA Nemotron 3 Nano 30B A3B BF16 has a directly sourced output price: $0.20 per million tokens.
Which has a larger context window, Gemma 4 12B or NVIDIA Nemotron 3 Nano 30B A3B BF16?+
Neither model has a larger sourced context window in this comparison. Gemma 4 12B is 262K and NVIDIA Nemotron 3 Nano 30B A3B BF16 is 262K.
Which performs better in benchmarks, Gemma 4 12B or NVIDIA Nemotron 3 Nano 30B A3B BF16?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Gemma 4 12B or NVIDIA Nemotron 3 Nano 30B A3B BF16 be self-hosted?+
Both models have the same recorded self-hosting status: supported. Gemma 4 12B is open weight; NVIDIA Nemotron 3 Nano 30B A3B BF16 is open weight.
Can Gemma 4 12B and NVIDIA Nemotron 3 Nano 30B A3B BF16 understand images?+
Gemma 4 12B is documented with image input; NVIDIA Nemotron 3 Nano 30B A3B BF16 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Gemma 4 12B or NVIDIA Nemotron 3 Nano 30B A3B BF16?+
Neither has a larger sourced maximum output. Gemma 4 12B is — and NVIDIA Nemotron 3 Nano 30B A3B BF16 is 1,049K.
Do Gemma 4 12B and NVIDIA Nemotron 3 Nano 30B A3B BF16 support reasoning and tool use?+
Gemma 4 12B: reasoning, tool calling, and image input. NVIDIA Nemotron 3 Nano 30B A3B BF16: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Gemma 4 12B or NVIDIA Nemotron 3 Nano 30B A3B BF16?+
Gemma 4 12B has 1 sourced provider route; NVIDIA Nemotron 3 Nano 30B A3B BF16 has 3, so NVIDIA Nemotron 3 Nano 30B A3B BF16 has broader tracked availability.
Which offers better value, Gemma 4 12B or NVIDIA Nemotron 3 Nano 30B A3B BF16?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.