AI Models · Paid vs Paid

Claude Fable 5.1 (batch) Paid vs PEPerceptron Mk1.5 Paid

Claude Fable 5.1 (batch) vs Perceptron Mk1.5 compared — price per token, context window, multimodality, openness and which to choose. Full 2026 breakdown.

Prices & specs refreshed from live data · olud.ai

Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.

Claude Fable 5.1 (batch)PaidAnthropic
$5 /M input
$25 /M outputManaged API (no infra to run)
TypeProprietary
Context window1M tokens
MultimodalYes
Self-hostNo
PEPerceptron Mk1.5PaidPerceptron
$0.15 /M input
$1.5 /M outputManaged API (no infra to run)
TypeProprietary
Context window37K tokens
MultimodalYes
Self-hostNo
Choose Perceptron Mk1.5 for the lower output price ($1.5/M vs $25/M). Choose Claude Fable 5.1 (batch) if you need the larger 1M context window.

Claude Fable 5.1 (batch) vs Perceptron Mk1.5 specs

SpecClaude Fable 5.1 (batch)Perceptron Mk1.5Winner
MakerAnthropicPerceptron–
TypeProprietaryProprietary–
Context window1M tokens37K tokensClaude Fable 5.1 (batch)
Input price$5/M$0.15/MPEPerceptron Mk1.5
Output price$25/M$1.5/MPEPerceptron Mk1.5
Vision / multimodalYesYes= Tie
Tool / function callingYesYes= Tie
Self-hostableNo (API only)No (API only)–
LicenseProprietaryProprietary–

Price gap & when to choose each

17×cheaper per output token

Perceptron Mk1.5 is ~17× cheaper than Claude Fable 5.1 (batch) on output tokens ($1.5 vs $25 per M tokens).

Choose Claude Fable 5.1 (batch) if…
  • You want frontier performance through a managed API
  • You need the longer 1M context window
  • You value reliability & ecosystem
  • You don't want to manage infrastructure
PEChoose Perceptron Mk1.5 if…
  • You want frontier performance through a managed API
  • You want the lower output price
  • You value reliability & ecosystem
  • You don't want to manage infrastructure

Feature comparison

CapabilityClaude Fable 5.1 (batch)Perceptron Mk1.5
Open weights (downloadable)✗✗
Self-hostable✗✗
Runs fully offline✗✗
Vision / multimodal✓✓
Tool / function calling✓✓
1M+ context window✓✗

Benchmarks: Claude Fable 5.1 (batch) vs Perceptron Mk1.5

Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).

Claude Fable 5.1 (batch)
Perceptron Mk1.5
Intelligence index
53.4
–
Coding index
81.6
–
GPQA
93.7%
–
Humanity's Last Exam
59.1%
–
Long Context Reasoning
85.3%
–
SciCode
63.1%
–
τ-Bench Banking
47.2%
–
Terminal-Bench
91.4%
–
Speed
71.4 tok/s
–
Latency
138.2s
–
Intelligence per $
2.7
–

Benchmark data by Artificial Analysis.

How Claude Fable 5.1 (batch) and Perceptron Mk1.5 score

🤝 Neck and neck on these criteria (3.1 vs 2.9 / 5).
CriterionClaude Fable 5.1 (batch)Perceptron Mk1.5
Cost-efficiency3.04.5
Context window5.02.5
Openness1.51.5
Self-hosting1.01.0
Multimodality5.05.0

Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.

What each model is

Claude Fable 5.1 (batch) Paid

Anthropic · Proprietary

Claude Fable 5.1 improves on Claude Fable 5 across the board, with the biggest gains in agentic coding, long-running agentic workflows, and knowledge work: long code refactors, front-end and visual...

Perceptron Mk1.5 Paid

Perceptron · Proprietary

Perceptron Mk1.5 is Perceptron's embodied reasoning model for physical agents. It accepts text, image, video, and audio input, and answers with text plus optional structured annotations: points, boxes, polygons, tracks,...

Frequently asked questions

Claude Fable 5.1 (batch) vs Perceptron Mk1.5 — which is cheaper?

Perceptron Mk1.5 is cheaper on output ($1.5/M vs $25/M).

Which has the larger context window?

Claude Fable 5.1 (batch) offers the larger context window (1M tokens).

Claude Fable 5.1 (batch) vs Perceptron Mk1.5 — which should I pick in 2026?

Choose Perceptron Mk1.5 for the lower output price ($1.5/M vs $25/M). Choose Claude Fable 5.1 (batch) if you need the larger 1M context window.

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