Hunyuan Large V2 vs Claude Opus 5.5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Hunyuan Large V2 by Tencent against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.
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Hunyuan Large V2
Modelo Principal de FronteiraO Hunyuan Large V2 da Tencent é um modelo de IA projetado para raciocínio corporativo de fronteira, programação avançada e cargas de produção, oferecendo janela de contexto de 512K, velocidade de 80 tokens/s, índice de inteligência de 85/10
$0.70 / 1M
$2.80 / 1M
512K tokens
N/A
Claude Opus 5.5
Modelo Principal de FronteiraO Claude Opus 5.5 da Anthropic é um modelo de IA projetado para raciocínio corporativo de fronteira, programação avançada e cargas de produção, oferecendo janela de contexto de 1M, velocidade de 78 tokens/s, índice de inteligência de 94/100
$4.00 / 1M
$20.00 / 1M
1M tokens
84.6%
Principais Diferenças em Resumo
- 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.
| Feature | Hunyuan Large V2 | Claude Opus 5.5 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 85 | 94 |
Provider | Tencent | Anthropic |
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 text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 16K | 128K |
Throughput Speed Tokens generated per second | 80 tok/s | 78 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 84.6% |
GPQA Diamond Graduate-level reasoning | 66% | 82.3% |
Cached Input Price Prompt caching discount per 1M tokens | $0.07 / 1M | $0.40 / 1M |
Quem vence em cada categoria?
At-a-glance decision frameworkEvaluations ongoing
Pontuações de Benchmarks Verificadas
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latência e Tempo de Resposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interativo de Custo de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Hunyuan Large V2 · Strengths & Key Advantages
- Janela de contexto de 512K com limite máximo de saída de 16K tokens (GPQA Diamond 66% · MMLU-Pro 82.5%)
- Taxa de transferência rápida de 80 tokens/segundo com latência inicial (TTFT) de 480 ms
- Economia de API competitiva ($0.7/$2.8 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
Claude Opus 5.5 · Strengths & Key Advantages
- Janela de contexto de 1M com limite máximo de saída de 128K tokens (SWE-bench Verified 84.6% · GPQA Diamond 82.3%)
- Taxa de transferência rápida de 78 tokens/segundo com latência inicial (TTFT) de 1400 ms
- Economia de API competitiva ($4/$20 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.
| Metric | Hunyuan Large V2 | Claude Opus 5.5 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.22 | $3.85 |
Output Tokens / Task Tokens generated per task | 22K | 68K |
Reasoning Tokens / Task Thinking tokens burned per task | 7K | 42K |
Especificações Técnicas
Architecture, release timeline, capabilities, and modalities.
| Feature | Hunyuan Large V2 | Claude Opus 5.5 |
|---|---|---|
| Official API Model ID (SDK) | hunyuan-large-v2 | claude-opus-5-5-20260901 |
| API Protocol | Tencent REST API (OpenAI-Compatible) | Anthropic Messages API + AWS Bedrock + Vertex AI |
| Release Date | 2026-05 | 2026-09 |
| Knowledge Cutoff | February 2026 | June 2026 |
| Architecture | High-Scale Sparse Mixture-of-Experts Transformer | Extended Autonomous Hybrid Reasoning Transformer |
| Parameters | 500B total (30B active MoE) | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 4,000 – 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 window | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Cached input at $0.07/1M tokens | $0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Native Web Search Citations + Code Execution Tool + MCP Connectors |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | Custom Model Tuning via Amazon Bedrock & Prompt Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| Quantization & Min GPU VRAM | Cloud-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 Classification | Tencent Production Safety & Alignment Verified | Anthropic 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 Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text | text, vision |
| Output Modalities | text | text |
Hunyuan Large V2 vs Claude Opus 5.5: Respostas 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.
Veredito
Choose Hunyuan Large V2 for indicado para raciocínio corporativo de fronteira, programação avançada e cargas de produção, arquiteturas rag corporativas e integração escalável via api., or choose Claude Opus 5.5 for indicado para raciocínio corporativo de fronteira, programação avançada e cargas de produção, arquiteturas rag corporativas e integração escalável via api..
Perguntas Frequentes (FAQ)
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.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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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: Tencent & Anthropic Official Documentation