GLM-5V-Turbo vs Hunyuan Large V2
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Zhipu AI 的 GLM-5V-Turbo 与 Tencent 的 Hunyuan Large V2 是当前备受关注的两款主力 AI 模型。GLM-5V-Turbo 提供 200K Token 上下文窗口，API 定价为每百万 Token 输入 $0.90 / 输出 $2.70；而 Hunyuan Large V2 提供 512K Token 上下文窗口，定价为每百万 Token 输入 $0.70 / 输出 $2.80。以下为两者的基准测试、延迟与成本全面对比。
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GLM-5V-Turbo
原生多模态视觉模型Zhipu AI 推出的 GLM-5V-Turbo 是一款原生支持图文多模态理解、视觉图表解析与跨模态推理的大模型，具备 200K 上下文窗口、85 Token/秒生成速度与 85/100 综合智能指数（每百万 Token $0.9 输入 / $2.7 输出）。
$0.90 / 1M
$2.70 / 1M
200K tokens
N/A
Hunyuan Large V2
旗舰前沿大模型Tencent 推出的 Hunyuan Large V2 是一款面向复杂企业级推理、软件开发与全场景生产工作流的旗舰前沿大模型，具备 512K 上下文窗口、80 Token/秒生成速度与 85/100 综合智能指数（每百万 Token $0.7 输入 / $2.8 输出）。
$0.70 / 1M
$2.80 / 1M
512K tokens
N/A
核心差异一览
- Hunyuan Large V2 is 1.1x cheaper for API usage (input + output tokens combined).
- Hunyuan Large V2 has a larger context window (512K vs 200K tokens).
- GLM-5V-Turbo is faster at 85 tok/s vs 80 tok/s.
| Feature | GLM-5V-Turbo | Hunyuan Large V2 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 85 | 85 |
Provider | Zhipu AI | Tencent |
Input Price Cost per million input tokens | $0.90 / 1M | $0.70 / 1M |
Output Price Cost per million output tokens | $2.70 / 1M | $2.80 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.51 / 1M | $0.47 / 1M |
Context Window Maximum input + output tokens | 200K tokens~300 A4 pages of text | 512K tokens~768 A4 pages of text |
Max Output Tokens Per single request | 16K | 16K |
Throughput Speed Tokens generated per second | 85 tok/s | 80 tok/s |
SWE-bench Verified Real-world software engineering | N/A | N/A |
GPQA Diamond Graduate-level reasoning | 64% | 66% |
Cached Input Price Prompt caching discount per 1M tokens | $0.09 / 1M | $0.07 / 1M |
各项指标谁更胜一筹？
At-a-glance decision frameworkEvaluations ongoing
权威基准测试得分对比
Official evaluation metrics verified by independent third-party research labs.
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.
Tokens emitted per second during active generation streaming.
延迟与响应速度
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
实时 Token 成本模拟器
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
GLM-5V-Turbo · Strengths & Key Advantages
- 提供 200K 上下文窗口与最高 16K 输出容量，核心基准表现优异（GPQA Diamond 64% · MMLU-Pro 81%）
- 高达 85 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 490 毫秒
- 极具竞争力的 API 定价（每百万 Token $0.9 输入 / $2.7 输出），原生支持提示词缓存、函数调用与结构化 JSON 输出
Considerations & Trade-offs
- 闭源专有云端模型，不支持下载权重进行离线本地物理隔离部署
- 在超长链路的前沿科研推导任务上，深度略逊于顶配重型旗舰推理模型
Hunyuan Large V2 · Strengths & Key Advantages
- 提供 512K 上下文窗口与最高 16K 输出容量，核心基准表现优异（GPQA Diamond 66% · MMLU-Pro 82.5%）
- 高达 80 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 480 毫秒
- 极具竞争力的 API 定价（每百万 Token $0.7 输入 / $2.8 输出），原生支持提示词缓存、函数调用与结构化 JSON 输出
Considerations & Trade-offs
- 闭源专有云端模型，不支持下载权重进行离线本地物理隔离部署
- 在超长链路的前沿科研推导任务上，深度略逊于顶配重型旗舰推理模型
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | GLM-5V-Turbo | Hunyuan Large V2 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.22 | $0.22 |
Output Tokens / Task Tokens generated per task | 20K | 22K |
Reasoning Tokens / Task Thinking tokens burned per task | 6K | 7K |
技术规格参数
Architecture, release timeline, capabilities, and modalities.
| Feature | GLM-5V-Turbo | Hunyuan Large V2 |
|---|---|---|
| Official API Model ID (SDK) | glm-5v-turbo | hunyuan-large-v2 |
| API Protocol | Zhipu AI REST API (OpenAI-Compatible) | Tencent REST API (OpenAI-Compatible) |
| Release Date | 2026-04 | 2026-05 |
| Knowledge Cutoff | February 2026 | February 2026 |
| Architecture | Frontier Commercial Vision-Language Transformer | High-Scale Sparse Mixture-of-Experts Transformer |
| Parameters | Confidential | 500B total (30B active MoE) |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.9/1M in) across full 200K window | Flat rate ($0.7/1M in) across full 512K window |
| Prompt Cache Policy & TTL | Cached input at $0.09/1M tokens | Cached input at $0.07/1M tokens |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| 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 | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | API Prompt Engineering & RAG Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | Text BPE (~4 chars/token) |
| 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 | Zhipu AI Production Safety & Alignment Verified | Tencent Production Safety & Alignment Verified |
| 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, vision | text |
| Output Modalities | text | text |
GLM-5V-Turbo vs Hunyuan Large V2: 常见问题解答 (FAQ)
Which model is faster?
GLM-5V-Turbo is faster, generating 85 tokens per second compared with 80 tokens per second.
Which model is cheaper to run?
Hunyuan Large V2 is cheaper at $0.47 per 1M tokens blended, compared with $0.51 (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 0.49s.
Which model has a larger context window?
Hunyuan Large V2 has a larger context window, supporting 512K tokens compared with 200K tokens.
综合结论
综合来看，GLM-5V-Turbo（适合：原生支持图文多模态理解、视觉图表解析与跨模态推理的任务、企业级 RAG 检索增强生成、自动化智能体工作流与高可靠 API 集成。）与 Hunyuan Large V2（适合：面向复杂企业级推理、软件开发与全场景生产工作流的旗舰前沿任务、企业级 RAG 检索增强生成、自动化智能体工作流与高可靠 API 集成。）各具优势：GLM-5V-Turbo 在综合智能与编程基准测试中表现更强，GLM-5V-Turbo 拥有更快的 Token 生成速度，而 Hunyuan Large V2 则在规模化 API 部署中具备更高的成本效益。
常见问题 (FAQ)
在编程和深度推理方面，GLM-5V-Turbo 和 Hunyuan Large V2 哪个更强？+
在综合智能指数与编程基准评测中，GLM-5V-Turbo 表现占优。建议结合上方的 SWE-bench Verified 与 GPQA Diamond 跑分根据具体场景选择。
GLM-5V-Turbo 与 Hunyuan Large V2 的 API 价格哪个更便宜？+
GLM-5V-Turbo 的 API 价格为输入 $0.90 / 输出 $2.70（每百万 Token），Hunyuan Large V2 为输入 $0.70 / 输出 $2.80。综合混合成本来看，Hunyuan Large V2 更具性价比。
哪款模型拥有更大的上下文窗口和更快的响应速度？+
GLM-5V-Turbo 支持 200K Token 上下文窗口，而 Hunyuan Large V2 支持 512K Token。在流式生成速度方面，GLM-5V-Turbo 的吞吐表现更快。
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.
数据来源: Zhipu AI 与 Tencent 官方 API 文档、模型发布说明及独立基准测试报告 (2026)。