Head-to-Head Model Comparison

Llama Nemotron Rerank VL 1B v2 vs Llama Nemotron Embed VL 1B v2

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: October 2026Política editorial

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Llama Nemotron Rerank VL 1B v2Profile

Llama Nemotron Embed VL 1B v2Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

NVIDIA

Llama Nemotron Rerank VL 1B v2

Modelo Leve e Econômico

O Llama Nemotron Rerank VL 1B v2 da NVIDIA é um modelo de IA projetado para máxima economia por token e alto desempenho em escala de produção, oferecendo janela de contexto de 128K, velocidade de 240 tokens/s, índice de inteligência de 33/1

Intelligence Index33 / 100

Input Token:

$0.03 / 1M

Output Token:

$0.03 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

NVIDIA

Llama Nemotron Embed VL 1B v2

Embeddings Vetoriais e RAG

O Llama Nemotron Embed VL 1B v2 da NVIDIA é um modelo de IA projetado para busca vetorial semântica, indexação de documentos e pipelines RAG, oferecendo janela de contexto de 32K, velocidade de 280 tokens/s, índice de inteligência de 32/100

Intelligence Index32 / 100

Input Token:

$0.02 / 1M

Output Token:

$0.02 / 1M

Context Window:

32K tokens

SWE-bench Verified:

N/A

Principais Diferenças em Resumo

Llama Nemotron Embed VL 1B v2 is 1.5x cheaper for API usage (input + output tokens combined).
Llama Nemotron Rerank VL 1B v2 has a larger context window (128K vs 32K tokens).
Llama Nemotron Embed VL 1B v2 is faster at 280 tok/s vs 240 tok/s.

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Feature	Llama Nemotron Rerank VL 1B v2	Llama Nemotron Embed VL 1B v2
Intelligence Index Composite reasoning & knowledge score (0-100)	33	32
Provider	NVIDIA	NVIDIA
Input Price Cost per million input tokens	$0.03 / 1M	$0.02 / 1M
Output Price Cost per million output tokens	$0.03 / 1M	$0.02 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.01 / 1M	$0.01 / 1M
Context Window Maximum input + output tokens	128K tokens~192 A4 pages of text	32K tokens~48 A4 pages of text
Max Output Tokens Per single request	2K	2K
Throughput Speed Tokens generated per second	240 tok/s	280 tok/s
SWE-bench Verified Real-world software engineering	N/A	N/A
Cached Input Price Prompt caching discount per 1M tokens	$0.01 / 1M	$0.01 / 1M

Quem vence em cada categoria?

At-a-glance decision framework

Coding

Evaluations ongoing

Cost

Llama Nemotron Embed VL 1B v2

1.5x cheaper monthly runtime

Speed

Llama Nemotron Embed VL 1B v2

+17% faster generation

Context

Llama Nemotron Rerank VL 1B v2

128K tokens window

Pontuações de Benchmarks Verificadas

Official evaluation metrics verified by independent third-party research labs.

Llama Nemotron Rerank VL 1B v2Llama Nemotron Embed VL 1B v2

LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1220ptsvs1210pts

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

240 tok/s vs280 tok/s

Latência e Tempo de Resposta

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better

Llama Nemotron Rerank VL 1B v20.09s

Llama Nemotron Embed VL 1B v20.08s

Est. End-to-End Response (500 tokens)TTFT + generation time

Llama Nemotron Rerank VL 1B v22.17s

Llama Nemotron Embed VL 1B v21.87s

Simulador Interativo de Custo de Tokens

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% cached

0% (Cold)50%90% (Warm)

Llama Nemotron Rerank VL 1B v2 Monthly API Bill

$0.08 / month

$0.03/1M in · $0.03/1M out

Llama Nemotron Embed VL 1B v2 Monthly API Bill

$0.06 / month

$0.02/1M in · $0.02/1M out

Llama Nemotron Embed VL 1B v2 saves approximately $0.03 / month (34%) under this workload.1.5x Savings

Llama Nemotron Rerank VL 1B v2 · Strengths & Key Advantages

Janela de contexto de 128K com limite máximo de saída de 2K tokens (Arena Elo 1220)
Taxa de transferência rápida de 240 tokens/segundo com latência inicial (TTFT) de 90 ms
Pesos abertos (1B) para auto-hospedagem local ou em nuvem privada via vLLM, SGLang ou Ollama

Considerations & Trade-offs

Requer servidores GPU com memória VRAM adequada para execução local em precisão total
Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade

Llama Nemotron Embed VL 1B v2 · Strengths & Key Advantages

Janela de contexto de 32K com limite máximo de saída de 2K tokens (Arena Elo 1210)
Taxa de transferência rápida de 280 tokens/segundo com latência inicial (TTFT) de 80 ms
Pesos abertos (1B) para auto-hospedagem local ou em nuvem privada via vLLM, SGLang ou Ollama

Considerations & Trade-offs

Requer servidores GPU com memória VRAM adequada para execução local em precisão total
Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

Metric	Llama Nemotron Rerank VL 1B v2	Llama Nemotron Embed VL 1B v2
Cost per Task Estimated USD to finish one task	$0.01	$0.01
Output Tokens / Task Tokens generated per task	1K	1K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

Feature	Llama Nemotron Rerank VL 1B v2	Llama Nemotron Embed VL 1B v2
Official API Model ID (SDK)	llama-nemotron-rerank-vl-1b-v2	llama-nemotron-embed-vl-1b-v2
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2026-03	2026-02
Knowledge Cutoff	January 2026	December 2025
Architecture	Cross-Encoder Multimodal Reranking Transformer	Dense Multimodal Embedding Transformer
Parameters	1B	1B
Enterprise Rate Limits (RPM / TPM)	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)	Flat rate ($0.03/1M in) across full 128K window	Flat rate ($0.02/1M in) across full 32K window
Prompt Cache Policy & TTL	Cached input at $0.008/1M tokens	Cached input at $0.005/1M tokens
Computer Use / GUI Agent	Text-only completion (No GUI action loop)	Text-only completion (No GUI action loop)
MCP & Parallel Tool Calling	Prompt-based JSON extraction only	Prompt-based JSON extraction only
Web Search Grounding & Sandbox	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning Support	Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)	Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Token Billing	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAM	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 2 GB VRAM (4-bit Quantized) · 4 GB VRAM (Native BF16)	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 2 GB VRAM (4-bit Quantized) · 4 GB VRAM (Native BF16)
Safety & Frontier Classification	Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)	Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (ZDR/HIPAA/SOC2)	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalities	text, vision	text, vision
Output Modalities	score	embedding

Llama Nemotron Rerank VL 1B v2 vs Llama Nemotron Embed VL 1B v2: Respostas Rápidas (FAQ)

Which is more intelligent, Llama Nemotron Rerank VL 1B v2 or Llama Nemotron Embed VL 1B v2?

Llama Nemotron Rerank VL 1B v2 is more intelligent. It scores 33 compared with 32 on the composite Intelligence Index.

Which model is faster?

Llama Nemotron Embed VL 1B v2 is faster, generating 280 tokens per second compared with 240 tokens per second.

Which model has lower latency?

Llama Nemotron Embed VL 1B v2 has lower latency, with a time to first token of 0.08s compared with 0.09s.

Which model has a larger context window?

Llama Nemotron Rerank VL 1B v2 has a larger context window, supporting 128K tokens compared with 32K tokens.

Veredito

Tanto Llama Nemotron Rerank VL 1B v2 (Indicado para máxima economia por token e alto desempenho em escala de produção, arquiteturas RAG corporativas e integração escalável via API.) quanto Llama Nemotron Embed VL 1B v2 (Indicado para busca vetorial semântica, indexação de documentos e pipelines RAG, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: Llama Nemotron Rerank VL 1B v2 lidera em inteligência geral e programação, Llama Nemotron Embed VL 1B v2 oferece geração mais rápida e Llama Nemotron Embed VL 1B v2 apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, Llama Nemotron Rerank VL 1B v2 ou Llama Nemotron Embed VL 1B v2?+

Nas avaliações de inteligência e código, Llama Nemotron Rerank VL 1B v2 leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, Llama Nemotron Rerank VL 1B v2 ou Llama Nemotron Embed VL 1B v2?+

O Llama Nemotron Rerank VL 1B v2 custa $0.03 / $0.03 por 1M de tokens (entrada/saída) e o Llama Nemotron Embed VL 1B v2 custa $0.02 / $0.02. No custo combinado, Llama Nemotron Embed VL 1B v2 é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O Llama Nemotron Rerank VL 1B v2 suporta 128K tokens de contexto contra 32K tokens do Llama Nemotron Embed VL 1B v2, enquanto Llama Nemotron Embed VL 1B v2 entrega maior velocidade de geração.

AI Terminology & Guide

Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

Llama Nemotron Rerank VL 1B v2 vs Llama Nemotron Embed VL 1B v2

Troque e Compare Qualquer Modelo

Llama Nemotron Rerank VL 1B v2

Llama Nemotron Embed VL 1B v2

Quem vence em cada categoria?

Pontuações de Benchmarks Verificadas

Latência e Tempo de Resposta

Simulador Interativo de Custo de Tokens

Llama Nemotron Rerank VL 1B v2 · Strengths & Key Advantages

Considerations & Trade-offs

Llama Nemotron Embed VL 1B v2 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificações Técnicas

Llama Nemotron Rerank VL 1B v2 vs Llama Nemotron Embed VL 1B v2: Respostas Rápidas (FAQ)

Veredito

Perguntas Frequentes (FAQ)

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