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Mercury 2.5 vs MiniMax M3.1 Flash

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

Mercury 2.5 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.

inception

Mercury 2.5

Blended / 1M
$0.068
Context
260K
Released
Sep 8, 2026
Overall score
Not evaluated
reasoningtool callingprompt caching

minimax

MiniMax M3.1 Flash

Blended / 1M
$0.131
Context
1.0M
Released
Oct 19, 2026
Overall score
66.9
reasoningtool callingimage inputvideo inputprompt caching

Specs and pricing

MetricMercury 2.5MiniMax M3.1 Flash
LiveBench overall

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

—66.9
Cost per point

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

—$0.0015
Blended price / 1M

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

$0.068win$0.131
Input price / 1M$0.040win$0.075
Output price / 1M$0.150win$0.300
Cached input / 1M

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

$0.0040win$0.0075
Context window260K1.0Mwin
Max output tokens66K524Kwin

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Mercury 2.5 on top, MiniMax M3.1 Flash below, both out of 100.

Long-horizon agentic
—
28.8
Coding
—
83.9
Reasoning
—
82.9
Browser
—
80.6
Data analysis
—
71.4
Research
—
72.7
Documents & design
—
74.0

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.

WorkloadMercury 2.5MiniMax M3.1 Flash
Support chatbot

1.2K in / 400 out × 200K requests

$19.01/mo$37.14/mo
RAG assistant

8K in / 600 out × 100K requests

$26.60/mo$51.00/mo
Coding agent

40K in / 4K out × 20K requests

$23.84/mo$46.20/mo
Document extraction

20K in / 1.5K out × 50K requests

$49.45/mo$94.13/mo
Bulk classification

500 in / 20 out × 5M requests

$97.00/mo$183.75/mo
Run these two through the cost calculator

Which should you pick?

You need to fit large documents in one call

MiniMax M3.1 Flash

Wider context window — 1.0M against 260K.

You are cost-constrained

Mercury 2.5

Cheaper on blended list price at $0.068 per million tokens.

Mercury 2.5 vs MiniMax M3.1 Flash FAQ

Which is better, Mercury 2.5 or MiniMax M3.1 Flash?

Mercury 2.5 is the cheaper of the two; neither can be ranked on quality here. Mercury 2.5 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 Mercury 2.5 cheaper than MiniMax M3.1 Flash?

Mercury 2.5 is cheaper. On a 3:1 input:output blend, Mercury 2.5 lists at $0.068 per million tokens and MiniMax M3.1 Flash at $0.131 — Mercury 2.5 is 1.9× cheaper. Input and output are priced separately — Mercury 2.5 charges $0.040 in and $0.150 out, MiniMax M3.1 Flash charges $0.075 and $0.300 — so the model that looks cheaper flips depending on how output-heavy your workload is.

Does Mercury 2.5 or MiniMax M3.1 Flash have a bigger context window?

MiniMax M3.1 Flash has the larger context window: 260K for Mercury 2.5 against 1.0M for MiniMax M3.1 Flash. 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 Mercury 2.5 and MiniMax M3.1 Flash support prompt caching?

Both publish a cached-input rate: $0.0040 per million for Mercury 2.5 and $0.0075 for MiniMax M3.1 Flash, against full input rates of $0.040 and $0.075. 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.
  • Scores — LiveBench release 2026-10-25, 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.