Claude 3.5 Haiku vs GPT-6 Astra
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Claude 3.5 Haiku by Anthropic against GPT-6 Astra by OpenAI across real-world coding, reasoning, token economics, and latency.
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Claude 3.5 Haiku
Hochleistungs-KI-ModellClaude 3.5 Haiku von Anthropic ist ein leistungsstarkes KI-Modell mit einem Kontextfenster von 200K Token zu API-Preisen von $0.8/1M Input- und $4/1M Output-Token für Softwareentwicklung, Analyse und Enterprise-Workflows.
$0.80 / 1M
$4.00 / 1M
200K tokens
40.6%
GPT-6 Astra
Deep-Reasoning-ModellGPT-6 Astra von OpenAI ist ein leistungsstarkes KI-Modell mit einem Kontextfenster von 1M Token zu API-Preisen von $10.0/1M Input- und $50.0/1M Output-Token für Softwareentwicklung, Analyse und Enterprise-Workflows.
$10.00 / 1M
$50.00 / 1M
272K tokens
82.4%
Wichtigste Unterschiede auf einen Blick
- Claude 3.5 Haiku is 12.5x cheaper for API usage (input + output tokens combined).
- GPT-6 Astra has a larger context window (272K vs 200K tokens).
- Claude 3.5 Haiku is faster at 130 tok/s vs 100 tok/s.
- GPT-6 Astra leads on SWE-bench coding (82.4% vs 40.6%).
| Feature | Claude 3.5 Haiku | GPT-6 Astra |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 36 | 96 |
Provider | Anthropic | OpenAI |
Input Price Cost per million input tokens | $0.80 / 1M | $10.00 / 1M |
Output Price Cost per million output tokens | $4.00 / 1M | $50.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.62 / 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 | 8K | 128K |
Throughput Speed Tokens generated per second | 130 tok/s | 100 tok/s |
SWE-bench Verified Real-world software engineering | 40.6% | 82.4% |
GPQA Diamond Graduate-level reasoning | 41.6% | 80.9% |
Cached Input Price Prompt caching discount per 1M tokens | $0.08 / 1M | $1.00 / 1M |
Wer gewinnt in welcher Disziplin?
At-a-glance decision frameworkGeprüfte 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.
Claude 3.5 Haiku · Strengths & Key Advantages
- Fortschrittliche Optimized Lightweight Transformer-Architektur von Anthropic mit 200K Token Kontextfenster
- Starkes Preis-Leistungs-Verhältnis ($0.8/1M Input, $4/1M Output) bei hoher Durchsatzrate
- Hohe Präzision bei Code-Generierung, logischem Schließen und mehrsprachigen Benchmarks
Considerations & Trade-offs
- Bei sehr großen Kontextmengen ist eine sorgfältige Token-Budgetierung ratsam
- Spezialisierte Fachaufgaben profitieren von gezieltem Prompt-Engineering
GPT-6 Astra · Strengths & Key Advantages
- Fortschrittliche Omni-Adaptive Autoregressive with Dynamic CoT-Architektur von OpenAI mit 1M Token Kontextfenster
- Starkes Preis-Leistungs-Verhältnis ($10.0/1M Input, $50.0/1M Output) bei hoher Durchsatzrate
- Hohe Präzision bei Code-Generierung, logischem Schließen und mehrsprachigen Benchmarks
Considerations & Trade-offs
- Bei sehr großen Kontextmengen ist eine sorgfältige Token-Budgetierung ratsam
- Spezialisierte Fachaufgaben profitieren von gezieltem Prompt-Engineering
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Claude 3.5 Haiku | GPT-6 Astra |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.90 | $2.15 |
Output Tokens / Task Tokens generated per task | 45K | 58K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 32K |
Technische Spezifikationen
Architecture, release timeline, capabilities, and modalities.
| Feature | Claude 3.5 Haiku | GPT-6 Astra |
|---|---|---|
| Official API Model ID (SDK) | claude-3-5-haiku-20241101 | gpt-6-astra |
| API Protocol | Anthropic Messages API + AWS Bedrock + Vertex AI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2024-11 | 2026-09 |
| Knowledge Cutoff | July 2024 | June 2026 |
| Architecture | Optimized Lightweight Transformer | Omni-Adaptive Autoregressive with Dynamic CoT |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 4,000 – 10,000 RPM (Tier 4 + Priority 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) | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens | Flat rate ($10/1M in) across full 272K window |
| Prompt Cache Policy & TTL | $0.08/1M cached read (90% off); 5-min default & 1-hour extended TTL | Automatic prefix caching at $1/1M (no extra cache-write fee) |
| 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 | Native Web Search Citations + Code Execution Tool + MCP Connectors | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | Custom Model Tuning via Amazon Bedrock & Prompt Distillation | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| 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) · 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 | Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated | 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, vision | text, vision, audio |
| Output Modalities | text | text, audio |
Claude 3.5 Haiku vs GPT-6 Astra: Schnelle Antworten (FAQ)
Which is more intelligent, Claude 3.5 Haiku or GPT-6 Astra?
GPT-6 Astra is more intelligent. It scores 96 compared with 36 on the composite Intelligence Index.
Which model is faster?
Claude 3.5 Haiku is faster, generating 130 tokens per second compared with 100 tokens per second.
Which model is cheaper to run?
Claude 3.5 Haiku is cheaper at $0.62 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Claude 3.5 Haiku has lower latency, with a time to first token of 0.38s 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.
Fazit
Choose Claude 3.5 Haiku for unternehmensautomatisierung, software-engineering, autonome ki-agenten und anthropic-produktionssysteme, or choose GPT-6 Astra for unternehmensautomatisierung, software-engineering, autonome ki-agenten und openai-produktionssysteme.
Häufig gestellte Fragen (FAQ)
Which is cheaper: Claude 3.5 Haiku or GPT-6 Astra?+
Claude 3.5 Haiku costs $0.8/1M input and $4/1M output tokens, while GPT-6 Astra costs $10/1M input and $50/1M output tokens.
Which model has a larger context window: Claude 3.5 Haiku or GPT-6 Astra?+
Claude 3.5 Haiku 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.
Offizielle Quellen: Anthropic & OpenAI Official Documentation