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Grok 4.5 – xAI

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Grok 4.5 is a Flagship coding/agent from xAI (United States).

One-line fit: best used for High-volume coding agents, cost-efficient SWE, office plugins.

Key specifications

Provider xAI
Model Grok 4.5
Type Flagship coding/agent
Context window 500K
Pricing (indicative) $2 / $6 per 1M; cache ~$0.50
Company category Frontier Lab
Region United States
Official site https://x.ai

Benchmarks and public standing

SWE Marathon 29% (#1 in xAI table); Terminal Bench 2.1 ~83.3%; SWE-Bench Pro ~64.7%; ~4.2x fewer tokens vs Opus 4.8 on some tasks

Treat scores as directional. SWE-bench, Terminal-Bench, LMSYS Arena, Artificial Analysis, and vendor cards use different harnesses and are not always comparable 1:1. Re-check the latest official model card before decisions.

What this model is good at

High-volume coding agents, cost-efficient SWE, office plugins

This aligns with xAI’s broader strengths:

  • Intelligence per dollar
  • Coding agents (Cursor flywheel)
  • Realtime news/culture via X
  • High TPS inference

Limitations and watch-outs

SWE-Pro trails Fable; EU lag at launch

  • Rate limits, regional availability, and data retention policies vary by plan.
  • Agent harness quality (Cursor, Claude Code, Codex, custom tools) can change outcomes more than raw model Elo.
  • Open-weight availability (if any) is separate from hosted API quality and safety filters.

Ideal users

  • Product engineers shipping features that match: High-volume coding agents, cost-efficient SWE, office plugins
  • Teams standardizing on the xAI ecosystem
  • Agent builders who need a Flagship coding/agent

When to pick something else

  • Cheaper volume: compare lower tiers from the same lab or open Chinese/EU alternatives.
  • Maximum hard SWE thoughtfulness: compare Claude Fable-class and other coding flagships.
  • Giant multimodal corpora / Workspace: compare Gemini-class models.
  • Self-host / open weights: Llama, Qwen, DeepSeek, GLM, Mistral open lines.

Parent company

xAI – Grok models emphasize real-time X data, coding agents, price/efficiency, and a distinct less-lecturing personality.

Related models from xAI

Data is curated for AIForumSphere model directory mid-2026 directional figures.

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