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Van Data Team

text model comparison

Claude Fable 5 vs GPT-5.6 Sol

Claude Fable 5 and GPT-5.6 Sol are both current text models, from Anthropic and OpenAI. GPT-5.6 Sol is 60% cheaper per 1M input tokens than Claude Fable 5, $4 vs $10. On Arena Text, Claude Fable 5 scores 1504 Elo and GPT-5.6 Sol 1485 Elo (Arena, measured October 8, 2026). GPT-5.6 Sol has the larger context window, 1,050,000 vs 1,000,000 tokens.

Data verified October 13, 2026 · Dataset 2026-10-13

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Side by side

Prices in effect today, compared at the same tier wherever both list one. The better value in each row is highlighted.

FactClaude Fable 5GPT-5.6 Sol
Price per 1M input tokens$10$4 (better)
Price per 1M output tokens$50$20 (better)
Arena Text1504 Elo (#3 of 49) (better)1485 Elo (#11 of 49)
GPQA Diamond85.9% (#33 of 40)93.5% (#11 of 40) (better)
FrontierMath Tiers 1-3 (v2)87% (#8 of 40)89.1% (#6 of 40) (better)
SimpleQA Verified70.7% (#6 of 36) (better)69.7% (#7 of 36)
ProviderAnthropicOpenAI
Release dateJune 9, 2026July 9, 2026
AccessAPI onlyAPI only
Context window1,000,000 tokens1,050,000 tokens
Max output128,000 tokens128,000 tokens
Inputtext, imagetext, image
Outputtexttext

Scores:Arena · 2026-10-12Epoch AI · 2026-10-12

Open both in the interactive comparison

What each costs

Example workloads at each provider's listed rates, then every other rate either one lists. The cheaper figure in each row is highlighted.

Workload or rateClaude Fable 5GPT-5.6 Sol
10M input and 2M output tokens$200$80 (better)
The same, with 9M of the input tokens cached$119$47.60 (better)
Other listed rates
1M input tokens, cached$1$0.40 (better)

When to choose each

Claude Fable 5

Where it leads

  • Higher Arena Text score, 1504 Elo vs 1485 Elo
  • Higher SimpleQA Verified score, 70.7% vs 69.7%

Best for

  • Long-horizon coding, reasoning, and knowledge-work evaluations

Watch out for

  • Fable requires 30-day data retention, and classifier-triggered requests fall back to Claude Opus 4.8
Full Claude Fable 5 profile

GPT-5.6 Sol

Where it leads

  • Lower input and output prices, $4 and $20 vs $10 and $50 per 1M tokens
  • Higher GPQA Diamond score, 93.5% vs 85.9%
  • Higher FrontierMath Tiers 1-3 (v2) score, 89.1% vs 87%
  • Larger context window 1,050,000 vs 1,000,000 tokens
  • Cheaper cached input, $0.40 vs $1 per 1M tokens

Best for

  • Frontier capability evaluations for complex API workflows
  • Long-horizon coding and research agents that use computer use or MCP tools

Watch out for

  • Not in the pinned LiveBench snapshot; its independent scores here come from Epoch AI's own GPQA Diamond, FrontierMath and SimpleQA Verified runs
Full GPT-5.6 Sol profile

Claude Fable 5 vs GPT-5.6 Sol FAQ

Which is cheaper, Claude Fable 5 or GPT-5.6 Sol?

GPT-5.6 Sol is 60% cheaper per 1M input tokens than Claude Fable 5, $4 vs $10. For 10M input and 2M output tokens, Claude Fable 5 costs $200 and GPT-5.6 Sol $80 at standard rates.

Which is cheaper with prompt caching, Claude Fable 5 or GPT-5.6 Sol?

Claude Fable 5 charges $1 per 1M cached input tokens, 90% below its standard input rate, and GPT-5.6 Sol $0.40, 90% below. With 9M of 10M input tokens cached and 2M output tokens, Claude Fable 5 costs $119 and GPT-5.6 Sol $47.60.

Which scores higher on independent benchmarks, Claude Fable 5 or GPT-5.6 Sol?

Claude Fable 5 leads on Arena Text, 1504 Elo to 1485 Elo; GPT-5.6 Sol leads on GPQA Diamond, 93.5% to 85.9%; GPT-5.6 Sol leads on FrontierMath Tiers 1-3 (v2), 89.1% to 87%. Scores are independent evaluations, not either vendor's launch figures.

Which has the larger context window, Claude Fable 5 or GPT-5.6 Sol?

GPT-5.6 Sol has the larger context window, 1,050,000 vs 1,000,000 tokens. Both return up to 128,000 tokens per response.

Articles on Claude Fable 5 and GPT-5.6 Sol

Production evaluation

Choosing between Claude Fable 5 and GPT-5.6 Sol?

Public benchmarks narrow the shortlist. We run both on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.

  • A head-to-head evaluation on your real workload
  • Routing between models by cost and difficulty