Hunyuan Large V2 vs Claude Opus 4.8
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Hunyuan Large V2 by Tencent and Claude Opus 4.8 by Anthropic represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Hunyuan Large V2 holds a notable pricing advantage for token ingestion. On output generation, Hunyuan Large V2 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Claude Opus 4.8 provides an expanded memory horizon with 1,000K tokens. In latency-sensitive production environments, Hunyuan Large V2 leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
किसी भी मॉडल को बदलें और तुलना करें
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Hunyuan Large V2
डीप रीजनिंग मॉडलTencent द्वारा विकसित Hunyuan Large V2 एक उन्नत AI मॉडल है, जिसमें 512K टोकन का कॉन्टेक्स्ट विंडो और $0.7/1M इनपुट तथा $2.8/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।
$0.70 / 1M
$2.80 / 1M
512K tokens
N/A
Claude Opus 4.8
डीप रीजनिंग मॉडलAnthropic द्वारा विकसित Claude Opus 4.8 एक उन्नत AI मॉडल है, जिसमें 1M टोकन का कॉन्टेक्स्ट विंडो और $5/1M इनपुट तथा $25/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।
$5.00 / 1M
$25.00 / 1M
1M tokens
80.8%
एक नज़र में मुख्य अंतर
- Hunyuan Large V2 is 8.4x cheaper for API usage (input + output tokens combined).
- Claude Opus 4.8 has a larger context window (1M vs 512K tokens).
- Hunyuan Large V2 is faster at 80 tok/s vs 64 tok/s.
| Feature | Hunyuan Large V2 | Claude Opus 4.8 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 85 | 67 |
Provider | Tencent | Anthropic |
Input Price Cost per million input tokens | $0.70 / 1M | $5.00 / 1M |
Output Price Cost per million output tokens | $2.80 / 1M | $25.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.47 / 1M | $3.85 / 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 | 64 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 80.8% |
GPQA Diamond Graduate-level reasoning | 66% | 78.9% |
Cached Input Price Prompt caching discount per 1M tokens | $0.07 / 1M | $0.50 / 1M |
किस क्षेत्र में कौन आगे है?
At-a-glance decision frameworkEvaluations ongoing
सत्यापित बेंचमार्क स्कोर तुलना
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.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Tokens emitted per second during active generation streaming.
लेटेंसी और रिस्पॉन्स समय
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
रियल-टाइम टोकन लागत सिम्युलेटर
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Hunyuan Large V2 · Strengths & Key Advantages
- Tencent की उन्नत High-Scale Sparse Mixture-of-Experts Transformer आर्किटेक्चर और 512K कॉन्टेक्स्ट विंडो क्षमता
- किफायती और पारदर्शी API मूल्य ($0.7/1M इनपुट, $2.8/1M आउटपुट) तेज़ रिस्पॉन्स के साथ
- जटिल कोडिंग, तार्किक विश्लेषण और बहुभाषी कार्यों में उच्च सटीकता
Considerations & Trade-offs
- बड़े पैमाने पर लंबे कॉन्टेक्स्ट प्रॉम्प्ट्स के लिए टोकन बजट प्रबंधन आवश्यक है
- विशिष्ट डोमेन कार्यों में सर्वोत्तम परिणाम के लिए सटीक प्रॉम्प्ट इंजीनियरिंग की आवश्यकता होती है
Claude Opus 4.8 · Strengths & Key Advantages
- Anthropic की उन्नत Frontier Hybrid Cognitive Architecture आर्किटेक्चर और 1M कॉन्टेक्स्ट विंडो क्षमता
- किफायती और पारदर्शी API मूल्य ($5/1M इनपुट, $25/1M आउटपुट) तेज़ रिस्पॉन्स के साथ
- जटिल कोडिंग, तार्किक विश्लेषण और बहुभाषी कार्यों में उच्च सटीकता
Considerations & Trade-offs
- बड़े पैमाने पर लंबे कॉन्टेक्स्ट प्रॉम्प्ट्स के लिए टोकन बजट प्रबंधन आवश्यक है
- विशिष्ट डोमेन कार्यों में सर्वोत्तम परिणाम के लिए सटीक प्रॉम्प्ट इंजीनियरिंग की आवश्यकता होती है
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Hunyuan Large V2 | Claude Opus 4.8 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.22 | $5.49 |
Output Tokens / Task Tokens generated per task | 22K | 72K |
Reasoning Tokens / Task Thinking tokens burned per task | 7K | 37K |
तकनीकी विशिष्टताएँ (Specs)
Architecture, release timeline, capabilities, and modalities.
| Feature | Hunyuan Large V2 | Claude Opus 4.8 |
|---|---|---|
| Official API Model ID (SDK) | hunyuan-large-v2 | claude-opus-4-8-20260501 |
| API Protocol | Tencent REST API (OpenAI-Compatible) | Anthropic Messages API + AWS Bedrock + Vertex AI |
| Release Date | 2026-05 | 2026-05 |
| Knowledge Cutoff | February 2026 | March 2026 |
| Architecture | High-Scale Sparse Mixture-of-Experts Transformer | Frontier Hybrid Cognitive Architecture |
| 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 | $0.5/1M 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 4.8: त्वरित प्रश्नोत्तर (FAQ)
Which is more intelligent, Hunyuan Large V2 or Claude Opus 4.8?
Hunyuan Large V2 is more intelligent. It scores 85 compared with 67 on the composite Intelligence Index.
Which model is faster?
Hunyuan Large V2 is faster, generating 80 tokens per second compared with 64 tokens per second.
Which model is cheaper to run?
Hunyuan Large V2 is cheaper at $0.47 per 1M tokens blended, compared with $3.85 (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 1.65s.
Which model has a larger context window?
Claude Opus 4.8 has a larger context window, supporting 1M tokens compared with 512K tokens.
निष्कर्ष
Verdict & Model Selection Recommendation: Choose Hunyuan Large V2 if your priority is Social chatbots, creative writing, game NPC dialogue, and extensive document summarization. Its performance in demanding tasks justifies its operational token cost. Choose Claude Opus 4.8 if your workflow prioritizes Frontier AI research, multi-agent systems orchestration, and enterprise software engineering. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
अक्सर पूछे जाने वाले प्रश्न (FAQ)
How does Hunyuan Large V2 compare to Claude Opus 4.8 in API token pricing and cost per token?+
Hunyuan Large V2 costs $0.70 per 1M input tokens and $2.80 per 1M output tokens, whereas Claude Opus 4.8 costs $5.00 input and $25.00 output. Overall, Hunyuan Large V2 is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: Hunyuan Large V2 or Claude Opus 4.8?+
Hunyuan Large V2 supports a context window of 512K tokens (~384k words), while Claude Opus 4.8 supports 1,000K tokens (~750k words). Therefore, Claude Opus 4.8 can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Hunyuan Large V2 or Claude Opus 4.8?+
Hunyuan Large V2 scores at the frontier of coding benchmarks, while Claude Opus 4.8 scores 80.8%. For complex autonomous debugging and agentic engineering, Claude Opus 4.8 provides robust code generation and tool calling.
What is the difference in reasoning capability and extended thinking between Hunyuan Large V2 and Claude Opus 4.8?+
Hunyuan Large V2 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Claude Opus 4.8 provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Hunyuan Large V2 and Claude Opus 4.8?+
Hunyuan Large V2 generates approximately 80 tokens per second, while Claude Opus 4.8 delivers 64 tokens per second. In latency-sensitive production environments, Hunyuan Large V2 provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Hunyuan Large V2 and Claude Opus 4.8 to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Hunyuan Large V2 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Claude Opus 4.8. This tiered routing pattern cuts overall API bills by up to 70%.
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.
स्रोत: GetInfoUs Independent AI Benchmarks & Official API Specs