// head_to_head

Claude Opus 5.5 vs Nex-N2.5-Mini

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

Nex-N2.5-Mini is the cheaper of the two; neither can be ranked on quality here.

Nex-N2.5-Mini 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 Opus 5.5

Blended / 1M
$8.00
Context
1M
Released
Sep 22, 2026
Overall score
83.2
reasoningtool callingimage inputfile inputprompt caching

nex-agi

Nex-N2.5-Mini

Blended / 1M
$0.044
Context
262K
Released
Sep 8, 2026
Overall score
Not evaluated
reasoningimage inputprompt caching

Specs and pricing

MetricClaude Opus 5.5Nex-N2.5-Mini
LiveBench overall

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

83.2
Cost per point

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

$0.4474
Blended price / 1M

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

$8.00$0.044win
Input price / 1M$4.00$0.025win
Output price / 1M$20.00$0.100win
Cached input / 1M

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

$0.200$0.0025win
Context window1Mwin262K
Max output tokens128K236Kwin

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Claude Opus 5.5 on top, Nex-N2.5-Mini below, both out of 100.

Agentic coding
71.7
Coding
89.3
Reasoning
92.2
Mathematics
97.1
Data analysis
80.3
Language
86.3
Instruction following
65.7

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 Opus 5.5Nex-N2.5-Mini
Support chatbot

1.2K in / 400 out × 200K requests

$2,286/mo$12.38/mo
RAG assistant

8K in / 600 out × 100K requests

$2,880/mo$17.00/mo
Coding agent

40K in / 4K out × 20K requests

$2,672/mo$15.40/mo
Document extraction

20K in / 1.5K out × 50K requests

$5,310/mo$31.37/mo
Bulk classification

500 in / 20 out × 5M requests

$10,100/mo$61.25/mo
Run these two through the cost calculator

Which should you pick?

You need to fit large documents in one call

Claude Opus 5.5

Wider context window — 1M against 262K.

You are cost-constrained

Nex-N2.5-Mini

Cheaper on blended list price at $0.044 per million tokens.

Claude Opus 5.5 vs Nex-N2.5-Mini FAQ

Which is better, Claude Opus 5.5 or Nex-N2.5-Mini?

Nex-N2.5-Mini is the cheaper of the two; neither can be ranked on quality here. Nex-N2.5-Mini 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 Opus 5.5 cheaper than Nex-N2.5-Mini?

Nex-N2.5-Mini is cheaper. On a 3:1 input:output blend, Claude Opus 5.5 lists at $8.00 per million tokens and Nex-N2.5-Mini at $0.044 — Nex-N2.5-Mini is 183× cheaper. Input and output are priced separately — Claude Opus 5.5 charges $4.00 in and $20.00 out, Nex-N2.5-Mini charges $0.025 and $0.100 — so the model that looks cheaper flips depending on how output-heavy your workload is.

Does Claude Opus 5.5 or Nex-N2.5-Mini have a bigger context window?

Claude Opus 5.5 has the larger context window: 1M for Claude Opus 5.5 against 262K for Nex-N2.5-Mini. 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 Opus 5.5 and Nex-N2.5-Mini support prompt caching?

Both publish a cached-input rate: $0.200 per million for Claude Opus 5.5 and $0.0025 for Nex-N2.5-Mini, against full input rates of $4.00 and $0.025. 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.