Switchpoint: Switchpoint Router

Public pricingIntelligence 79/100Medium memory

Switchpoint Router 是一款文本模型，适合通用对话、分析与生产场景。它结合了稳定的通用表现、131K tokens上下文和均衡成本定位，可在general chat, analysis, and production workloads中提供可靠表现。它适合重视质量、速度与成本的团队，能带来稳定输出、灵活部署与扩展空间。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。

Input

$0.85/1M

Output

$3.40/1M

Cached

$0.09/1M

Batch

$0.42/1M

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Technical specifications

Switchpoint Router at a glance.

Memory

131,072

tokens

Max reply

32,768

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

—

Released

May 2025

Training cutoff

Dec 2024

Availability

Public pricing

Status

active

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick Switchpoint Router

  • High-volume workloads where unit cost matters.

When to look elsewhere

  • Your workload involves images — pick a vision-capable model instead.
  • You need tool-use / function calling for agent workflows.

Alternatives

Similar models to compare.

FAQ

Switchpoint Router — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, Switchpoint Router costs roughly $200 per month. Input is $0.85 /1M tokens and output is $3.40 /1M tokens.
Switchpoint Router has a 131,072-token context window (medium memory — a long report or a codebase file). That means you can fit about 24,576 words of input and history in a single call.
Switchpoint Router was released in May 2025, with training data cut off around December 2024.
Models in a similar class include Relace Apply 3, Llama 3.1 Euryale 70B v2.2, Aion-2.0. The "Similar models" section below this FAQ links into each.

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