Side-by-side analysis of Google Text Embedding 004, Nvidia Llama 3 3 Nemotron Super 49b V1 5 across performance, benchmarks, capabilities, and infrastructure requirements.
Source: inferbase.ai
Side-by-side analysis of Google Text Embedding 004, Nvidia Llama 3 3 Nemotron Super 49b V1 5 across performance, benchmarks, capabilities, and infrastructure requirements.
Text Embedding 004 is a language model from Google. It features a 2K context window.
Llama-3.3-Nemotron-Super-49B-v1.5 is a 49B-parameter, English-centric reasoning/chat model derived from Meta’s Llama-3.3-70B-Instruct with a 128K context. It’s post-trained for agentic workflows (RAG, tool calling) via SFT across math, code, science, and multi-turn chat, followed by multiple RL stages; Reward-aware Preference Optimization (RPO) for alignment, RL with Verifiable Rewards (RLVR) for step-wise reasoning, and iterative DPO to refine tool-use behavior.
| Specification | Text Embedding 004 | Llama 3.3 Nemotron Super 49B V1.5 |
|---|---|---|
| Provider | NVIDIA | |
| Parameters | — | 49B |
| Context window | 2K | 131K |
| Max output | 1 | — |
| Input modalities | text | text |
| Output modalities | text | text |
| License | proprietary | other |
| Model type | — | chat |
| Capability | Text Embedding 004 | Llama 3.3 Nemotron Super 49B V1.5 |
|---|---|---|
| embeddings | Yes | — |
| function_calling | — | Yes |
| json_mode | — | Yes |
| reasoning | — | Yes |
| streaming | — | Yes |
| text_generation | — | Yes |
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