Head-to-Head Model Comparison

Qwen-VL Plus vs Yi-Large

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: October 2026Política editorial
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Related topics (12)
AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Qwen-VL Plus vs Yi-Large: Benchmarks, Pricing & Speed Comparison

Qwen-VL Plus da Alibaba e Yi-Large da 01.AI são dois modelos de IA de destaque. O Qwen-VL Plus oferece uma janela de contexto de 131.1K tokens a $0.21/$0.63 por milhão de tokens, enquanto o Yi-Large oferece 32.8K tokens de contexto a $2.50/$2.50 por milhão de tokens. Veja abaixo a comparação completa de benchmarks, latência e custos.

Comparação Direta (VS)

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Popular Matchups:
Alibaba

Qwen-VL Plus

IA Multimodal Nativa

O Qwen-VL Plus da Alibaba é um modelo de IA projetado para compreensão multimodal nativa de texto e imagem e leitura visual de documentos, oferecendo janela de contexto de 131K, velocidade de 105 tokens/s, índice de inteligência de 71/100 e

Intelligence Index71 / 100
Input Token:

$0.21 / 1M

Output Token:

$0.63 / 1M

Context Window:

131.1K tokens

SWE-bench Verified:

N/A

01.AI

Yi-Large

Modelo de Geração Clássica

O Yi-Large da 01.AI é um modelo de IA projetado para assistentes conversacionais, síntese de textos e tarefas corporativas, oferecendo janela de contexto de 33K, velocidade de 75 tokens/s, índice de inteligência de 79/100 e tarifa de $2.5/$

Intelligence Index79 / 100
Input Token:

$2.50 / 1M

Output Token:

$2.50 / 1M

Context Window:

32.8K tokens

SWE-bench Verified:

N/A

Principais Diferenças em Resumo

  • Qwen-VL Plus is 7.0x cheaper for API usage (input + output tokens combined).
  • Qwen-VL Plus has a larger context window (131K vs 33K tokens).
  • Qwen-VL Plus is faster at 105 tok/s vs 75 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureQwen-VL PlusYi-Large
Intelligence Index
Composite reasoning & knowledge score (0-100)
7179
Provider
Alibaba01.AI
Input Price
Cost per million input tokens
$0.21 / 1M$2.50 / 1M
Output Price
Cost per million output tokens
$0.63 / 1M$2.50 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.12 / 1M$0.93 / 1M
Context Window
Maximum input + output tokens
131.1K tokens~197 A4 pages of text32.8K tokens~49 A4 pages of text
Max Output Tokens
Per single request
8K4K
Throughput Speed
Tokens generated per second
105 tok/s75 tok/s
SWE-bench Verified
Real-world software engineering
N/AN/A
GPQA Diamond
Graduate-level reasoning
N/A52%
Cached Input Price
Prompt caching discount per 1M tokens
$0.02 / 1M$0.25 / 1M

Quem vence em cada categoria?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Qwen-VL Plus
7.0x cheaper monthly runtime
Speed
Qwen-VL Plus
+40% faster generation
Context
Qwen-VL Plus
131.1K tokens window

Pontuações de Benchmarks Verificadas

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

Qwen-VL PlusYi-Large
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

N/Avs52%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

70.5%vs76.5%
LMSYS Chatbot Arena Elo

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

1240ptsvs1290pts
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

105 tok/s vs75 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
Qwen-VL Plus0.48s
Yi-Large0.51s
Est. End-to-End Response (500 tokens)TTFT + generation time
Qwen-VL Plus5.24s
Yi-Large7.18s

Simulador Interativo de Custo de Tokens

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

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Qwen-VL Plus Monthly API Bill
$0.91 / month
$0.21/1M in · $0.63/1M out
Yi-Large Monthly API Bill
$6.38 / month
$2.5/1M in · $2.5/1M out
Qwen-VL Plus saves approximately $5.46 / month (86%) under this workload.7.0x Savings

Qwen-VL Plus · Strengths & Key Advantages

  • Janela de contexto de 131K com limite máximo de saída de 8K tokens (MMLU-Pro 70.5% · Arena Elo 1240)
  • Taxa de transferência rápida de 105 tokens/segundo com latência inicial (TTFT) de 480 ms
  • Economia de API competitiva ($0.21/$0.63 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas
Considerations & Trade-offs
  • Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
  • Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade

Yi-Large · Strengths & Key Advantages

  • Janela de contexto de 33K com limite máximo de saída de 4K tokens (GPQA Diamond 52% · MMLU-Pro 76.5%)
  • Taxa de transferência rápida de 75 tokens/segundo com latência inicial (TTFT) de 510 ms
  • Economia de API competitiva ($2.5/$2.5 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas
Considerations & Trade-offs
  • Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
  • Para alto volume de requisições, recomenda-se ativar o cache de prompts e a Batch API para reduzir custos

Token Use & Task Economics

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

MetricQwen-VL PlusYi-Large
Cost per Task
Estimated USD to finish one task
$0.05$0.15
Output Tokens / Task
Tokens generated per task
14K14K
Reasoning Tokens / Task
Thinking tokens burned per task
2K0K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

FeatureQwen-VL PlusYi-Large
Official API Model ID (SDK)qwen-vl-plus-instructyi-large
API ProtocolAlibaba REST API (OpenAI-Compatible)01.AI REST API (OpenAI-Compatible)
Release Date2024-012024-05
Knowledge CutoffDecember 2023March 2024
ArchitectureEfficient Multimodal Vision-Language TransformerDense Bilingual Foundation Transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.21/1M in) across full 131K windowFlat rate ($2.5/1M in) across full 33K window
Prompt Cache Policy & TTLCached input at $0.021/1M tokensCached input at $0.25/1M tokens
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationAPI Prompt Engineering & RAG Distillation
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)Text BPE (~4 chars/token)
Quantization & Min GPU VRAMCloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationAlibaba Production Safety & Alignment Verified01.AI Production Safety & Alignment Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext
Output Modalitiestexttext

Qwen-VL Plus vs Yi-Large: Respostas Rápidas (FAQ)

Which is more intelligent, Qwen-VL Plus or Yi-Large?

Yi-Large is more intelligent. It scores 79 compared with 71 on the composite Intelligence Index.

Which model is faster?

Qwen-VL Plus is faster, generating 105 tokens per second compared with 75 tokens per second.

Which model is cheaper to run?

Qwen-VL Plus is cheaper at $0.12 per 1M tokens blended, compared with $0.93 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Qwen-VL Plus has lower latency, with a time to first token of 0.48s compared with 0.51s.

Which model has a larger context window?

Qwen-VL Plus has a larger context window, supporting 131.1K tokens compared with 32.8K tokens.

Veredito

Tanto Qwen-VL Plus (Indicado para compreensão multimodal nativa de texto e imagem e leitura visual de documentos, arquiteturas RAG corporativas e integração escalável via API.) quanto Yi-Large (Indicado para assistentes conversacionais, síntese de textos e tarefas corporativas, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: Yi-Large lidera em inteligência geral e programação, Qwen-VL Plus oferece geração mais rápida e Qwen-VL Plus apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, Qwen-VL Plus ou Yi-Large?+

Nas avaliações de inteligência e código, Yi-Large leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, Qwen-VL Plus ou Yi-Large?+

O Qwen-VL Plus custa $0.21 / $0.63 por 1M de tokens (entrada/saída) e o Yi-Large custa $2.50 / $2.50. No custo combinado, Qwen-VL Plus é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O Qwen-VL Plus suporta 131.1K tokens de contexto contra 32.8K tokens do Yi-Large, enquanto Qwen-VL Plus 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.

Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.

Fontes oficiais: Documentação oficial de API da Alibaba e 01.AI e benchmarks independentes (2026).