Nex-N2.5-Mini

by Nex AGInex-agi/nex-n2.5-mini

  • Text
  • No route yet
  • Released

LLMCompare cannot run Nex-N2.5-Mini yet.No route to this model is configured on this site yet. Its prices and parameters are listed below for reference.

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Nex-N2.5-Mini at a glance

Context length
262,144 tokens
Maximum output
235,929 tokens
Accepts
Text, Image
Returns
Text
Features
ReasoningJSON outputPrompt cachingImage input
Reasoning effort levels
highmediumnoneReasoning can be turned off.
Released
8 Sep 2026
Knowledge cutoff
Not published

Model facts synced from the OpenRouter model list on 21 Oct 2026.

Nex-N2.5-Mini pricing by route

A route is the service LLMCompare calls to reach the model. Nex-N2.5-Mini has 1 route. Prices are in US dollars.

Prices of Nex-N2.5-Mini on each route
RouteOn LLMCompareInputper 1M tokensOutputper 1M tokensCache readper 1M tokensPrice verified onSource
OpenRouterDefaultNot configured$0.025$0.10$0.0025openrouter.ai/nex-agi/nex-n2.5-mini

The cost shown in an LLMCompare report is calculated from these prices as they were at the time of the run.

Cost calculator

Estimate what a batch of calls to Nex-N2.5-Mini costs. The starting numbers are examples. Change them to match your task.

Part of the input tokens above, billed at the cache read price.

Billed in addition to the output tokens.

Cost per call
$0.000075
1 credits
Cost of 100 calls
$0.0075
100 credits

Calculated from the OpenRouter prices verified on 21 Oct 2026. Credits are the cost plus a 20% service fee, at $0.001 per credit, rounded up for each call, with a minimum of 1 per call. A real run is charged for the usage the provider reports.

Parameters you can set

These are the parameters LLMCompare can set when it calls the model through OpenRouter.

Parameters of Nex-N2.5-Mini
ParameterTypeRange or optionsDefault
temperatureNumber0 to 2in steps of 0.1Provider default
top_pNumber0 to 1in steps of 0.05Provider default
max_tokensInteger1 to 235,929Provider default
reasoning_effortOne ofhighmediumnonehigh

About Nex-N2.5-Mini

Nex-N2.5 is an agentic model built to turn goals into working, verified outcomes. Its core strength is agentic coding within a visual feedback loop: it can explore codebases, implement multi-file...

Description as published for this model. LLMCompare has not edited it.

Models to compare with Nex-N2.5-Mini

Text models from the same provider and models at the nearest price. The order is not a ranking.

Models to compare with Nex-N2.5-Mini
Add to comparisonModelContextMax outputInput priceper 1M tokensOutput priceper 1M tokensFeaturesReleasedOn LLMCompare
Nex-N2.5-ProNex AGInex-agi/nex-n2.5-pro262k236k$0.075$0.25ReasoningJSONToolsCacheVisionNo route yet
Granite 4.0 MicroIBMibm-granite/granite-4.0-h-micro131k118k$0.017$0.112JSONNo route yet
Mistral Small 3Mistralmistralai/mistral-small-24b-instruct-250132.8k16.4k$0.05$0.08JSONNo route yet
Llama 3.1 8B InstructMetameta-llama/llama-3.1-8b-instruct131k118k$0.05$0.08JSONToolsCacheNo route yet
gpt-oss-20bOpenAIopenai/gpt-oss-20b131k32.8k$0.018$0.09ReasoningJSONToolsCacheNo route yet
Qwen3.7 FlashQwenqwen/qwen3.7-flash1M65.5k$0.03$0.13JSONToolsCacheVisionNo route yet

Questions about Nex-N2.5-Mini

How much does Nex-N2.5-Mini cost?
On the OpenRouter route, Nex-N2.5-Mini costs $0.025 per 1 million input tokens and $0.10 per 1 million output tokens, in US dollars. Input tokens that Nex-N2.5-Mini reads from the prompt cache cost $0.0025 per 1 million tokens. LLMCompare verified this price on 21 Oct 2026.
What is the context length of Nex-N2.5-Mini?
Nex-N2.5-Mini has a context length of 262,144 tokens and returns up to 235,929 output tokens in one call.
What inputs does Nex-N2.5-Mini accept?
Nex-N2.5-Mini accepts these inputs: Text, Image. Nex-N2.5-Mini returns: Text.
Which reasoning effort levels does Nex-N2.5-Mini support?
Nex-N2.5-Mini supports these reasoning effort levels: high, medium, none. Reasoning can be turned off for Nex-N2.5-Mini.
Can I test Nex-N2.5-Mini on my own data?
Not yet. LLMCompare lists the prices and parameters of Nex-N2.5-Mini, but no route to Nex-N2.5-Mini is configured on LLMCompare, so it cannot be selected for an evaluation.