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Head-to-Head Model Comparison

GPT-6 Astra vs Claude Sonnet 4.5

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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Compare GPT-6 Astra by OpenAI against Claude Sonnet 4.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

模型直接对比 (VS)

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OpenAI

GPT-6 Astra

原生语音与音频大模型

OpenAI 推出的 GPT-6 Astra 是一款专注于超自然语音合成、实时音频理解与低延迟语音交互的大模型，具备 272K 上下文窗口、100 Token/秒生成速度与 96/100 综合智能指数（每百万 Token $10 输入 / $50 输出）。

Intelligence Index96 / 100
Input Token:

$10.00 / 1M

Output Token:

$50.00 / 1M

Context Window:

272K tokens

SWE-bench Verified:

82.4%

Anthropic

Claude Sonnet 4.5

旗舰前沿大模型

Anthropic 推出的 Claude Sonnet 4.5 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、90 Token/秒生成速度与 91/100 综合智能指数（每百万 Token $3 输入 / $15 输出）。

Intelligence Index91 / 100
Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

77.8%

核心差异一览

  • Claude Sonnet 4.5 is 3.3x cheaper for API usage (input + output tokens combined).
  • Claude Sonnet 4.5 has a larger context window (1M vs 272K tokens).
  • GPT-6 Astra is faster at 100 tok/s vs 90 tok/s.
  • GPT-6 Astra leads on SWE-bench coding (82.4% vs 77.8%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGPT-6 AstraClaude Sonnet 4.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
9691
Provider
OpenAIAnthropic
Input Price
Cost per million input tokens
$10.00 / 1M$3.00 / 1M
Output Price
Cost per million output tokens
$50.00 / 1M$15.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$7.70 / 1M$2.31 / 1M
Context Window
Maximum input + output tokens
272K tokens~408 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
128K64K
Throughput Speed
Tokens generated per second
100 tok/s90 tok/s
SWE-bench Verified
Real-world software engineering
82.4%77.8%
GPQA Diamond
Graduate-level reasoning
80.9%70.2%
Cached Input Price
Prompt caching discount per 1M tokens
$1.00 / 1M$0.30 / 1M

各项指标谁更胜一筹？

At-a-glance decision framework
Coding
GPT-6 Astra
+4.6% SWE-bench lead
Cost
Claude Sonnet 4.5
3.3x cheaper monthly runtime
Speed
GPT-6 Astra
+11% faster generation
Context
Claude Sonnet 4.5
1M tokens window

权威基准测试得分对比

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

GPT-6 AstraClaude Sonnet 4.5
SWE-bench Verified (Autonomous Coding)

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

82.4%vs77.8%
GPQA Diamond (Doctorate-Level Science & Math)

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

80.9%vs70.2%
MMLU-Pro (Multi-task Language Understanding)

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

89.9%vs84.5%
LMSYS Chatbot Arena Elo

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

1520ptsvs1355pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

18.2%vs10.4%
Terminal-Bench (Agentic Coding & Terminal Use)

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

63.8%vs50.1%
SciCode (Scientific Computing)

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

54.9%vs43.9%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

79.8%vs72.6%
AIME (Advanced Math Competition)

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

93.6%vs84.7%
Long-Context Reasoning

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

91.2%vs74.8%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

100 tok/s vs90 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
GPT-6 Astra0.95s
Claude Sonnet 4.50.90s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT-6 Astra5.95s
Claude Sonnet 4.56.46s

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)
GPT-6 Astra Monthly API Bill
$61.50 / month
$10/1M in · $50/1M out
Claude Sonnet 4.5 Monthly API Bill
$18.45 / month
$3/1M in · $15/1M out
Claude Sonnet 4.5 saves approximately $43.05 / month (70%) under this workload.3.3x Savings

GPT-6 Astra · Strengths & Key Advantages

  • 提供 272K 上下文窗口与最高 128K 输出容量，核心基准表现优异（SWE-bench Verified 82.4% · GPQA Diamond 80.9%）
  • 高达 100 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 950 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

Claude Sonnet 4.5 · Strengths & Key Advantages

  • 提供 1M 上下文窗口与最高 64K 输出容量，核心基准表现优异（SWE-bench Verified 77.8% · GPQA Diamond 70.2%）
  • 高达 90 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 900 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

Token Use & Task Economics

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

MetricGPT-6 AstraClaude Sonnet 4.5
Cost per Task
Estimated USD to finish one task
$2.15$2.10
Output Tokens / Task
Tokens generated per task
58K55K
Reasoning Tokens / Task
Thinking tokens burned per task
32K30K

技术规格参数

Architecture, release timeline, capabilities, and modalities.

FeatureGPT-6 AstraClaude Sonnet 4.5
Official API Model ID (SDK)gpt-6-astraclaude-sonnet-4-5-20251101
API ProtocolOpenAI Responses API & Chat Completions v1Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2026-092025-11
Knowledge CutoffJune 2026March 2025
ArchitectureOmni-Adaptive Autoregressive with Dynamic CoTHybrid Reasoning
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($10/1M in) across full 272K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLAutomatic prefix caching at $1/1M (no extra cache-write fee)$0.3/1M 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 & SandboxNative Web Search tool + Hosted Code Interpreter & File Search RAGNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)Custom 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)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 ClassificationOpenAI Preparedness Framework Audited & System Card PublishedAnthropic 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, audiotext, vision
Output Modalitiestext, audiotext

GPT-6 Astra vs Claude Sonnet 4.5: 常见问题解答 (FAQ)

Which is more intelligent, GPT-6 Astra or Claude Sonnet 4.5?

GPT-6 Astra is more intelligent. It scores 96 compared with 91 on the composite Intelligence Index.

Which model is faster?

GPT-6 Astra is faster, generating 100 tokens per second compared with 90 tokens per second.

Which model is cheaper to run?

Claude Sonnet 4.5 is cheaper at $2.31 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude Sonnet 4.5 has lower latency, with a time to first token of 0.90s compared with 0.95s.

Which model has a larger context window?

Claude Sonnet 4.5 has a larger context window, supporting 1M tokens compared with 272K tokens.

综合结论

Choose GPT-6 Astra for 专注于超自然语音合成、实时音频理解与低延迟语音交互的任务、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。, or choose Claude Sonnet 4.5 for 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。.

常见问题 (FAQ)

Which is cheaper: GPT-6 Astra or Claude Sonnet 4.5?+

GPT-6 Astra costs $10/1M input and $50/1M output tokens, while Claude Sonnet 4.5 costs $3/1M input and $15/1M output tokens.

Which model has a larger context window: GPT-6 Astra or Claude Sonnet 4.5?+

GPT-6 Astra supports 272K tokens whereas Claude Sonnet 4.5 supports 1M tokens.

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: OpenAI & Anthropic Official Documentation