Head-to-Head Model Comparison

Claude Fable 5.1 vs GPT-6.1 Sol

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Reviewed by the GetInfoUs research teamLast reviewed: October 2026Editorial policy
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Compare Claude Fable 5.1 by Anthropic against GPT-6.1 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.

Head-to-Head Comparison

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Anthropic

Claude Fable 5.1

Auditable Frontier

Anthropic's highest-intelligence commercial foundation model of late 2026, offering 75% cheaper prompt cache reads, enterprise data controls, and auditable reasoning.

Intelligence Index82 / 100
Input Token:

$10.00 / 1M

Output Token:

$50.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

83.8%

OpenAI

GPT-6.1 Sol

Near-Astra Value

Delivers results close to GPT-6 Astra at roughly one fifth of the price — the latest 2026 release.

Intelligence Index94 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.3%

Key Differences at a Glance

  • GPT-6.1 Sol is 5.0x cheaper for API usage (input + output tokens combined).
  • GPT-6.1 Sol is faster at 120 tok/s vs 65 tok/s.
  • Claude Fable 5.1 leads on SWE-bench coding (83.8% vs 82.3%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureClaude Fable 5.1GPT-6.1 Sol
Intelligence Index
Composite reasoning & knowledge score (0-100)
8294
Provider
AnthropicOpenAI
Input Price
Cost per million input tokens
$10.00 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$50.00 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$7.17 / 1M$1.47 / 1M
Context Window
Maximum input + output tokens
1M tokens~1,500 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
128K128K
Throughput Speed
Tokens generated per second
65 tok/s120 tok/s
SWE-bench Verified
Real-world software engineering
83.8%82.3%
GPQA Diamond
Graduate-level reasoning
81.6%80.8%
Cached Input Price
Prompt caching discount per 1M tokens
$0.25 / 1M$0.10 / 1M

Who Wins Where?

At-a-glance decision framework
Coding
Claude Fable 5.1
+1.5% SWE-bench lead
Cost
GPT-6.1 Sol
5.0x cheaper monthly runtime
Speed
GPT-6.1 Sol
+85% faster generation
Context
Tied
1M tokens window

Empirical Head-to-Head Benchmark Scores

Official evaluation metrics verified by independent third-party research labs.

Claude Fable 5.1GPT-6.1 Sol
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

83.8%vs82.3%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

81.6%vs80.8%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

91%vs89.9%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1510ptsvs1519pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs18.1%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

62%vs63.6%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs54.8%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs79.7%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

N/Avs93.5%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

N/Avs91%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

65 tok/s vs120 tok/s

Latency & Response Time

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
Claude Fable 5.11.45s
GPT-6.1 Sol1.12s
Est. End-to-End Response (500 tokens)TTFT + generation time
Claude Fable 5.19.14s
GPT-6.1 Sol5.29s

Real-Time Interactive Token Cost Simulator

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Claude Fable 5.1 Monthly API Bill
$60.38 / month
$10/1M in · $50/1M out
GPT-6.1 Sol Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
GPT-6.1 Sol saves approximately $48.23 / month (80%) under this workload.5.0x Savings

Claude Fable 5.1 · Strengths & Key Advantages

  • Top-ranked intelligence index with 75% reduced prompt caching cost ($0.25/M tokens)
  • 60% reduction in cybersecurity vulnerability false-positives
  • Enterprise Frontier Safeguards providing customer-controlled auditing keys
Considerations & Trade-offs
  • Premium $10/$50 token economics unsuitable for generic consumer tasks
  • Tool choice parameter "any" is not supported in current API specification
  • Conservative safety filters may trigger verbose refusal explanations on dual-use research

GPT-6.1 Sol · Strengths & Key Advantages

  • Near-Astra results at roughly a fifth of the cost
  • Excellent coding and long-horizon agent performance
  • Strong reliability with far lower latency than Astra
  • Near-flagship results at roughly a fifth of the price
Considerations & Trade-offs
  • Still marginally behind Astra on the very hardest reasoning
  • Same price as GPT-6 Sol, so the upgrade decision is easy

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricClaude Fable 5.1GPT-6.1 Sol
Cost per Task
Estimated USD to finish one task
$10.97$2.05
Output Tokens / Task
Tokens generated per task
72K62K
Reasoning Tokens / Task
Thinking tokens burned per task
37K36K

Technical Specifications

Architecture, release timeline, capabilities, and modalities.

FeatureClaude Fable 5.1GPT-6.1 Sol
Official API Model ID (SDK)claude-fable-5-1-20260901gpt-6-1-sol
API ProtocolAnthropic Messages API + AWS Bedrock + Vertex AIOpenAI Responses API & Chat Completions v1
Release Date2026-092026-09
Knowledge CutoffJune 2026April 2026
ArchitectureFrontier Auditable Multimodal TransformerNear-Astra unified reasoning model
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM10,000 – 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 tokensFlat rate ($2/1M in) across full 1000K window
Prompt Cache Policy & TTL$0.25/1M cached read (90% off); 5-min default & 1-hour extended TTLAutomatic prefix caching at $0.1/1M (no extra cache-write fee)
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxNative Web Search Citations + Code Execution Tool + MCP ConnectorsNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportCustom Model Tuning via Amazon Bedrock & Prompt DistillationSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText 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 VRAMCloud-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 ClassificationAnthropic RSP ASL-2 / ASL-3 Constitutional Safety EvaluatedOpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision
Output Modalitiestexttext

Claude Fable 5.1 vs GPT-6.1 Sol: Quick Answers

Which is more intelligent, Claude Fable 5.1 or GPT-6.1 Sol?

GPT-6.1 Sol is more intelligent. It scores 94 compared with 82 on the composite Intelligence Index.

Which model is faster?

GPT-6.1 Sol is faster, generating 120 tokens per second compared with 65 tokens per second.

Which model is cheaper to run?

GPT-6.1 Sol is cheaper at $1.47 per 1M tokens blended, compared with $7.17 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-6.1 Sol has lower latency, with a time to first token of 1.12s compared with 1.45s.

Verdict

Choose Claude Fable 5.1 for high-stakes security auditing, automated vulnerability discovery, and mission-critical enterprise agents, or choose GPT-6.1 Sol for the best value frontier model for professional and agentic work.

Frequently asked questions

Which is cheaper: Claude Fable 5.1 or GPT-6.1 Sol?+

Claude Fable 5.1 costs $10/1M input and $50/1M output tokens, while GPT-6.1 Sol costs $2/1M input and $10/1M output tokens.

Which model has a larger context window: Claude Fable 5.1 or GPT-6.1 Sol?+

Claude Fable 5.1 supports 1M tokens whereas GPT-6.1 Sol supports 1M tokens.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

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: Anthropic & OpenAI Official Documentation