Grok 4.5 Guide: xAI's Coding Model, Specs and Pricing
xAI trained a model on real developer sessions. It shows.
Grok 4.5 arrived on July 8, 2026, and it is the first xAI release aimed squarely at one audience: developers running long coding and agent sessions. Where Grok 4.20's multi-agent beta was an architectural experiment, this release is a focused product — trained on real Cursor developer session data, benchmarked on whether it can survive a real codebase over a long session, and priced to undercut every frontier rival. Elon Musk called it "an Opus-class model, but faster, more token-efficient and lower cost," later clarifying it lands "roughly comparable to Opus 4.7, but much faster." Marketing aside, the published numbers back a surprising amount of that up.
- Released July 8, 2026 — xAI's first model built specifically for coding and agentic work.
- 500K-token context window and a per-call reasoning effort dial.
- Priced at $2 / $6 per million tokens — over 60% cheaper than Opus 4.8 or GPT-5.5.
- Scores 54 on the Artificial Analysis Intelligence Index: #4 overall, a 16-point jump over Grok 4.3.
- Startlingly token-efficient: ~14,000 output tokens per Index task vs ~67,000 for Opus 4.8.
What are Grok 4.5's actual specs?
The headline numbers, in one place:
| Spec | Grok 4.5 | Why it matters |
|---|---|---|
| Context window | 500K tokens | A large monorepo slice plus docs and logs in one session |
| Pricing | $2 / $6 per 1M tokens | Frontier-adjacent quality at budget-tier cost |
| Reasoning | Effort dial, set per call | Cheap quick answers and deep runs from the same model |
| Foundation | 1.5T-parameter V9 base | New foundation, not a fine-tune of Grok 4 |
| Intelligence Index | 54 (#4 overall) | Behind Fable 5 (60), Opus 4.8 (56), GPT-5.5 (55) |
| API compatibility | Responses + Chat Completions | Drops into OpenAI-compatible codebases unmodified |
The training story is the differentiator. xAI trained on real Cursor developer session data — actual multi-file editing sessions with all their mess — rather than only sanitized coding benchmarks. The result is a model tuned for the loop developers actually live in: read the codebase, make a change, hit an error, recover, continue.
Is Grok 4.5 really "Opus-class"?
Depends which claim you grade. On the Artificial Analysis Intelligence Index it scores 54, a genuine 16-point leap over Grok 4.3 and good for fourth place — behind Claude Fable 5 at 60, Opus 4.8 at 56, and GPT-5.5 at 55. So no, it does not beat Anthropic's flagships outright, and Musk's own clarification (comparable to Opus 4.7) is the honest read.
But the efficiency numbers change the conversation. Grok 4.5 spends roughly 14,000 output tokens per Index task versus about 67,000 for Opus 4.8 — nearly five times fewer tokens to reach its answers. Combine that with the $2/$6 pricing and the per-task cost gap becomes enormous: xAI estimates roughly half the per-task cost of GPT-5.5 in Codex-style workloads, and the gap versus Opus is wider still. For high-volume agentic work, "slightly less smart, five times cheaper per task" is not a consolation prize — for many teams it is the correct engineering decision.
What should you use the Grok 4.5 coding model for?
Where it shines
- Long coding sessions: the 500K context plus session-data training means it stays coherent deep into a refactor instead of forgetting what it renamed an hour ago.
- Agentic pipelines: token efficiency compounds — an agent that takes hundreds of steps saves real money when each step emits 5x fewer tokens.
- Budget-conscious teams: if you have been rationing a frontier model, this is frontier-adjacent quality you can afford to stop rationing.
- Fast iteration: "much faster" holds up in practice; the effort dial keeps quick questions quick.
Where to stay skeptical
- Peak-difficulty reasoning: Fable 5 and Opus 4.8 still win the hardest problems. If a single wrong answer is expensive, pay for the top of the leaderboard.
- Writing tone: this generation was tuned for code; for prose and marketing work, Claude remains the stylist. Our writing-model comparison covers that lane.
- Vendor benchmarks: the Cursor-derived benchmark suite is designed by xAI. Directionally credible, but test on your own repo before migrating a pipeline.
The practical move: run your gnarliest real prompt through Grok 4.5, Claude Sonnet 5, and GPT-5.6 Terra side by side in CoreAI's Compare view. Ninety seconds of evidence beats any leaderboard argument — including ours.
How does Grok 4.5 stack up against this month's rivals?
July 2026 turned into a three-way launch war: Claude Sonnet 5 on June 30, this release on July 8, GPT-5.6 on July 9. Sonnet 5 counters with a 1M-token context window and near-Opus general intelligence at $2/$10; GPT-5.6 counters with a cleaner tier system and coding gains of its own. Grok's pitch is the sharpest on cost-per-task for agentic coding, and TechCrunch's launch coverage notes the OpenAI-compatible API makes switching costs nearly zero — you can trial it in an afternoon.
All three are live on CoreAI's model library under one subscription, which is the cheapest way to let the models compete for your workload instead of committing blind.
How should you set the reasoning effort dial?
The per-call effort dial is easy to overlook and easy to overuse. A sensible starting policy: keep effort low for lookups, boilerplate, and single-file edits — the speed is the feature. Step up to medium when the task spans files or needs a plan before code. Reserve high effort for debugging sessions where the first two attempts failed, because that is exactly where extra deliberation pays for itself and where the token-efficiency advantage keeps the bill sane anyway. The dial also changes the comparison math against fixed-reasoning rivals: a well-routed Grok session spends frontier-level thinking only on the ten percent of calls that need it, which is a large part of how the per-task costs land so low in practice.
Frequently Asked Questions
What is Grok 4.5 best at?
Coding and agentic workflows. It was trained on real Cursor developer session data, holds a 500K-token context, and is exceptionally token-efficient — about 14,000 output tokens per benchmark task versus 67,000 for Opus 4.8 — which makes long autonomous sessions dramatically cheaper.
How much does Grok 4.5 cost?
$2 per million input tokens and $6 per million output via the xAI API — more than 60% cheaper than Opus 4.8 or GPT-5.5. On CoreAI it is included under the standard plans alongside 300+ other models.
Is Grok 4.5 better than Claude Opus 4.8?
Not on raw capability — Opus 4.8 scores 56 on the Artificial Analysis Intelligence Index versus 54 for Grok 4.5. But per task it is roughly five times more token-efficient and far cheaper, so for high-volume coding work it often wins on value.
Does Grok 4.5 work with OpenAI-compatible tools?
Yes — it supports both the Responses API and Chat Completions formats, so it slots into codebases and tools built for OpenAI-style APIs without modification.
Where can I try Grok 4.5 without an xAI account?
On CoreAI — web, iOS, and Android — where you can also run it side by side against Claude Sonnet 5, GPT-5.6, and the rest of the frontier in one subscription.
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