Claude Fable 5.1 vs Gemini 3 Pro
Benchmarks, API Token Pricing, Context Window & Speed Comparison
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Claude Fable 5.1 by Anthropic and Gemini 3 Pro by Google 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, Gemini 3 Pro holds a notable pricing advantage for token ingestion. On output generation, Gemini 3 Pro is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Gemini 3 Pro provides an expanded memory horizon with 2,000K tokens. In latency-sensitive production environments, Gemini 3 Pro 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.
Changez et Comparez les Modèles
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Claude Fable 5.1
Frontière auditabled'Anthropic le plus élevé-intelligence commercial modèle de fondation de late 2026, offrant 75% cheaper prompt cache reads, d'entreprise données controls, et auditable raisonnement.
$10.00 / 1M
$50.00 / 1M
1M tokens
83.8%
Gemini 3 Pro
Roi du contextede Google contexte king avec un industry-leading 2M-token window et le #1 LMSYS Arena ranking, spécialement conçu pour long-document et multimodal raisonnement.
$2.00 / 1M
$12.00 / 1M
2M tokens
76.2%
Différences Clés en un Coup d’Œil
- Gemini 3 Pro is 4.3x cheaper for API usage (input + output tokens combined).
- Gemini 3 Pro has a larger context window (2M vs 1M tokens).
- Gemini 3 Pro is faster at 118 tok/s vs 65 tok/s.
- Claude Fable 5.1 leads on SWE-bench coding (83.8% vs 76.2%).
| Caractéristique | Claude Fable 5.1 | Gemini 3 Pro |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 82 | 62 |
Provider | Anthropic | |
Input Price Cost per million input tokens | $10.00 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $50.00 / 1M | $12.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $7.17 / 1M | $1.74 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 A4 pages of text | 2M tokens~3,000 A4 pages of text |
Max Output Tokens Per single request | 128K | 66K |
Throughput Speed Tokens generated per second | 65 tok/s | 118 tok/s |
SWE-bench Verified Real-world software engineering | 83.8% | 76.2% |
GPQA Diamond Graduate-level reasoning | 81.6% | 73.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.25 / 1M | $0.20 / 1M |
Qui gagne où ?
At-a-glance decision frameworkScores de Benchmarks Vérifiés
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.
Latence et Temps de Réponse
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulateur Interactif de Coût de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Claude Fable 5.1 · Strengths & Key Advantages
- haut de gamme-ranked intelligence index avec 75% reduced prompt caching coût ($0.25/M tokens)
- 60% reduction dans cybersecurity vulnerability false-positives
- d'entreprise de pointe Safeguards fournissant client-controlled auditing keys
Considerations & Trade-offs
- Premium $10/$50 token economics unsuitable pour generic grand public tâches
- outil choice paramètre "any" est pas supported dans current API specification
- Conservative sécurité filters may trigger verbose refusal explanations sur dual-use recherche
Gemini 3 Pro · Strengths & Key Advantages
- Industry-leading 2M-token fenêtre de contexte (10x la plupart rivals)
- #1 LMSYS Chatbot Arena ranking à launch
- natif multimodal entrée à travers texte, image, audio, et vidéo
- 90% cached-contexte discount pour repeated long inputs
Considerations & Trade-offs
- supérieur rates apply au-dessus le 200K standard palier
- sortie prix ($12/1M) au-dessus GPT-5.1 pour short tâches
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Claude Fable 5.1 | Gemini 3 Pro |
|---|---|---|
Cost per Task Estimated USD to finish one task | $10.97 | $2.40 |
Output Tokens / Task Tokens generated per task | 72K | 60K |
Reasoning Tokens / Task Thinking tokens burned per task | 37K | 31K |
Spécifications Techniques
Architecture, release timeline, capabilities, and modalities.
| Caractéristique | Claude Fable 5.1 | Gemini 3 Pro |
|---|---|---|
| Official API Model ID (SDK) | claude-fable-5-1-20260901 | models/gemini-3-pro |
| API Protocol | Anthropic Messages API + AWS Bedrock + Vertex AI | Google Gemini API (generateContent) + OpenAI-Compatible SDK |
| Release Date | 2026-09 | 2025-11 |
| Knowledge Cutoff | June 2026 | January 2025 |
| Architecture | Frontier Auditable Multimodal Transformer | Sparse Multimodal MoE |
| 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) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | $0.25/1M cached read (90% off); 5-min default & 1-hour extended TTL | Implicit + Explicit Context Caching at $0.2/1M with configurable 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 | Native Web Search Citations + Code Execution Tool + MCP Connectors | Built-in Google Search Grounding + Managed Python Code Execution Sandbox |
| Official Fine-Tuning Support | Custom Model Tuning via Amazon Bedrock & Prompt Distillation | Vertex AI Supervised Adapter Tuning & Context 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) · Audio (~25–32 tokens/sec) · Video (~258–300 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 | Google DeepMind Frontier Safety Framework Verified |
| 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, video |
| Output Modalities | text | text |
Claude Fable 5.1 vs Gemini 3 Pro: Réponses Rapides (FAQ)
Which is more intelligent, Claude Fable 5.1 or Gemini 3 Pro?
Claude Fable 5.1 is more intelligent. It scores 82 compared with 62 on the composite Intelligence Index.
Which model is faster?
Gemini 3 Pro is faster, generating 118 tokens per second compared with 65 tokens per second.
Which model is cheaper to run?
Gemini 3 Pro is cheaper at $1.74 per 1M tokens blended, compared with $7.17 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Claude Fable 5.1 has lower latency, with a time to first token of 1.45s compared with 1.80s.
Which model has a larger context window?
Gemini 3 Pro has a larger context window, supporting 2M tokens compared with 1M tokens.
Verdict
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 Gemini 3 Pro if your workflow prioritizes Long-document analysis, full-codebase reasoning, and multimodal tasks needing 500K+ tokens. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Questions fréquentes
How does Claude Fable 5.1 compare to Gemini 3 Pro in API token pricing and cost per token?+
Claude Fable 5.1 costs $10.00 per 1M input tokens and $50.00 per 1M output tokens, whereas Gemini 3 Pro costs $2.00 input and $12.00 output. Overall, Gemini 3 Pro is the more cost-effective model for high-volume API pipelines. 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 Gemini 3 Pro?+
Claude Fable 5.1 supports a context window of 1,000K tokens (~750k words), while Gemini 3 Pro supports 2,000K tokens (~1,500k words). Therefore, Gemini 3 Pro 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 Gemini 3 Pro?+
Claude Fable 5.1 scores 83.8% on SWE-bench Verified while Gemini 3 Pro scores 76.2%. 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 Gemini 3 Pro?+
Claude Fable 5.1 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Gemini 3 Pro 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 Gemini 3 Pro?+
Claude Fable 5.1 generates approximately 65 tokens per second, while Gemini 3 Pro delivers 118 tokens per second. In latency-sensitive production environments, Gemini 3 Pro 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 Gemini 3 Pro to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Gemini 3 Pro to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Claude Fable 5.1. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.
Sources: GetInfoUs Independent AI Benchmarks & Official API Specs