Grok 4.5's Coding Cost/Performance Trade-off, Explained in One Table

On July 8, 2026, SpaceXAI shipped Grok 4.5, a coding-and-agentic model priced at $2 per million input tokens and $6 per million output — more than 60% cheaper than Claude Opus 4.8's headline rate, with cached input at just $0.50/M. Independent coding-agent evaluations put it at $2.49 per completed task versus $11.80 for Claude Code. The catch: hallucination rate jumped from 25% to 54% as raw accuracy rose from 35% to 52% on the same benchmark run — one architecture decision, two numbers.

What You'll Learn

What Grok 4.5 actually costs against Opus 4.8 and GPT-5.5 on real coding-agent tasks, where it wins and loses on independent benchmarks, and the one rule for deciding when the discount is worth the added risk.

The Numbers

Metric	Grok 4.5	Comparison
Pricing	$2/M in, $6/M out	60%+ cheaper than Opus 4.8
Cached input	$0.50/M	75% discount
Cost per agent task	$2.49	Claude Code: $11.80
Token use (SWE-Bench Pro)	4.2x fewer tokens	vs. Opus 4.8
Artificial Analysis Intelligence Index	54	Fable 5: 60, Opus 4.8: 56, GPT-5.5: 55
DeepSWE 1.1 (real GitHub issues resolved)	53%	GPT-5.5: 67%, Fable 5: 70%
Hallucination rate	54%, up from 25%	accuracy rose 35% → 52% in tandem

The One Rule

Route by task risk, not task type. For scaffolding, boilerplate, and high-volume agent loops where you review every diff anyway, Grok 4.5's 4-5x cost edge is close to free money. For anything meant to resolve a real issue unattended, the DeepSWE 1.1 gap (53% vs. 70% for Fable 5) is exactly where the extra hallucinations bite. Keep it out of unattended-agent loops until you've A/B tested it against your own repo's issues — the same lesson the Kimi K2.7 Code / GLM-5.2 rollout taught in June: published benchmarks tell you where to start testing, not what to ship.

Conclusion

Grok 4.5 is the clearest evidence yet that frontier coding models now compete on cost-per-task as hard as on raw capability. The trade-off is quantified, not marketing copy: cheaper and faster, with a materially higher hallucination rate on unattended agentic work. Route accordingly. For the full multi-model cost comparison across Grok 4.5, Opus 4.8, Kimi K2.7 Code, and GLM-5.2, see Chapter 18 of the Vibe Coding Ebook; for ongoing coverage of AI coding tool releases, see endofcoding.com.