// head_to_head

Claude Fable 5 vs Inkling Small

Published LiveBench scores across all seven categories, live list pricing, context windows, and the measured cost of a point of capability — for both models, side by side.

OpenRouter + LiveBenchAll comparisonsFull leaderboard

Inkling Small is the cheaper of the two; neither can be ranked on quality here.

Inkling Small does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.

anthropic

Claude Fable 5

Blended / 1M
$20.00
Context
1M
Released
Jun 9, 2026
Overall score
83.0
reasoningtool callingimage inputfile inputprompt caching

thinkingmachines

Inkling Small

Blended / 1M
$0.637
Context
1.0M
Released
Jul 30, 2026
Overall score
Not evaluated
reasoningtool callingimage inputaudio inputprompt caching

Specs and pricing

MetricClaude Fable 5Inkling Small
LiveBench overall

Mean of the seven LiveBench category scores, 0–100. Higher is better.

83.0
Cost per point

Measured benchmark spend divided by overall score — dollars per point of capability.

$0.7925
Blended price / 1M

3:1 input:output mix, the usual shape of production traffic.

$20.00$0.637win
Input price / 1M$10.00$0.450win
Output price / 1M$50.00$1.20win
Cached input / 1M

Price of an input token served from the prompt cache, where the provider publishes one.

$1.00$0.100win
Context window1M1.0M
Max output tokens128K262Kwin

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Claude Fable 5 on top, Inkling Small below, both out of 100.

Agentic coding
62.2
Coding
86.0
Reasoning
89.7
Mathematics
96.0
Data analysis
80.5
Language
90.7
Instruction following
75.8

What each one costs to run

Per-token prices are hard to feel. These are monthly list costs for both models across five workload shapes, using each provider's published cached-input rate where there is one.

WorkloadClaude Fable 5Inkling Small
Support chatbot

1.2K in / 400 out × 200K requests

$5,752/mo$178.80/mo
RAG assistant

8K in / 600 out × 100K requests

$7,400/mo$292.00/mo
Coding agent

40K in / 4K out × 20K requests

$6,960/mo$260.00/mo
Document extraction

20K in / 1.5K out × 50K requests

$13,300/mo$522.50/mo
Bulk classification

500 in / 20 out × 5M requests

$25,500/mo$1,070/mo
Run these two through the cost calculator

Which should you pick?

You are cost-constrained

Inkling Small

Cheaper on blended list price at $0.637 per million tokens.

Claude Fable 5 vs Inkling Small FAQ

Which is better, Claude Fable 5 or Inkling Small?

Inkling Small is the cheaper of the two; neither can be ranked on quality here. Inkling Small does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.

Is Claude Fable 5 cheaper than Inkling Small?

Inkling Small is cheaper. On a 3:1 input:output blend, Claude Fable 5 lists at $20.00 per million tokens and Inkling Small at $0.637 — Inkling Small is 31× cheaper. Input and output are priced separately — Claude Fable 5 charges $10.00 in and $50.00 out, Inkling Small charges $0.450 and $1.20 — so the model that looks cheaper flips depending on how output-heavy your workload is.

Does Claude Fable 5 or Inkling Small have a bigger context window?

They are effectively the same — 1M for Claude Fable 5 and 1.0M for Inkling Small.

Do Claude Fable 5 and Inkling Small support prompt caching?

Both publish a cached-input rate: $1.00 per million for Claude Fable 5 and $0.100 for Inkling Small, against full input rates of $10.00 and $0.450. On a workload with a long stable prefix — a system prompt, a tool schema, a retrieved corpus — that changes the economics more than the headline price does.

Related comparisons

How these numbers are produced

  • Price — provider list price from OpenRouter, refreshed every 15 minutes. “Blended” is a 3:1 input:output mix.
  • ScoresLiveBench release 2026-06-25, using their own category map. Each model shows its strongest published run. A blank means “not evaluated”, never “bad”.
  • Cost per point — the measured dollars LiveBench spent on the run, divided by the score it earned.
  • “Win” — awarded only past a threshold: one full point on a benchmark score, 10% on a price, 25% on a context window. Anything tighter reports as a tie, because effort settings alone move a LiveBench score by more than that.

Published benchmarks rank models on someone else's tasks. Before committing, see LLM & agent evaluation for building an eval on your own.