nvidia · gemma4 · based on google/gemma-4-31B-it
Gemma-4-31B-IT-NVFP4
Gemma-4-31B-IT-NVFP4 by nvidia: a 20.9B-parameter dense open-weight model under the other license and vision.
1,638,603 downloads · 567 likes · Model card · synced 2026-09-19
Specifications
- Parameters
- 20.9B
- Architecture
- dense · gemma4
- Layers
- 60
- Hidden size
- 5,376
- KV heads · head dim
- 16 · 256
- Vocabulary
- 262,144
- Native dtype
- —
- Context window
- 262,144 tokens
- Released
- 2026-04-02
- Last modified on Hub
- 2026-07-13
Features & licensing
- License
- other
- Commercial use
- No
- Modalities
- text, vision
- Tool / function calling
- No
- Reasoning mode
- No
- Languages
- EN
- Quantised variants on Hub
- GGUF, GPTQ
- Pipeline
- text-generation
Task fit
Editorial scores (0–100) used by the recommendation engine.
- Chat70
- RAG / Q&A70
- Code70
- Summarisation70
- Extraction70
- Agents70
Hardware to run Gemma-4-31B-IT-NVFP4
Weights need about 46 GB at FP16, 24 GB at INT8 and 14 GB at INT4. The KV cache adds roughly 983 MB per 1,000 tokens per request. For a reference workload of 5 requests per second with 1,500 input and 300 output tokens, total GPU memory is around 39.9 GB, which fits on 1 × NVIDIA A100 (80 GB).
| Configuration | VRAM | Utilisation | Est. first token | Cloud / month |
|---|---|---|---|---|
| 2 × NVIDIA L4 (24 GB) | 48 GB | 83 % | ~0.5 s | $1,168 |
| 1 × NVIDIA L40S (48 GB) | 48 GB | 83 % | ~0.2 s | $1,387 |
| 1 × NVIDIA A100 (80 GB)recommended | 80 GB | 50 % | ~0.1 s | $2,336 |
| 1 × NVIDIA H100 (80 GB) | 80 GB | 50 % | ~0.0 s | $3,285 |
Estimates only. Run an assessment for your own traffic.
Auto-imported from Hugging Face. Architecture, license and feature data are synced from the model repository; the task-fit scores below are provisional defaults until a curator reviews them.