Qwen Flash vs Hunyuan TurboS
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Alibaba 的 Qwen Flash 与 Tencent 的 Hunyuan TurboS 是当前备受关注的两款主力 AI 模型。Qwen Flash 提供 1M Token 上下文窗口，API 定价为每百万 Token 输入 $0.02 / 输出 $0.08；而 Hunyuan TurboS 提供 32.8K Token 上下文窗口，定价为每百万 Token 输入 $0.06 / 输出 $0.24。以下为两者的基准测试、延迟与成本全面对比。
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Qwen Flash
超高速低延迟推理Alibaba 推出的 Qwen Flash 是一款面向实时交互对话、高并发路由与极低延迟生产环境的超高速大模型，具备 1M 上下文窗口、180 Token/秒生成速度与 67/100 综合智能指数（每百万 Token $0.02 输入 / $0.08 输出）。
$0.02 / 1M
$0.08 / 1M
1M tokens
N/A
Hunyuan TurboS
超高速低延迟推理Tencent 推出的 Hunyuan TurboS 是一款面向实时交互对话、高并发路由与极低延迟生产环境的超高速大模型，具备 33K 上下文窗口、160 Token/秒生成速度与 70/100 综合智能指数（每百万 Token $0.06 输入 / $0.24 输出）。
$0.06 / 1M
$0.24 / 1M
32.8K tokens
N/A
核心差异一览
- Qwen Flash is 3.0x cheaper for API usage (input + output tokens combined).
- Qwen Flash has a larger context window (1M vs 33K tokens).
- Qwen Flash is faster at 180 tok/s vs 160 tok/s.
| Feature | Qwen Flash | Hunyuan TurboS |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 67 | 70 |
Provider | Alibaba | Tencent |
Input Price Cost per million input tokens | $0.02 / 1M | $0.06 / 1M |
Output Price Cost per million output tokens | $0.08 / 1M | $0.24 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.01 / 1M | $0.04 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 A4 pages of text | 32.8K tokens~49 A4 pages of text |
Max Output Tokens Per single request | 8K | 4K |
Throughput Speed Tokens generated per second | 180 tok/s | 160 tok/s |
SWE-bench Verified Real-world software engineering | N/A | N/A |
Cached Input Price Prompt caching discount per 1M tokens | $0.00 / 1M | $0.01 / 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.
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.
Qwen Flash · Strengths & Key Advantages
- 提供 1M 上下文窗口与最高 8K 输出容量，核心基准表现优异（MMLU-Pro 63.5% · Arena Elo 1195）
- 高达 180 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 250 毫秒
- 极具竞争力的 API 定价（每百万 Token $0.02 输入 / $0.08 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 TurboS · Strengths & Key Advantages
- 提供 33K 上下文窗口与最高 4K 输出容量，核心基准表现优异（MMLU-Pro 67% · Arena Elo 1225）
- 高达 160 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 250 毫秒
- 极具竞争力的 API 定价（每百万 Token $0.06 输入 / $0.24 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 | Qwen Flash | Hunyuan TurboS |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.01 | $0.01 |
Output Tokens / Task Tokens generated per task | 10K | 8K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
技术规格参数
Architecture, release timeline, capabilities, and modalities.
| Feature | Qwen Flash | Hunyuan TurboS |
|---|---|---|
| Official API Model ID (SDK) | qwen-flash-instruct | hunyuan-turbos |
| API Protocol | Alibaba REST API (OpenAI-Compatible) | Tencent REST API (OpenAI-Compatible) |
| Release Date | 2025-07 | 2025-03 |
| Knowledge Cutoff | May 2025 | January 2025 |
| Architecture | Ultra-Lightweight Distilled Autoregressive Transformer | Lightweight Fast-Inference Transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.02/1M in) across full 1000K window | Flat rate ($0.06/1M in) across full 33K window |
| Prompt Cache Policy & TTL | Cached input at $0.002/1M tokens | Cached input at $0.006/1M tokens |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | 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) | 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 | Alibaba 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 | text |
| Output Modalities | text | text |
Qwen Flash vs Hunyuan TurboS: 常见问题解答 (FAQ)
Which is more intelligent, Qwen Flash or Hunyuan TurboS?
Hunyuan TurboS is more intelligent. It scores 70 compared with 67 on the composite Intelligence Index.
Which model is faster?
Qwen Flash is faster, generating 180 tokens per second compared with 160 tokens per second.
Which model is cheaper to run?
Qwen Flash is cheaper at $0.01 per 1M tokens blended, compared with $0.04 (7:2:1 cache:input:output ratio).
Which model has a larger context window?
Qwen Flash has a larger context window, supporting 1M tokens compared with 32.8K tokens.
综合结论
综合来看，Qwen Flash（适合：面向实时交互对话、高并发路由与极低延迟生产环境的超高速任务、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 TurboS（适合：面向实时交互对话、高并发路由与极低延迟生产环境的超高速任务、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：Hunyuan TurboS 在综合智能与编程基准测试中表现更强，Qwen Flash 拥有更快的 Token 生成速度，而 Qwen Flash 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，Qwen Flash 和 Hunyuan TurboS 哪个更强？+
在综合智能指数与编程基准评测中，Hunyuan TurboS 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。
Qwen Flash 与 Hunyuan TurboS 的 API 价格哪个更便宜？+
Qwen Flash 的 API 价格为输入 $0.02 / 输出 $0.08（每百万 Token），Hunyuan TurboS 为输入 $0.06 / 输出 $0.24。综合混合成本来看，Qwen Flash 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？+
Qwen Flash 支持 1M Token 上下文窗口，而 Hunyuan TurboS 支持 32.8K Token。在流式生成速度方面，Qwen Flash 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: Alibaba 与 Tencent 官方 API 文档、模型发布说明及独立基准测试报告 (2026)。