vakati-tech.ai

// head_to_head

Perceptron Mk1.5 vs MiMo-V2.6-Pro

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

Perceptron Mk1.5 is the cheaper of the two; neither can be ranked on quality here.

Perceptron Mk1.5 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.

perceptron

Perceptron Mk1.5

Blended / 1M
$0.487
Context
37K
Released
Sep 25, 2026
Overall score
Not evaluated
reasoningtool callingimage inputvideo inputaudio input

xiaomi

MiMo-V2.6-Pro

Blended / 1M
$0.544
Context
1.1M
Released
Sep 21, 2026
Overall score
68.5
reasoningtool callingimage inputvideo inputaudio inputprompt caching

Specs and pricing

MetricPerceptron Mk1.5MiMo-V2.6-Pro
LiveBench overall

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

—68.5
Cost per point

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

—$0.0018
Blended price / 1M

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

$0.487win$0.544
Input price / 1M$0.150win$0.435
Output price / 1M$1.50$0.870win
Cached input / 1M

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

—$0.0036
Context window37K1.1Mwin
Max output tokens8K131Kwin

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Perceptron Mk1.5 on top, MiMo-V2.6-Pro below, both out of 100.

Long-horizon agentic
—
35.2
Coding
—
81.5
Reasoning
—
79.6
Browser
—
77.3
Data analysis
—
72.3
Research
—
76.7
Documents & design
—
78.5

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.

WorkloadPerceptron Mk1.5MiMo-V2.6-Pro
Support chatbot

1.2K in / 400 out × 200K requests

$156.00/mo$142.94/mo
RAG assistant

8K in / 600 out × 100K requests

$210.00/mo$227.64/mo
Coding agent

40K in / 4K out × 20K requests

$240.00/mo$176.02/mo
Document extraction

20K in / 1.5K out × 50K requests

$262.50/mo$478.68/mo
Bulk classification

500 in / 20 out × 5M requests

$525.00/mo$958.80/mo
Run these two through the cost calculator

Which should you pick?

You need to fit large documents in one call

MiMo-V2.6-Pro

Wider context window — 1.1M against 37K.

You are cost-constrained

Perceptron Mk1.5

Cheaper on blended list price at $0.487 per million tokens.

Perceptron Mk1.5 vs MiMo-V2.6-Pro FAQ

Which is better, Perceptron Mk1.5 or MiMo-V2.6-Pro?

Perceptron Mk1.5 is the cheaper of the two; neither can be ranked on quality here. Perceptron Mk1.5 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 Perceptron Mk1.5 cheaper than MiMo-V2.6-Pro?

Perceptron Mk1.5 is cheaper. On a 3:1 input:output blend, Perceptron Mk1.5 lists at $0.487 per million tokens and MiMo-V2.6-Pro at $0.544 — Perceptron Mk1.5 is 12% cheaper. Input and output are priced separately — Perceptron Mk1.5 charges $0.150 in and $1.50 out, MiMo-V2.6-Pro charges $0.435 and $0.870 — so the model that looks cheaper flips depending on how output-heavy your workload is.

Does Perceptron Mk1.5 or MiMo-V2.6-Pro have a bigger context window?

MiMo-V2.6-Pro has the larger context window: 37K for Perceptron Mk1.5 against 1.1M for MiMo-V2.6-Pro. 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 Perceptron Mk1.5 and MiMo-V2.6-Pro support prompt caching?

MiMo-V2.6-Pro publishes a cached-input rate of $0.0036 per million tokens against a full input rate of $0.435. The catalogue lists no separate cached rate for Perceptron Mk1.5, 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.
  • 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.