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Claude Fable 5 vs DeepSeek V4 Pro

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Claude Fable 5 and DeepSeek V4 Pro.

Anthropic

Claude Fable 5

Claude Fable 5 is a Mythos-class model from Anthropic, built for autonomous knowledge work and coding. It supports text, image, and file inputs with text output, with reasoning support and...

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DeepSeek

DeepSeek V4 Pro

DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding,...

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Technical Specifications

SpecificationClaude Fable 5DeepSeek V4 Pro
ProviderAnthropicDeepSeek
Context Window1,000,000 tokens1,048,576 tokens
Agent SuitabilityN/A94/100
Time to First Token (TTFT)N/A280 ms
Deployment Modelmanaged apimanaged api
Production Stabilitybetastable
API AvailableYesYes
Released Date2026-06-092026-04-24

API Pricing Comparison

Input Price per Million Tokens

Claude Fable 5

$10.00

DeepSeek V4 Pro

$0.43

Output Price per Million Tokens

Claude Fable 5

$50.00

DeepSeek V4 Pro

$0.87

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Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
N/Avs8850.0%
Claude Fable 5
DeepSeek V4 Pro
HumanEvalPython coding & logic synthesis
N/Avs8900.0%
Claude Fable 5
DeepSeek V4 Pro
MATHComplex mathematical problem solving
N/Avs7460.0%
Claude Fable 5
DeepSeek V4 Pro
GPQAGraduate-level expert reasoning
N/Avs4900.0%
Claude Fable 5
DeepSeek V4 Pro
HellaSwagCommonsense reasoning and inference
N/Avs8750.0%
Claude Fable 5
DeepSeek V4 Pro
MT-BenchMulti-turn conversation flow quality
N/Avs918.0%
Claude Fable 5
DeepSeek V4 Pro

Claude Fable 5 Quirks & Gotchas

No developer gotchas reported.

DeepSeek V4 Pro Quirks & Gotchas

  • โ–ธMoE architecture โ€” cold-start latency on first request, use keep-alive
  • โ–ธBest cost-performance ratio of any frontier model โ€” strong tool calling for agentic use