// head_to_head

Claude Fable 5.1 vs Mercury 2

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

Mercury 2 is the cheaper of the two; neither can be ranked on quality here.

Mercury 2 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 5.1

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

inception

Mercury 2

Blended / 1M
$0.375
Context
128K
Released
Mar 4, 2026
Overall score
Not evaluated
reasoningtool callingprompt caching

Specs and pricing

MetricClaude Fable 5.1Mercury 2
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.

$20.00$0.375win
Input price / 1M$10.00$0.250win
Output price / 1M$50.00$0.750win
Cached input / 1M

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

$0.250$0.025win
Context window1Mwin128K
Max output tokens128Kwin50K

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Claude Fable 5.1 on top, Mercury 2 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.

WorkloadClaude Fable 5.1Mercury 2
Support chatbot

1.2K in / 400 out × 200K requests

$5,698/mo$103.80/mo
RAG assistant

8K in / 600 out × 100K requests

$7,100/mo$155.00/mo
Coding agent

40K in / 4K out × 20K requests

$6,540/mo$134.00/mo
Document extraction

20K in / 1.5K out × 50K requests

$13,263/mo$295.00/mo
Bulk classification

500 in / 20 out × 5M requests

$25,125/mo$587.50/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 128K.

You are cost-constrained

Mercury 2

Cheaper on blended list price at $0.375 per million tokens.

Claude Fable 5.1 vs Mercury 2 FAQ

Which is better, Claude Fable 5.1 or Mercury 2?

Mercury 2 is the cheaper of the two; neither can be ranked on quality here. Mercury 2 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 5.1 cheaper than Mercury 2?

Mercury 2 is cheaper. On a 3:1 input:output blend, Claude Fable 5.1 lists at $20.00 per million tokens and Mercury 2 at $0.375 — Mercury 2 is 53× cheaper. Input and output are priced separately — Claude Fable 5.1 charges $10.00 in and $50.00 out, Mercury 2 charges $0.250 and $0.750 — so the model that looks cheaper flips depending on how output-heavy your workload is.

Does Claude Fable 5.1 or Mercury 2 have a bigger context window?

Claude Fable 5.1 has the larger context window: 1M for Claude Fable 5.1 against 128K for Mercury 2. 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 Claude Fable 5.1 and Mercury 2 support prompt caching?

Both publish a cached-input rate: $0.250 per million for Claude Fable 5.1 and $0.025 for Mercury 2, against full input rates of $10.00 and $0.250. 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.