GLM-5-Turbo vs GPT-6 Astra
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
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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GLM-5-Turbo
Faster GLM-5Hosted commercial accelerator of the GLM-5 architecture offering reduced latency and optimized tool execution for demanding enterprise apps.
$0.60 / 1M
$1.80 / 1M
200K tokens
55%
GPT-6 Astra
Autonomous OS AgentOpenAI's late-2026 flagship foundation model featuring native Computer-Use agents, dynamic UI orchestration, and deep STEM reasoning.
$10.00 / 1M
$50.00 / 1M
272K tokens
82.4%
Key Differences at a Glance
- 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%).
| Feature | GLM-5-Turbo | GPT-6 Astra |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 86 | 96 |
Provider | Zhipu AI | OpenAI |
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 text | 272K tokens~408 A4 pages of text |
Max Output Tokens Per single request | 16K | 128K |
Throughput Speed Tokens generated per second | 95 tok/s | 100 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 |
Who Wins Where?
At-a-glance decision frameworkEmpirical Head-to-Head Benchmark Scores
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latency & Response Time
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Real-Time Interactive Token Cost Simulator
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
GLM-5-Turbo · Strengths & Key Advantages
- Reduced latency and swift time-to-first-token compared to raw open-source cluster serving
- Reliable enterprise SLA backed by official Zhipu Cloud infrastructure
- Affordable $0.60/1M input pricing for flagship-grade intelligence
Considerations & Trade-offs
- Proprietary hosted endpoint rather than freely downloadable weights
- Context window is 200K compared to 1M on the upcoming GLM-5.2 tier
GPT-6 Astra · Strengths & Key Advantages
- Flawless OS-level navigation and Computer-Use automation
- Seamless real-time multimodal voice and vision interactivity
- Dynamic Chain-of-Thought that self-adjusts depth based on query difficulty
- Huge 1M context window with instant prefix caching
Considerations & Trade-offs
- Strict safety filters can occasionally throttle complex penetration testing prompts
- Slightly higher reasoning latency on high-effort math queries
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | GLM-5-Turbo | GPT-6 Astra |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.16 | $2.15 |
Output Tokens / Task Tokens generated per task | 22K | 58K |
Reasoning Tokens / Task Thinking tokens burned per task | 7K | 32K |
Technical Specifications
Architecture, release timeline, capabilities, and modalities.
| Feature | GLM-5-Turbo | GPT-6 Astra |
|---|---|---|
| Official API Model ID (SDK) | glm-5-turbo | gpt-6-astra |
| API Protocol | Zhipu AI REST API (OpenAI-Compatible) | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2026-03 | 2026-09 |
| Knowledge Cutoff | January 2026 | June 2026 |
| Architecture | Hosted Accelerated Frontier Transformer | Omni-Adaptive Autoregressive with Dynamic CoT |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 10,000 – 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 window | Flat rate ($10/1M in) across full 272K window |
| Prompt Cache Policy & TTL | Cached input at $0.06/1M tokens | Automatic prefix caching at $1/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) |
| Quantization & Min GPU VRAM | Cloud-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 Classification | Zhipu AI Production Safety & Alignment Verified | OpenAI Preparedness Framework Audited & System Card Published |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text | text, vision, audio |
| Output Modalities | text | text, audio |
GLM-5-Turbo vs GPT-6 Astra: Quick Answers
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.
Verdict
Choose GLM-5-Turbo for high-throughput enterprise applications, code assistants, and automated customer workflows, or choose GPT-6 Astra for autonomous browser/computer workflows, real-time voice agents, and high-difficulty mathematical reasoning.
Frequently asked questions
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.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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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.
Sources: Zhipu AI & OpenAI Official Documentation