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Claude Sonnet 4.6 vs Gemini 3.1 Flash-Lite

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
Claude Sonnet 4.6 vs Gemini 3.1 Flash-Lite: Benchmarks, Pricing & Speed Comparison

Anthropic 的 Claude Sonnet 4.6 与 Google 的 Gemini 3.1 Flash-Lite 是当前备受关注的两款主力 AI 模型。Claude Sonnet 4.6 提供 1M Token 上下文窗口，API 定价为每百万 Token 输入 $3.00 / 输出 $15.00；而 Gemini 3.1 Flash-Lite 提供 1.05M Token 上下文窗口，定价为每百万 Token 输入 $0.15 / 输出 $0.60。以下为两者的基准测试、延迟与成本全面对比。

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Anthropic

Claude Sonnet 4.6

旗舰前沿大模型

Anthropic 推出的 Claude Sonnet 4.6 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 1M 上下文窗口、92 Token/秒生成速度与 60/100 综合智能指数（每百万 Token $3 输入 / $15 输出）。

Intelligence Index60 / 100
Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

76.1%

Google

Gemini 3.1 Flash-Lite

轻量级高性价比模型

Google 推出的 Gemini 3.1 Flash-Lite 是一款兼顾极低 API 调用成本与高吞吐效率的轻量级大模型，具备 1.0M 上下文窗口、250 Token/秒生成速度与 60/100 综合智能指数（每百万 Token $0.15 输入 / $0.6 输出）。

Intelligence Index60 / 100
Input Token:

$0.15 / 1M

Output Token:

$0.60 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

N/A

核心差异一览

  • Gemini 3.1 Flash-Lite is 22.6x cheaper for API usage (input + output tokens combined).
  • Gemini 3.1 Flash-Lite has a larger context window (1M vs 1M tokens).
  • Gemini 3.1 Flash-Lite is faster at 250 tok/s vs 92 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureClaude Sonnet 4.6Gemini 3.1 Flash-Lite
Intelligence Index
Composite reasoning & knowledge score (0-100)
6060
Provider
AnthropicGoogle
Input Price
Cost per million input tokens
$3.00 / 1M$0.15 / 1M
Output Price
Cost per million output tokens
$15.00 / 1M$0.60 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$2.31 / 1M$0.11 / 1M
Context Window
Maximum input + output tokens
1M tokens~1,500 A4 pages of text1.05M tokens~1,573 A4 pages of text
Max Output Tokens
Per single request
128K33K
Throughput Speed
Tokens generated per second
92 tok/s250 tok/s
SWE-bench Verified
Real-world software engineering
76.1%N/A
GPQA Diamond
Graduate-level reasoning
74%N/A
Cached Input Price
Prompt caching discount per 1M tokens
$0.30 / 1M$0.04 / 1M

各项指标谁更胜一筹？

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Gemini 3.1 Flash-Lite
22.6x cheaper monthly runtime
Speed
Gemini 3.1 Flash-Lite
+172% faster generation
Context
Gemini 3.1 Flash-Lite
1.05M tokens window

权威基准测试得分对比

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

Claude Sonnet 4.6Gemini 3.1 Flash-Lite
SWE-bench Verified (Autonomous Coding)

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

76.1%vsN/A
GPQA Diamond (Doctorate-Level Science & Math)

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

74%vsN/A
MMLU-Pro (Multi-task Language Understanding)

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

86.7%vs78.5%
LMSYS Chatbot Arena Elo

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

1380ptsvs1355pts
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

47.8%vsN/A
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

92 tok/s vs250 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
Claude Sonnet 4.60.65s
Gemini 3.1 Flash-Lite0.27s
Est. End-to-End Response (500 tokens)TTFT + generation time
Claude Sonnet 4.66.08s
Gemini 3.1 Flash-Lite2.27s

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)
Claude Sonnet 4.6 Monthly API Bill
$18.45 / month
$3/1M in · $15/1M out
Gemini 3.1 Flash-Lite Monthly API Bill
$0.82 / month
$0.15/1M in · $0.6/1M out
Gemini 3.1 Flash-Lite saves approximately $17.63 / month (96%) under this workload.22.6x Savings

Claude Sonnet 4.6 · Strengths & Key Advantages

  • 提供 1M 上下文窗口与最高 128K 输出容量，核心基准表现优异（SWE-bench Verified 76.1% · GPQA Diamond 74%）
  • 高达 92 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 650 毫秒
  • 极具竞争力的 API 定价（每百万 Token $3 输入 / $15 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
  • 在大规模高频调用场景下，建议结合提示词缓存 (Prompt Caching) 与批量 API 以控制成本

Gemini 3.1 Flash-Lite · Strengths & Key Advantages

  • 提供 1.0M 上下文窗口与最高 33K 输出容量，核心基准表现优异（MMLU-Pro 78.5% · Arena Elo 1355）
  • 高达 250 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 270 毫秒
  • 极具竞争力的 API 定价（每百万 Token $0.15 输入 / $0.6 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.

MetricClaude Sonnet 4.6Gemini 3.1 Flash-Lite
Cost per Task
Estimated USD to finish one task
$3.29$0.38
Output Tokens / Task
Tokens generated per task
72K14K
Reasoning Tokens / Task
Thinking tokens burned per task
37K5K

技术规格参数

Architecture, release timeline, capabilities, and modalities.

FeatureClaude Sonnet 4.6Gemini 3.1 Flash-Lite
Official API Model ID (SDK)claude-sonnet-4-6-20260201models/gemini-3-1-flash-lite
API ProtocolAnthropic Messages API + AWS Bedrock + Vertex AIGoogle Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date2026-022026-03
Knowledge CutoffDecember 2025November 2025
ArchitectureHigh-Throughput Multimodal Agent TransformerCompact efficient multimodal transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Standard rate up to 200K tokens; 2x input/output tier above 200K tokensStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL$0.3/1M cached read (90% off); 5-min default & 1-hour extended TTLImplicit + Explicit Context Caching at $0.035/1M with configurable TTL
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)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 & SandboxNative Web Search Citations + Code Execution Tool + MCP ConnectorsBuilt-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning SupportCustom Model Tuning via Amazon Bedrock & Prompt DistillationVertex AI Supervised Adapter Tuning & Context Distillation
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)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)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationAnthropic RSP ASL-2 / ASL-3 Constitutional Safety EvaluatedGoogle DeepMind Frontier Safety Framework Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision
Output Modalitiestexttext

Claude Sonnet 4.6 vs Gemini 3.1 Flash-Lite: 常见问题解答 (FAQ)

Which model is faster?

Gemini 3.1 Flash-Lite is faster, generating 250 tokens per second compared with 92 tokens per second.

Which model is cheaper to run?

Gemini 3.1 Flash-Lite is cheaper at $0.11 per 1M tokens blended, compared with $2.31 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 3.1 Flash-Lite has lower latency, with a time to first token of 0.27s compared with 0.65s.

Which model has a larger context window?

Gemini 3.1 Flash-Lite has a larger context window, supporting 1.05M tokens compared with 1M tokens.

综合结论

综合来看，Claude Sonnet 4.6（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。）与 Gemini 3.1 Flash-Lite（适合：兼顾极低 API 调用成本与高吞吐效率的轻量级任务、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：Claude Sonnet 4.6 在综合智能与编程基准测试中表现更强，Gemini 3.1 Flash-Lite 拥有更快的 Token 生成速度，而 Gemini 3.1 Flash-Lite 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，Claude Sonnet 4.6 和 Gemini 3.1 Flash-Lite 哪个更强？+

在综合智能指数与编程基准评测中，Claude Sonnet 4.6 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。

Claude Sonnet 4.6 与 Gemini 3.1 Flash-Lite 的 API 价格哪个更便宜？+

Claude Sonnet 4.6 的 API 价格为输入 $3.00 / 输出 $15.00（每百万 Token），Gemini 3.1 Flash-Lite 为输入 $0.15 / 输出 $0.60。综合混合成本来看，Gemini 3.1 Flash-Lite 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？+

Claude Sonnet 4.6 支持 1M Token 上下文窗口，而 Gemini 3.1 Flash-Lite 支持 1.05M Token。在流式生成速度方面，Gemini 3.1 Flash-Lite 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: Anthropic 与 Google 官方 API 文档、模型发布说明及独立基准测试报告 (2026)。