Head-to-Head Model Comparison

Gemini 4 Argon vs Claude Fable 5.1

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
Gemini 4 Argon vs Claude Fable 5.1: Benchmarks, Pricing & Speed Comparison

Google 的 Gemini 4 Argon 与 Anthropic 的 Claude Fable 5.1 是当前备受关注的两款主力 AI 模型。Gemini 4 Argon 提供 1M Token 上下文窗口,API 定价为每百万 Token 输入 $2.00 / 输出 $10.00;而 Claude Fable 5.1 提供 1M Token 上下文窗口,定价为每百万 Token 输入 $10.00 / 输出 $50.00。以下为两者的基准测试、延迟与成本全面对比。

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Google

Gemini 4 Argon

原生多模态视觉模型

Google 推出的 Gemini 4 Argon 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 1M 上下文窗口、115 Token/秒生成速度与 97/100 综合智能指数(每百万 Token $2 输入 / $10 输出)。

Intelligence Index97 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

81.9%

Anthropic

Claude Fable 5.1

旗舰前沿大模型

Anthropic 推出的 Claude Fable 5.1 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、65 Token/秒生成速度与 82/100 综合智能指数(每百万 Token $10 输入 / $50 输出)。

Intelligence Index82 / 100
Input Token:

$10.00 / 1M

Output Token:

$50.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

83.8%

核心差异一览

  • Gemini 4 Argon is 5.0x cheaper for API usage (input + output tokens combined).
  • Gemini 4 Argon is faster at 115 tok/s vs 65 tok/s.
  • Claude Fable 5.1 leads on SWE-bench coding (83.8% vs 81.9%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGemini 4 ArgonClaude Fable 5.1
Intelligence Index
Composite reasoning & knowledge score (0-100)
9782
Provider
GoogleAnthropic
Input Price
Cost per million input tokens
$2.00 / 1M$10.00 / 1M
Output Price
Cost per million output tokens
$10.00 / 1M$50.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$1.47 / 1M$7.17 / 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
1000K128K
Throughput Speed
Tokens generated per second
115 tok/s65 tok/s
SWE-bench Verified
Real-world software engineering
81.9%83.8%
GPQA Diamond
Graduate-level reasoning
81.5%81.6%
Cached Input Price
Prompt caching discount per 1M tokens
$0.10 / 1M$0.25 / 1M

各项指标谁更胜一筹?

At-a-glance decision framework
Coding
Claude Fable 5.1
+1.9% SWE-bench lead
Cost
Gemini 4 Argon
5.0x cheaper monthly runtime
Speed
Gemini 4 Argon
+77% 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.

Gemini 4 ArgonClaude Fable 5.1
SWE-bench Verified (Autonomous Coding)

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

81.9%vs83.8%
GPQA Diamond (Doctorate-Level Science & Math)

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

81.5%vs81.6%
MMLU-Pro (Multi-task Language Understanding)

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

90.8%vs91%
LMSYS Chatbot Arena Elo

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

1525ptsvs1510pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

18.9%vsN/A
Terminal-Bench (Agentic Coding & Terminal Use)

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

57.4%vs62%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

56.4%vsN/A
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

80.5%vsN/A
AIME (Advanced Math Competition)

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

94.8%vsN/A
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

96.4%vsN/A
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

115 tok/s vs65 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
Gemini 4 Argon0.85s
Claude Fable 5.11.45s
Est. End-to-End Response (500 tokens)TTFT + generation time
Gemini 4 Argon5.20s
Claude Fable 5.19.14s

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)
Gemini 4 Argon Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
Claude Fable 5.1 Monthly API Bill
$60.38 / month
$10/1M in · $50/1M out
Gemini 4 Argon saves approximately $48.23 / month (80%) under this workload.5.0x Savings

Gemini 4 Argon · Strengths & Key Advantages

  • 提供 1M 上下文窗口与最高 1M 输出容量,核心基准表现优异(SWE-bench Verified 81.9% · GPQA Diamond 81.5%)
  • 高达 115 Token/秒的生成吞吐量,首字延迟 (TTFT) 仅约 850 毫秒
  • 极具竞争力的 API 定价(每百万 Token $2 输入 / $10 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

Claude Fable 5.1 · 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 83.8% · GPQA Diamond 81.6%)
  • 高达 65 Token/秒的生成吞吐量,首字延迟 (TTFT) 仅约 1450 毫秒
  • 极具竞争力的 API 定价(每百万 Token $10 输入 / $50 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

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricGemini 4 ArgonClaude Fable 5.1
Cost per Task
Estimated USD to finish one task
$2.45$10.97
Output Tokens / Task
Tokens generated per task
75K72K
Reasoning Tokens / Task
Thinking tokens burned per task
36K37K

技术规格参数

Architecture, release timeline, capabilities, and modalities.

FeatureGemini 4 ArgonClaude Fable 5.1
Official API Model ID (SDK)models/gemini-4-argonclaude-fable-5-1-20260901
API ProtocolGoogle Gemini API (generateContent) + OpenAI-Compatible SDKAnthropic Messages API + AWS Bedrock + Vertex AI
Release Date2026-092026-09
Knowledge CutoffJune 2026June 2026
ArchitecturePathways Multimodal Sparse Mixture-of-ExpertsFrontier Auditable Multimodal Transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 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 & TTLImplicit + Explicit Context Caching at $0.1/1M with configurable TTL$0.25/1M cached read (90% off); 5-min default & 1-hour extended 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 & SandboxBuilt-in Google Search Grounding + Managed Python Code Execution SandboxNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportVertex AI Supervised Adapter Tuning & Context DistillationCustom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)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 ClassificationGoogle DeepMind Frontier Safety Framework VerifiedAnthropic 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 TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, vision, audio, videotext, vision
Output Modalitiestexttext

Gemini 4 Argon vs Claude Fable 5.1: 常见问题解答 (FAQ)

Which is more intelligent, Gemini 4 Argon or Claude Fable 5.1?

Gemini 4 Argon is more intelligent. It scores 97 compared with 82 on the composite Intelligence Index.

Which model is faster?

Gemini 4 Argon is faster, generating 115 tokens per second compared with 65 tokens per second.

Which model is cheaper to run?

Gemini 4 Argon is cheaper at $1.47 per 1M tokens blended, compared with $7.17 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 4 Argon has lower latency, with a time to first token of 0.85s compared with 1.45s.

综合结论

综合来看,Gemini 4 Argon(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 Claude Fable 5.1(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:Gemini 4 Argon 在综合智能与编程基准测试中表现更强,Gemini 4 Argon 拥有更快的 Token 生成速度,而 Gemini 4 Argon 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,Gemini 4 Argon 和 Claude Fable 5.1 哪个更强?+

在综合智能指数与编程基准评测中,Gemini 4 Argon 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。

Gemini 4 Argon 与 Claude Fable 5.1 的 API 价格哪个更便宜?+

Gemini 4 Argon 的 API 价格为输入 $2.00 / 输出 $10.00(每百万 Token),Claude Fable 5.1 为输入 $10.00 / 输出 $50.00。综合混合成本来看,Gemini 4 Argon 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?+

Gemini 4 Argon 支持 1M Token 上下文窗口,而 Claude Fable 5.1 支持 1M Token。在流式生成速度方面,Gemini 4 Argon 的吞吐表现更快。

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