Llama-3_3-Nemotron-Super-49B-v1_5-FP8
Llama-3.3-Nemotron-Super-49B-v1.5-FP8 is a significantly upgraded version of Llama-3.3-Nemotron-Super-49B-v1 and is a large language model (LLM) which is a derivative of Meta Llama-3.3-70B-Instruct (AKA the reference model). It is a reasoning model that is post trained for reasoning, human chat preferences, and agentic tasks, such as RAG and tool calling. The model supports a context length of 128K tokens.
Params
49.9 B
Context
131,072
Downloads 30d
256 K
Likes
28
Download history
daily snapshots · 10 days256 K250 K
Jul 28Jul 31Aug 3Aug 6
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f8_e4m3 | 52.0 GB | 65.1 GB | ❌ Won’t fit |
| model.safetensors (bf16, full) | bf16 + 128K ctx | 52.0 GB | 177.4 GB | ❌ Won’t fit |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Run it
copy-paste, exact tags checked against the Hub$ curl -s https://aimodelscomparison.com/api/v1/models/llama-3-3-nemotron-super-49b-v1-5-fp8
{
"hf_id": "nvidia/Llama-3_3-Nemotron-Super-49B-v1_5-FP8",
"params_b": 49.87,
"context_length": 131072,
"license": { "id": "other", "commercial": "unknown" },
"downloads_30d": 255770,
"vram_estimates": [
{ "quant": "f8_e4m3", "gb": 65.1 }
],
"updated_at": "2026-07-28T18:07:09Z"
}
Specifications
- Architecture
- DeciLMForCausalLM
- Parameters
- 49.9 B
- Tensor type
- F8_E4M3
- Context length
- 131,072
- Vocabulary
- 128,256
- Layers / heads
- 80 / 64
- Licence
- other
- First seen on the Hub
- 2025-07-31
- Training datasets
- undisclosed
- Added to our catalog
- 2026-07-28
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