GLM-5V-Turbo vs Claude Opus 5.5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare GLM-5V-Turbo by Zhipu AI against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.
Beliebige Modelle wechseln & vergleichen
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Live comparison: no in-depth editorial review has been published for this pair yet.
GLM-5V-Turbo
Nativ Multimodale KIGLM-5V-Turbo von Zhipu AI ist ein KI-Modell für nativ multimodale Verarbeitung von Text und Bild sowie visuelle Dokumentenanalyse mit 200K Kontextfenster, 85 Token/s Durchsatz, einem Intelligenz-Index von 85/100 und $0.9/$2.7 pro 1M Token.
$0.90 / 1M
$2.70 / 1M
200K tokens
N/A
Claude Opus 5.5
Frontier-Flaggschiff-ModellClaude Opus 5.5 von Anthropic ist ein KI-Modell für anspruchsvolles Enterprise-Reasoning, Softwareentwicklung und produktive KI-Workflows mit 1M Kontextfenster, 78 Token/s Durchsatz, einem Intelligenz-Index von 94/100 und $4/$20 pro 1M Toke
$4.00 / 1M
$20.00 / 1M
1M tokens
84.6%
Wichtigste Unterschiede auf einen Blick
- GLM-5V-Turbo is 6.3x cheaper for API usage (input + output tokens combined).
- Claude Opus 5.5 has a larger context window (1M vs 200K tokens).
- GLM-5V-Turbo is faster at 85 tok/s vs 78 tok/s.
| Feature | GLM-5V-Turbo | Claude Opus 5.5 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 85 | 94 |
Provider | Zhipu AI | Anthropic |
Input Price Cost per million input tokens | $0.90 / 1M | $4.00 / 1M |
Output Price Cost per million output tokens | $2.70 / 1M | $20.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.51 / 1M | $3.08 / 1M |
Context Window Maximum input + output tokens | 200K tokens~300 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 16K | 128K |
Throughput Speed Tokens generated per second | 85 tok/s | 78 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 84.6% |
GPQA Diamond Graduate-level reasoning | 64% | 82.3% |
Cached Input Price Prompt caching discount per 1M tokens | $0.09 / 1M | $0.40 / 1M |
Wer gewinnt in welcher Disziplin?
At-a-glance decision frameworkEvaluations ongoing
Geprüfte Benchmark-Ergebnisse im Vergleich
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.
Latenz & Antwortzeit
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Interaktiver Token-Kosten-Simulator
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
GLM-5V-Turbo · Strengths & Key Advantages
- 200K Kontextfenster und bis zu 16K maximale Output-Token (GPQA Diamond 64% · MMLU-Pro 81%)
- Hohe Generierungsgeschwindigkeit von 85 Token/Sekunde bei nur 490 ms Erstlatenz (TTFT)
- Effiziente API-Struktur ($0.9/$2.7 pro 1M Token) inklusive Prompt-Caching, Tool-Calling und strikter JSON-Ausgabe
Considerations & Trade-offs
- Proprietäres Cloud-Modell ohne Möglichkeit zum lokalen Download der Modellgewichte
- Bei extrem komplexen mehrstufigen Forschungsfragen bieten schwere Reasoning-Spezialmodelle noch tiefere Analysen
Claude Opus 5.5 · Strengths & Key Advantages
- 1M Kontextfenster und bis zu 128K maximale Output-Token (SWE-bench Verified 84.6% · GPQA Diamond 82.3%)
- Hohe Generierungsgeschwindigkeit von 78 Token/Sekunde bei nur 1400 ms Erstlatenz (TTFT)
- Effiziente API-Struktur ($4/$20 pro 1M Token) inklusive Prompt-Caching, Tool-Calling und strikter JSON-Ausgabe
Considerations & Trade-offs
- Proprietäres Cloud-Modell ohne Möglichkeit zum lokalen Download der Modellgewichte
- Bei hohem Anfragevolumen empfiehlt sich der Einsatz von Prompt-Caching und Batch-API zur Kostenoptimierung
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | GLM-5V-Turbo | Claude Opus 5.5 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.22 | $3.85 |
Output Tokens / Task Tokens generated per task | 20K | 68K |
Reasoning Tokens / Task Thinking tokens burned per task | 6K | 42K |
Technische Spezifikationen
Architecture, release timeline, capabilities, and modalities.
| Feature | GLM-5V-Turbo | Claude Opus 5.5 |
|---|---|---|
| Official API Model ID (SDK) | glm-5v-turbo | claude-opus-5-5-20260901 |
| API Protocol | Zhipu AI REST API (OpenAI-Compatible) | Anthropic Messages API + AWS Bedrock + Vertex AI |
| Release Date | 2026-04 | 2026-09 |
| Knowledge Cutoff | February 2026 | June 2026 |
| Architecture | Frontier Commercial Vision-Language Transformer | Extended Autonomous Hybrid Reasoning Transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.9/1M in) across full 200K window | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Cached input at $0.09/1M tokens | $0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | 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 Citations + Code Execution Tool + MCP Connectors |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | Custom Model Tuning via Amazon Bedrock & Prompt Distillation |
| Multimodal Token Billing | Text 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 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 | Anthropic 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 Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text, vision | text, vision |
| Output Modalities | text | text |
GLM-5V-Turbo vs Claude Opus 5.5: Schnelle Antworten (FAQ)
Which is more intelligent, GLM-5V-Turbo or Claude Opus 5.5?
Claude Opus 5.5 is more intelligent. It scores 94 compared with 85 on the composite Intelligence Index.
Which model is faster?
GLM-5V-Turbo is faster, generating 85 tokens per second compared with 78 tokens per second.
Which model is cheaper to run?
GLM-5V-Turbo is cheaper at $0.51 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).
Which model has lower latency?
GLM-5V-Turbo has lower latency, with a time to first token of 0.49s compared with 1.40s.
Which model has a larger context window?
Claude Opus 5.5 has a larger context window, supporting 1M tokens compared with 200K tokens.
Fazit
Choose GLM-5V-Turbo for optimal für nativ multimodale verarbeitung von text und bild sowie visuelle dokumentenanalyse, enterprise-rag-systeme und skalierbare api-pipelines., or choose Claude Opus 5.5 for optimal für anspruchsvolles enterprise-reasoning, softwareentwicklung und produktive ki-workflows, enterprise-rag-systeme und skalierbare api-pipelines..
Häufig gestellte Fragen (FAQ)
Which is cheaper: GLM-5V-Turbo or Claude Opus 5.5?+
GLM-5V-Turbo costs $0.9/1M input and $2.7/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.
Which model has a larger context window: GLM-5V-Turbo or Claude Opus 5.5?+
GLM-5V-Turbo supports 200K tokens whereas Claude Opus 5.5 supports 1M tokens.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
- Aion-3.0 vs. Aion-Mini: Benchmarks, API-Preise & Geschwindigkeit im Vergleich (2026)Vergleich
- Aion-3.0 vs. Gemini 3.6 Flash: Benchmarks, API-Preise & Geschwindigkeit im Vergleich (2026)Vergleich
- Aion-Mini vs. Laguna XS 2.1: Benchmarks, API-Preise & Geschwindigkeit im Vergleich (2026)Vergleich
- Aya Expanse 32B vs. Llama 3.2 90B Vision: Benchmarks, API-Preise & Geschwindigkeit im Vergleich (2026)Vergleich
- Aya Expanse 8B vs. Command R+: Benchmarks, API-Preise & Geschwindigkeit im Vergleich (2026)Vergleich
- Aya Expanse 8B vs. Qwen 2.5 7B Instruct: Benchmarks, API-Preise & Geschwindigkeit im Vergleich (2026)Vergleich
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.
Offizielle Quellen: Zhipu AI & Anthropic Official Documentation