// head_to_head

Magnum v4 72B vs Claude Fable 5.1

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

Magnum v4 72B is the cheaper of the two; neither can be ranked on quality here.

Magnum v4 72B 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.

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Magnum v4 72B

Blended / 1M
$3.13
Context
33K
Released
Oct 22, 2024
Overall score
Not evaluated

anthropic

Claude Fable 5.1

Blended / 1M
$20.00
Context
1M
Released
Sep 1, 2026
Overall score
83.4
reasoningtool callingimage inputfile inputprompt caching

Specs and pricing

MetricMagnum v4 72BClaude Fable 5.1
LiveBench overall

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

83.4
Cost per point

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

$0.6668
Blended price / 1M

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

$3.13win$20.00
Input price / 1M$2.50win$10.00
Output price / 1M$5.00win$50.00
Cached input / 1M

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

$0.250
Context window33K1Mwin
Max output tokens4K128Kwin

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Magnum v4 72B on top, Claude Fable 5.1 below, both out of 100.

Agentic coding
66.1
Coding
86.4
Reasoning
91.7
Mathematics
97.0
Data analysis
80.3
Language
89.5
Instruction following
73.0

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.

WorkloadMagnum v4 72BClaude Fable 5.1
Support chatbot

1.2K in / 400 out × 200K requests

$1,000/mo$5,698/mo
RAG assistant

8K in / 600 out × 100K requests

$2,300/mo$7,100/mo
Coding agent

40K in / 4K out × 20K requests

$2,400/mo$6,540/mo
Document extraction

20K in / 1.5K out × 50K requests

$2,875/mo$13,263/mo
Bulk classification

500 in / 20 out × 5M requests

$6,750/mo$25,125/mo
Run these two through the cost calculator

Which should you pick?

You need to fit large documents in one call

Claude Fable 5.1

Wider context window — 1M against 33K.

You are cost-constrained

Magnum v4 72B

Cheaper on blended list price at $3.13 per million tokens.

Magnum v4 72B vs Claude Fable 5.1 FAQ

Which is better, Magnum v4 72B or Claude Fable 5.1?

Magnum v4 72B is the cheaper of the two; neither can be ranked on quality here. Magnum v4 72B 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 Magnum v4 72B cheaper than Claude Fable 5.1?

Magnum v4 72B is cheaper. On a 3:1 input:output blend, Magnum v4 72B lists at $3.13 per million tokens and Claude Fable 5.1 at $20.00 — Magnum v4 72B is 6.4× cheaper. Input and output are priced separately — Magnum v4 72B charges $2.50 in and $5.00 out, Claude Fable 5.1 charges $10.00 and $50.00 — so the model that looks cheaper flips depending on how output-heavy your workload is.

Does Magnum v4 72B or Claude Fable 5.1 have a bigger context window?

Claude Fable 5.1 has the larger context window: 33K for Magnum v4 72B against 1M for Claude Fable 5.1. Note that a window you can fill is not a window you should fill — retrieval quality usually degrades well before the limit, and you pay for every token you put in it.

Do Magnum v4 72B and Claude Fable 5.1 support prompt caching?

Claude Fable 5.1 publishes a cached-input rate of $0.250 per million tokens against a full input rate of $10.00. The catalogue lists no separate cached rate for Magnum v4 72B, which means the provider does not price it separately here — not that caching is unavailable.

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.