Head-to-Head Model Comparison

Hunyuan Large V2 vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial
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Compare Hunyuan Large V2 by Tencent against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

Comparación Directa (VS)

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Popular Matchups:
Tencent

Hunyuan Large V2

IA social

de Tencent 500B MoE insignia con de China largest comercial 512K ventana de contexto, especializado para nuanced dialogue, social matiz, y roleplay.

Intelligence Index85 / 100
Input Token:

$0.70 / 1M

Output Token:

$2.80 / 1M

Context Window:

512K tokens

SWE-bench Verified:

N/A

Anthropic

Claude Opus 5.5

Titán de inteligencia de frontera

de Anthropic pinnacle modelo de frontera diseñado para de largo alcance agentic ingeniería de software, denso multimodal documento síntesis, y autónomo investigación flujos de trabajo.

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

Diferencias Clave de un Vistazo

  • Hunyuan Large V2 is 6.7x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 512K tokens).
  • Hunyuan Large V2 is faster at 80 tok/s vs 78 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaracterísticaHunyuan Large V2Claude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
8594
Provider
TencentAnthropic
Input Price
Cost per million input tokens
$0.70 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$2.80 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.47 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
512K tokens~768 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
16K128K
Throughput Speed
Tokens generated per second
80 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
N/A84.6%
GPQA Diamond
Graduate-level reasoning
66%82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.07 / 1M$0.40 / 1M

¿Quién gana en cada área?

At-a-glance decision framework
Código

Evaluations ongoing

Costo
Hunyuan Large V2
6.7x cheaper monthly runtime
Velocidad
Hunyuan Large V2
+3% faster generation
Contexto
Claude Opus 5.5
1M tokens window

Puntuaciones de Benchmarks Verificadas

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

Hunyuan Large V2Claude Opus 5.5
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

N/Avs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

66%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

82.5%vs91.5%
LMSYS Chatbot Arena Elo

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

1365ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

N/Avs66.4%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs83.1%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

N/Avs95.4%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

N/Avs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

80 tok/s vs78 tok/s

Latencia y Tiempo de Respuesta

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
Hunyuan Large V20.48s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
Hunyuan Large V26.73s
Claude Opus 5.57.81s

Simulador Interactivo de Costos 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)
Hunyuan Large V2 Monthly API Bill
$3.67 / month
$0.7/1M in · $2.8/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
Hunyuan Large V2 saves approximately $20.93 / month (85%) under this workload.6.7x Savings

Hunyuan Large V2 · Strengths & Key Advantages

  • Enormous 512K ventana de contexto ideal para procesamiento entire novels y book-length records
  • inigualable emotional inteligencia, social roleplay, y colloquial chino dialogue
  • Highly optimized Tencent Cloud infraestructura con dependable SLA availability
Considerations & Trade-offs
  • English documentation y international community tooling son somewhat limitado
  • texto-solo API; carece de nativo visión modality

Claude Opus 5.5 · Strengths & Key Advantages

  • inigualable autónomo multipaso codificación agéntica y refactorización
  • Flawless multidocumento razonamiento sobre 1M token contexto con no largo-prompt surcharge
  • más alto Artificial análisis inteligencia Index ever measured (58/100), leading SWE-bench Pro un 89.9%
  • Precise herramienta ejecución con robust error-recovery bucles
Considerations & Trade-offs
  • Premium salida precios ($20.00/M) plus heavy razonamiento-token usage (~119K salida tokens por index tarea) keeps largo agentic se ejecuta expensive
  • largo pensamiento times un maximum effort puede push un único hard agentic tarea toward ~$13

Token Use & Task Economics

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

MetricHunyuan Large V2Claude Opus 5.5
Cost per Task
Estimated USD to finish one task
$0.22$3.85
Output Tokens / Task
Tokens generated per task
22K68K
Reasoning Tokens / Task
Thinking tokens burned per task
7K42K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

CaracterísticaHunyuan Large V2Claude Opus 5.5
Official API Model ID (SDK)hunyuan-large-v2claude-opus-5-5-20260901
API ProtocolTencent REST API (OpenAI-Compatible)Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2026-052026-09
Knowledge CutoffFebruary 2026June 2026
ArchitectureHigh-Scale Sparse Mixture-of-Experts TransformerExtended Autonomous Hybrid Reasoning Transformer
Parameters500B total (30B active MoE)Confidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.7/1M in) across full 512K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.07/1M tokens$0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
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 toolsNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationCustom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
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 ClassificationTencent Production Safety & Alignment VerifiedAnthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated
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 Modalitiestexttext, vision
Output Modalitiestexttext

Hunyuan Large V2 vs Claude Opus 5.5: Respuestas Rápidas (FAQ)

Which is more intelligent, Hunyuan Large V2 or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 85 on the composite Intelligence Index.

Which model is faster?

Hunyuan Large V2 is faster, generating 80 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

Hunyuan Large V2 is cheaper at $0.47 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Hunyuan Large V2 has lower latency, with a time to first token of 0.48s compared with 1.40s.

Which model has a larger context window?

Claude Opus 5.5 has a larger context window, supporting 1M tokens compared with 512K tokens.

Veredicto

Choose Hunyuan Large V2 for social chatbots, creativo writing, game npc dialogue, y extensive documento resumen, or choose Claude Opus 5.5 for grande-escala software development agentes, empresarial codebases, y de misión crítica científico síntesis.

Preguntas frecuentes

Which is cheaper: Hunyuan Large V2 or Claude Opus 5.5?+

Hunyuan Large V2 costs $0.7/1M input and $2.8/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: Hunyuan Large V2 or Claude Opus 5.5?+

Hunyuan Large V2 supports 512K tokens whereas Claude Opus 5.5 supports 1M tokens.

AI Terminology & Guide
Explore Glossary →

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

Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.

Fuentes: Tencent & Anthropic Official Documentation