Head-to-Head Model Comparison

GLM-5-Turbo vs GPT-6 Astra

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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Compare GLM-5-Turbo by Zhipu AI against GPT-6 Astra by OpenAI across real-world coding, reasoning, token economics, and latency.

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Live comparison: no in-depth editorial review has been published for this pair yet.

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GLM-5-Turbo

Derin Akıl Yürütme Modeli

Zhipu AI tarafından geliştirilen GLM-5-Turbo, 200K token bağlam penceresi ve 1M girdi başına $0.6, 1M çıktı başına $1.8 API fiyatlandırmasıyla yazılım geliştirme, analiz ve kurumsal otomasyon için tasarlanmıştır.

Intelligence Index86 / 100
Input Token:

$0.60 / 1M

Output Token:

$1.80 / 1M

Context Window:

200K tokens

SWE-bench Verified:

55%

OpenAI

GPT-6 Astra

Derin Akıl Yürütme Modeli

OpenAI tarafından geliştirilen GPT-6 Astra, 1M token bağlam penceresi ve 1M girdi başına $10.0, 1M çıktı başına $50.0 API fiyatlandırmasıyla yazılım geliştirme, analiz ve kurumsal otomasyon için tasarlanmıştır.

Intelligence Index96 / 100
Input Token:

$10.00 / 1M

Output Token:

$50.00 / 1M

Context Window:

272K tokens

SWE-bench Verified:

82.4%

Bir Bakışta Temel Farklar

  • GLM-5-Turbo is 23.6x cheaper for API usage (input + output tokens combined).
  • GPT-6 Astra has a larger context window (272K vs 200K tokens).
  • GPT-6 Astra is faster at 100 tok/s vs 95 tok/s.
  • GPT-6 Astra leads on SWE-bench coding (82.4% vs 55.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGLM-5-TurboGPT-6 Astra
Intelligence Index
Composite reasoning & knowledge score (0-100)
8696
Provider
Zhipu AIOpenAI
Input Price
Cost per million input tokens
$0.60 / 1M$10.00 / 1M
Output Price
Cost per million output tokens
$1.80 / 1M$50.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.34 / 1M$7.70 / 1M
Context Window
Maximum input + output tokens
200K tokens~300 A4 pages of text272K tokens~408 A4 pages of text
Max Output Tokens
Per single request
16K128K
Throughput Speed
Tokens generated per second
95 tok/s100 tok/s
SWE-bench Verified
Real-world software engineering
55%82.4%
GPQA Diamond
Graduate-level reasoning
65%80.9%
Cached Input Price
Prompt caching discount per 1M tokens
$0.06 / 1M$1.00 / 1M

Hangi Alanda Kim Kazanıyor?

At-a-glance decision framework
Coding
GPT-6 Astra
+27.4% SWE-bench lead
Cost
GLM-5-Turbo
23.6x cheaper monthly runtime
Speed
GPT-6 Astra
+5% faster generation
Context
GPT-6 Astra
272K tokens window

Doğrulanmış Benchmark Puanları

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

GLM-5-TurboGPT-6 Astra
SWE-bench Verified (Autonomous Coding)

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

55%vs82.4%
GPQA Diamond (Doctorate-Level Science & Math)

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

65%vs80.9%
MMLU-Pro (Multi-task Language Understanding)

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

82.5%vs89.9%
LMSYS Chatbot Arena Elo

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

1365ptsvs1520pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs18.2%
Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs63.8%
SciCode (Scientific Computing)

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

N/Avs54.9%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs79.8%
AIME (Advanced Math Competition)

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

N/Avs93.6%
Long-Context Reasoning

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

N/Avs91.2%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

95 tok/s vs100 tok/s

Gecikme Süresi ve Yanıt Hızı

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
GLM-5-Turbo0.42s
GPT-6 Astra0.95s
Est. End-to-End Response (500 tokens)TTFT + generation time
GLM-5-Turbo5.68s
GPT-6 Astra5.95s

Gerçek Zamanlı Token Maliyet Simülatörü

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)
GLM-5-Turbo Monthly API Bill
$2.61 / month
$0.6/1M in · $1.8/1M out
GPT-6 Astra Monthly API Bill
$61.50 / month
$10/1M in · $50/1M out
GLM-5-Turbo saves approximately $58.89 / month (96%) under this workload.23.6x Savings

GLM-5-Turbo · Strengths & Key Advantages

  • Zhipu AI imzalı gelişmiş Hosted Accelerated Frontier Transformer mimarisi ve 200K token bağlam kapasitesi
  • Dengeli API maliyeti ($0.6/1M girdi, $1.8/1M çıktı) ve yüksek yanıt hızı
  • Kod üretimi, mantıksal çıkarım ve çok dilli görevlerde güçlü kıyaslama (benchmark) sonuçları
Considerations & Trade-offs
  • Çok uzun bağlamlı sorgularda token maliyetlerinin dikkatli yönetilmesi gerekir
  • Alan bazlı özel iş akışlarında en yüksek verim için doğru istem (prompt) tasarımı önerilir

GPT-6 Astra · Strengths & Key Advantages

  • OpenAI imzalı gelişmiş Omni-Adaptive Autoregressive with Dynamic CoT mimarisi ve 1M token bağlam kapasitesi
  • Dengeli API maliyeti ($10.0/1M girdi, $50.0/1M çıktı) ve yüksek yanıt hızı
  • Kod üretimi, mantıksal çıkarım ve çok dilli görevlerde güçlü kıyaslama (benchmark) sonuçları
Considerations & Trade-offs
  • Çok uzun bağlamlı sorgularda token maliyetlerinin dikkatli yönetilmesi gerekir
  • Alan bazlı özel iş akışlarında en yüksek verim için doğru istem (prompt) tasarımı önerilir

Token Use & Task Economics

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

MetricGLM-5-TurboGPT-6 Astra
Cost per Task
Estimated USD to finish one task
$0.16$2.15
Output Tokens / Task
Tokens generated per task
22K58K
Reasoning Tokens / Task
Thinking tokens burned per task
7K32K

Teknik Özellikler

Architecture, release timeline, capabilities, and modalities.

FeatureGLM-5-TurboGPT-6 Astra
Official API Model ID (SDK)glm-5-turbogpt-6-astra
API ProtocolZhipu AI REST API (OpenAI-Compatible)OpenAI Responses API & Chat Completions v1
Release Date2026-032026-09
Knowledge CutoffJanuary 2026June 2026
ArchitectureHosted Accelerated Frontier TransformerOmni-Adaptive Autoregressive with Dynamic CoT
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.6/1M in) across full 200K windowFlat rate ($10/1M in) across full 272K window
Prompt Cache Policy & TTLCached input at $0.06/1M tokensAutomatic prefix caching at $1/1M (no extra cache-write fee)
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 toolsNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)
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 ClassificationZhipu AI Production Safety & Alignment VerifiedOpenAI Preparedness Framework Audited & System Card Published
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 Modalitiestexttext, vision, audio
Output Modalitiestexttext, audio

GLM-5-Turbo vs GPT-6 Astra: Hızlı Yanıtlar (SSS)

Which is more intelligent, GLM-5-Turbo or GPT-6 Astra?

GPT-6 Astra is more intelligent. It scores 96 compared with 86 on the composite Intelligence Index.

Which model is faster?

GPT-6 Astra is faster, generating 100 tokens per second compared with 95 tokens per second.

Which model is cheaper to run?

GLM-5-Turbo is cheaper at $0.34 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GLM-5-Turbo has lower latency, with a time to first token of 0.42s compared with 0.95s.

Which model has a larger context window?

GPT-6 Astra has a larger context window, supporting 272K tokens compared with 200K tokens.

Sonuç

Choose GLM-5-Turbo for kurumsal otomasyon, yazılım mühendisliği, otonom yz ajanları ve zhipu ai tabanlı üretim sistemleri, or choose GPT-6 Astra for kurumsal otomasyon, yazılım mühendisliği, otonom yz ajanları ve openai tabanlı üretim sistemleri.

Sıkça Sorulan Sorular (SSS)

Which is cheaper: GLM-5-Turbo or GPT-6 Astra?+

GLM-5-Turbo costs $0.6/1M input and $1.8/1M output tokens, while GPT-6 Astra costs $10/1M input and $50/1M output tokens.

Which model has a larger context window: GLM-5-Turbo or GPT-6 Astra?+

GLM-5-Turbo supports 200K tokens whereas GPT-6 Astra supports 272K 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.

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.

Resmi kaynaklar: Zhipu AI & OpenAI Official Documentation