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Head-to-Head Model Comparison

Qwen3.7 Max vs Qwen3.8 Max Preview

Benchmarks, API Token Pricing, Context Window & Speed Comparison

由 GetInfoUs 研究团队审核最后审核日期：October 2026编辑政策
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Qwen3.7 Max vs Qwen3.8 Max Preview: Benchmarks, Pricing & Speed Comparison

Alibaba 的 Qwen3.7 Max 与 Alibaba 的 Qwen3.8 Max Preview 是当前备受关注的两款主力 AI 模型。Qwen3.7 Max 提供 1M Token 上下文窗口，API 定价为每百万 Token 输入 $1.80 / 输出 $7.20；而 Qwen3.8 Max Preview 提供 1M Token 上下文窗口，定价为每百万 Token 输入 $0.00 / 输出 $0.00。以下为两者的基准测试、延迟与成本全面对比。

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Alibaba

Qwen3.7 Max

自主智能体与工具专家

Alibaba 推出的 Qwen3.7 Max 是一款专为长周期自主智能体 (Agent)、工具调用与自动化工作流打造的大模型，具备 1M 上下文窗口、80 Token/秒生成速度与 92/100 综合智能指数（每百万 Token $1.8 输入 / $7.2 输出）。

Intelligence Index92 / 100
Input Token:

$1.80 / 1M

Output Token:

$7.20 / 1M

Context Window:

1M tokens

SWE-bench Verified:

73.5%

Alibaba

Qwen3.8 Max Preview

开源权重基础大模型

Alibaba 推出的 Qwen3.8 Max Preview 是一款支持私有云服务器自托管、微调与完全数据主权的开源权重基础大模型，具备 1M 上下文窗口、60 Token/秒生成速度与 93/100 综合智能指数（免费开源权重）。

Intelligence Index93 / 100
Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

75.2%

核心差异一览

  • Qwen3.8 Max Preview is 1.0x cheaper for API usage (input + output tokens combined).
  • Qwen3.7 Max is faster at 80 tok/s vs 60 tok/s.
  • Qwen3.8 Max Preview leads on SWE-bench coding (75.2% vs 73.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureQwen3.7 MaxQwen3.8 Max Preview
Intelligence Index
Composite reasoning & knowledge score (0-100)
9293
Provider
AlibabaAlibaba
Input Price
Cost per million input tokens
$1.80 / 1M$0.00 / 1M
Output Price
Cost per million output tokens
$7.20 / 1M$0.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$1.21 / 1M$0.00 / 1M
Context Window
Maximum input + output tokens
1M tokens~1,500 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
32K32K
Throughput Speed
Tokens generated per second
80 tok/s60 tok/s
SWE-bench Verified
Real-world software engineering
73.5%75.2%
GPQA Diamond
Graduate-level reasoning
78.5%79.5%
Cached Input Price
Prompt caching discount per 1M tokens
$0.18 / 1M$0.00 / 1M

各项指标谁更胜一筹？

At-a-glance decision framework
Coding
Qwen3.8 Max Preview
+1.7% SWE-bench lead
Cost
Qwen3.8 Max Preview
1.0x cheaper monthly runtime
Speed
Qwen3.7 Max
+33% faster generation
Context
Tied
1M tokens window

权威基准测试得分对比

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

Qwen3.7 MaxQwen3.8 Max Preview
SWE-bench Verified (Autonomous Coding)

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

73.5%vs75.2%
GPQA Diamond (Doctorate-Level Science & Math)

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

78.5%vs79.5%
MMLU-Pro (Multi-task Language Understanding)

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

88.5%vs89%
LMSYS Chatbot Arena Elo

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

1470ptsvs1485pts
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs77%
AIME (Advanced Math Competition)

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

86%vsN/A
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

80 tok/s vs60 tok/s

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.

Time to First Token (TTFT)Lower is better
Qwen3.7 Max0.58s
Qwen3.8 Max Preview0.68s
Est. End-to-End Response (500 tokens)TTFT + generation time
Qwen3.7 Max6.83s
Qwen3.8 Max Preview9.01s

实时 Token 成本模拟器

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)
Qwen3.7 Max Monthly API Bill
$9.45 / month
$1.8/1M in · $7.2/1M out
Qwen3.8 Max Preview Monthly API Bill
$0.00 / month
$0/1M in · $0/1M out
Qwen3.8 Max Preview saves approximately $9.45 / month (100%) under this workload.1.0x Savings

Qwen3.7 Max · Strengths & Key Advantages

  • 提供 1M 上下文窗口与最高 32K 输出容量，核心基准表现优异（SWE-bench Verified 73.5% · GPQA Diamond 78.5%）
  • 高达 80 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 580 毫秒
  • 极具竞争力的 API 定价（每百万 Token $1.8 输入 / $7.2 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

Qwen3.8 Max Preview · Strengths & Key Advantages

  • 提供 1M 上下文窗口与最高 32K 输出容量，核心基准表现优异（SWE-bench Verified 75.2% · GPQA Diamond 79.5%）
  • 高达 60 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 680 毫秒
  • 开放模型权重 (2.4T total (95B MoE))，支持通过 vLLM、SGLang 或 Ollama 在私有 GPU 集群上本地部署与微调
Considerations & Trade-offs
  • 在本地以满血精度运行需要较高的 GPU 显存 (VRAM) 与运维基础设施
  • 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.

MetricQwen3.7 MaxQwen3.8 Max Preview
Cost per Task
Estimated USD to finish one task
$0.38$0.00
Output Tokens / Task
Tokens generated per task
32K35K
Reasoning Tokens / Task
Thinking tokens burned per task
14K15K

技术规格参数

Architecture, release timeline, capabilities, and modalities.

FeatureQwen3.7 MaxQwen3.8 Max Preview
Official API Model ID (SDK)qwen3-7-max-instructqwen3-8-max-preview-instruct
API ProtocolAlibaba REST API (OpenAI-Compatible)OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2026-052026-07
Knowledge CutoffApril 2026April 2026
ArchitectureNext-Generation Deep Frontier Reasoning TransformerColossus-Scale Open Sparse Mixture-of-Experts
ParametersConfidential2.4T total (95B active MoE)
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPMUnlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)Flat rate ($1.8/1M in) across full 1000K windowFree across full context window (only KV-cache VRAM scales)
Prompt Cache Policy & TTLCached input at $0.18/1M tokensAutomatic prefix KV-caching in vLLM / SGLang (0 cost)
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 toolsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
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)BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 1488 GB VRAM (4-bit Quantized) · 5160 GB VRAM (Native BF16)
Safety & Frontier ClassificationAlibaba Production Safety & Alignment VerifiedOpen-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestexttext, vision
Output Modalitiestexttext

Qwen3.7 Max vs Qwen3.8 Max Preview: 常见问题解答 (FAQ)

Which is more intelligent, Qwen3.7 Max or Qwen3.8 Max Preview?

Qwen3.8 Max Preview is more intelligent. It scores 93 compared with 92 on the composite Intelligence Index.

Which model is faster?

Qwen3.7 Max is faster, generating 80 tokens per second compared with 60 tokens per second.

Which model is cheaper to run?

Qwen3.8 Max Preview is cheaper at $0.00 per 1M tokens blended, compared with $1.21 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Qwen3.7 Max has lower latency, with a time to first token of 0.58s compared with 0.68s.

综合结论

综合来看，Qwen3.7 Max（适合：专为长周期自主智能体 (Agent)、工具调用与自动化工作流打造的任务、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 Qwen3.8 Max Preview（适合：支持私有云服务器自托管、微调与完全数据主权的开源权重基础任务、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：Qwen3.8 Max Preview 在综合智能与编程基准测试中表现更强，Qwen3.7 Max 拥有更快的 Token 生成速度，而 Qwen3.8 Max Preview 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，Qwen3.7 Max 和 Qwen3.8 Max Preview 哪个更强？+

在综合智能指数与编程基准评测中，Qwen3.8 Max Preview 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。

Qwen3.7 Max 与 Qwen3.8 Max Preview 的 API 价格哪个更便宜？+

Qwen3.7 Max 的 API 价格为输入 $1.80 / 输出 $7.20（每百万 Token），Qwen3.8 Max Preview 为输入 $0.00 / 输出 $0.00。综合混合成本来看，Qwen3.8 Max Preview 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？+

Qwen3.7 Max 支持 1M Token 上下文窗口，而 Qwen3.8 Max Preview 支持 1M Token。在流式生成速度方面，Qwen3.7 Max 的吞吐表现更快。

AI Terminology & Guide
Explore Glossary →

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

Tokens & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

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 Alibaba 官方 API 文档、模型发布说明及独立基准测试报告 (2026)。