Claude Fable 5.1 vs GPT-6 Astra
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Claude Fable 5.1 by Anthropic and GPT-6 Astra by OpenAI represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, both models offer identical input token rates. On output generation, costs are matched. In data-heavy architectures requiring extensive repository or document analysis, Claude Fable 5.1 provides an expanded memory horizon with 1,000K tokens. In latency-sensitive production environments, GPT-6 Astra leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
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Claude Fable 5.1
Modello di Ragionamento ProfondoClaude Fable 5.1 di Anthropic è un modello di intelligenza artificiale con finestra di contesto da 1M token e tariffazione API di $10/1M token in input e $50/1M in output, ideale per coding, ragionamento e automazione aziendale.
$10.00 / 1M
$50.00 / 1M
1M tokens
83.8%
GPT-6 Astra
Modello di Ragionamento ProfondoGPT-6 Astra di OpenAI è un modello di intelligenza artificiale con finestra di contesto da 1M token e tariffazione API di $10.0/1M token in input e $50.0/1M in output, ideale per coding, ragionamento e automazione aziendale.
$10.00 / 1M
$50.00 / 1M
272K tokens
82.4%
Differenze Chiave a Colpo d’Occhio
- Claude Fable 5.1 is 1.0x cheaper for API usage (input + output tokens combined).
- Claude Fable 5.1 has a larger context window (1M vs 272K tokens).
- GPT-6 Astra is faster at 100 tok/s vs 65 tok/s.
- Claude Fable 5.1 leads on SWE-bench coding (83.8% vs 82.4%).
| Feature | Claude Fable 5.1 | GPT-6 Astra |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 82 | 96 |
Provider | Anthropic | OpenAI |
Input Price Cost per million input tokens | $10.00 / 1M | $10.00 / 1M |
Output Price Cost per million output tokens | $50.00 / 1M | $50.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $7.17 / 1M | $7.70 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 A4 pages of text | 272K tokens~408 A4 pages of text |
Max Output Tokens Per single request | 128K | 128K |
Throughput Speed Tokens generated per second | 65 tok/s | 100 tok/s |
SWE-bench Verified Real-world software engineering | 83.8% | 82.4% |
GPQA Diamond Graduate-level reasoning | 81.6% | 80.9% |
Cached Input Price Prompt caching discount per 1M tokens | $0.25 / 1M | $1.00 / 1M |
Chi vince in ogni categoria?
At-a-glance decision frameworkPunteggi Benchmark Verificati
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.
Latenza e Tempo di Risposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulatore Interattivo dei Costi Token
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Claude Fable 5.1 · Strengths & Key Advantages
- Architettura Frontier Auditable Multimodal Transformer avanzata di Anthropic con supporto fino a 1M token di contesto
- Ottimo rapporto qualità-prezzo ($10/1M input, $50/1M output) e bassa latenza
- Elevate prestazioni nei benchmark di programmazione, logica e comprensione multilingue
Considerations & Trade-offs
- L'utilizzo intensivo di contesti molto ampi richiede un attento monitoraggio dei costi dei token
- Per casi d'uso verticali complessi è consigliabile un prompt engineering mirato
GPT-6 Astra · Strengths & Key Advantages
- Architettura Omni-Adaptive Autoregressive with Dynamic CoT avanzata di OpenAI con supporto fino a 1M token di contesto
- Ottimo rapporto qualità-prezzo ($10.0/1M input, $50.0/1M output) e bassa latenza
- Elevate prestazioni nei benchmark di programmazione, logica e comprensione multilingue
Considerations & Trade-offs
- L'utilizzo intensivo di contesti molto ampi richiede un attento monitoraggio dei costi dei token
- Per casi d'uso verticali complessi è consigliabile un prompt engineering mirato
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Claude Fable 5.1 | GPT-6 Astra |
|---|---|---|
Cost per Task Estimated USD to finish one task | $10.97 | $2.15 |
Output Tokens / Task Tokens generated per task | 72K | 58K |
Reasoning Tokens / Task Thinking tokens burned per task | 37K | 32K |
Specifiche Tecniche
Architecture, release timeline, capabilities, and modalities.
| Feature | Claude Fable 5.1 | GPT-6 Astra |
|---|---|---|
| Official API Model ID (SDK) | claude-fable-5-1-20260901 | gpt-6-astra |
| API Protocol | Anthropic Messages API + AWS Bedrock + Vertex AI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2026-09 | 2026-09 |
| Knowledge Cutoff | June 2026 | June 2026 |
| Architecture | Frontier Auditable Multimodal Transformer | Omni-Adaptive Autoregressive with Dynamic CoT |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 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 | $0.25/1M 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 Fable 5.1 vs GPT-6 Astra: Risposte Rapide (FAQ)
Which is more intelligent, Claude Fable 5.1 or GPT-6 Astra?
GPT-6 Astra is more intelligent. It scores 96 compared with 82 on the composite Intelligence Index.
Which model is faster?
GPT-6 Astra is faster, generating 100 tokens per second compared with 65 tokens per second.
Which model is cheaper to run?
Claude Fable 5.1 is cheaper at $7.17 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).
Which model has lower latency?
GPT-6 Astra has lower latency, with a time to first token of 0.95s compared with 1.45s.
Which model has a larger context window?
Claude Fable 5.1 has a larger context window, supporting 1M tokens compared with 272K tokens.
Verdetto
Verdict & Model Selection Recommendation: Choose Claude Fable 5.1 if your priority is High-stakes security auditing, automated vulnerability discovery, and mission-critical enterprise agents. Its performance in demanding tasks justifies its operational token cost. Choose GPT-6 Astra if your workflow prioritizes Autonomous browser/computer workflows, real-time voice agents, and high-difficulty mathematical reasoning. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Domande Frequenti (FAQ)
How does Claude Fable 5.1 compare to GPT-6 Astra in API token pricing and cost per token?+
Both Claude Fable 5.1 and GPT-6 Astra share matched API token pricing at $10.00 per 1M input tokens and $50.00 per 1M output tokens. Because their token economics are identical, your selection should be guided by benchmark latency, memory horizon, and reasoning capabilities rather than operational token fees. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: Claude Fable 5.1 or GPT-6 Astra?+
Claude Fable 5.1 supports a context window of 1,000K tokens (~750k words), while GPT-6 Astra supports 272K tokens (~204k words). Therefore, Claude Fable 5.1 can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Claude Fable 5.1 or GPT-6 Astra?+
Claude Fable 5.1 scores 83.8% on SWE-bench Verified while GPT-6 Astra scores 82.4%. For autonomous software engineering and multi-file debugging, Claude Fable 5.1 holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Claude Fable 5.1 and GPT-6 Astra?+
Claude Fable 5.1 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, GPT-6 Astra provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Claude Fable 5.1 and GPT-6 Astra?+
Claude Fable 5.1 generates approximately 65 tokens per second, while GPT-6 Astra delivers 100 tokens per second. In latency-sensitive production environments, GPT-6 Astra provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Claude Fable 5.1 and GPT-6 Astra to optimize costs?+
Yes! Tiered multi-model routing can optimize for latency and accuracy: you can route high-frequency conversational turns and latency-sensitive queries to GPT-6 Astra, and route deep architectural or complex reasoning queries to Claude Fable 5.1. This balanced routing strategy maximizes system throughput and answer quality.
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.
Fonti ufficiali: GetInfoUs Independent AI Benchmarks & Official API Specs