Grok 4.5 is the latest frontier AI model from xAI, Elon Musk’s artificial intelligence company. It launched on July 8, 2026, making it one of the freshest and most talked-about models available right now.
Built specifically for real engineering work, the new model targets coding, agentic tasks, and knowledge-intensive workflows. It delivers a level of token efficiency that rivals models costing far more per API call — and that efficiency advantage is one of its defining selling points.
This guide covers everything you need to know: architecture, benchmark scores, pricing, availability, how it compares to competitors, and whether it is worth switching to in July 2026.
What Is Grok 4.5?
Grok 4.5 is xAI’s newest frontier AI model, announced and released on July 8, 2026. It is the company’s first major release since going public and completing its $60 billion acquisition of AI coding startup Cursor.
The model is designed to excel at coding, agentic workflows, and general knowledge tasks. Unlike previous Grok versions that were primarily chat-focused, this release is positioned as a serious engineering and productivity tool — not a consumer chatbot.
According to xAI, the model was trained alongside Cursor’s developer interaction data, which gave it a meaningful edge in coding-related tasks. The company describes it as “maximally truth-seeking,” meaning it is optimized to be direct and factually accurate rather than cautiously hedged like some competing models.
Grok 4.5 Architecture and Training
The model is built on xAI’s V9 foundation — a 1.5-trillion-parameter architecture that is approximately three times the size of the previous V8 model. Training ran across tens of thousands of NVIDIA GB300 GPUs at xAI’s Colossus supercluster in Memphis, Tennessee.
One important technical detail: Cursor’s supervised fine-tuning (SFT) and reinforcement learning (RL) data was added during supplemental training, not during pre-training. This distinction matters because it means the coding improvements are layered on top of the general-purpose foundation rather than baked in from the start. How broadly these gains generalize to novel coding problems remains to be seen.
A separate 2-trillion-parameter V-series model is reportedly already in development, targeting an August 2026 release. That positions Grok 4.5 as a strong mid-cycle release rather than the final word from xAI this year.
Grok 4.5 Benchmark Performance
xAI published benchmark scores across four key coding evaluations. Here is how the model compares to top competitors:
- DeepSWE 1.0 (pass@1): Scores 62.0%, behind Claude Fable (max) at 66.1% and GPT-5.5 (xhigh) at 64.31%, but ahead of Claude Opus 4.8 (max) at 55.75%.
- DeepSWE 1.1 (mini-swe-agent harness): Scores 53%, trailing Claude Fable (max) at 70% and GPT-5.5 (xhigh) at 67%, but ahead of GLM 5.2 at 44%.
- Terminal Bench 2.1: Scores 83.3%, nearly matching Claude Fable (max) at 84.3% and GPT-5.5 (xhigh) at 83.4%. This is its strongest result relative to competitors.
- SWE Bench Pro (resolve rate): Scores 64.7%, behind Claude Fable (max) at 80.4% and Claude Opus 4.8 (max) at 69.2%, but ahead of GPT-5.5 (xhigh) at 58.6%.
The pattern that emerges is consistent: the new xAI model is genuinely competitive — not the outright leader on every coding benchmark, but solidly in the top tier. It also ranked number one on Harvey’s Legal Agent Benchmark, which measures performance on structured professional and legal knowledge tasks, suggesting its strengths extend well beyond code.
Token Efficiency: The Standout Advantage
Token efficiency is where Grok 4.5 separates itself most dramatically from the competition. On SWE Bench Pro, the model completed tasks using an average of just 15,954 output tokens.
By comparison, Claude Opus 4.8 (max) used approximately 67,020 output tokens on the same benchmark — roughly 4.2 times more. Fewer output tokens means lower cost per completed task and faster end-to-end execution time on agentic pipelines.
xAI claims the model solves tasks in under half the number of steps compared to leading alternatives. In practical terms, this means an agentic coding workflow that would cost $10 on Opus 4.8 might cost closer to $2.50 when using the xAI model — a significant operational saving for teams running large-scale automation.
This efficiency gain is not just a cost story. It also affects latency: fewer steps and fewer output tokens means faster task completion, which matters for real-time developer tools like Cursor where waiting for an AI agent to finish a refactoring task impacts workflow.
Grok 4.5 Speed
The model is served at 80 tokens per second (TPS) according to xAI’s official figures. Independent benchmarking from Artificial Analysis recorded output speeds of up to 92.1 TPS from the SpaceXAI API provider — faster than the advertised rate under optimal conditions.
Time-to-first-token sits at approximately 15.22 seconds. For a frontier-class model of this parameter count, that is a competitive latency profile. When combined with the high token efficiency discussed above, the total wall-clock time per agentic task is significantly lower than for models that use more steps and more output tokens.
Grok 4.5 Pricing
Pricing is one of the most compelling aspects of this release. The official rates are:
- Input tokens: $2 per million tokens
- Output tokens: $6 per million tokens
- Blended price (with prompt caching): approximately $1.35 per million tokens
For context, comparable flagship models from Anthropic and OpenAI are priced considerably higher — often 3-5x more at the output token level. xAI is making a deliberate value play here, explicitly pitching the model as “Opus-class but cheaper.” Free usage is available for a limited time in both Grok Build and Cursor on all plans.
Where Can You Access Grok 4.5?
As of the July 8 launch, the model is available through three main channels:
- Grok Build: xAI’s developer-facing platform, where it is now the default model for all new projects.
- Cursor: Available on all Cursor plans including the free tier, for a limited introductory period. This is the most accessible entry point for developers who already use Cursor daily.
- SpaceXAI API Console: Available for enterprise and API access at the standard pricing listed above. Supports JSON mode and function calling (tool use).
One important caveat: the model is not yet available in the European Union. xAI expects EU availability by mid-July 2026, with the delay likely related to compliance requirements under the EU AI Act. Developers in the EU should check back in the coming weeks.
How Does Grok 4.5 Compare to Other Models?
Here is a direct comparison against the other major frontier models available in July 2026:
- vs. Claude Fable 5 (max): Claude Fable 5 leads on all four coding benchmarks, most strikingly on SWE Bench Pro at 80.4% vs. 64.7%. However, the xAI model wins on token efficiency by a wide margin and is priced significantly lower. For teams where budget and speed matter more than squeezing the last few benchmark points, it is a strong alternative.
- vs. GPT-5.5 (xhigh): The xAI model outperforms GPT-5.5 on SWE Bench Pro (64.7% vs. 58.6%) and costs less. GPT-5.5 leads slightly on DeepSWE 1.1 (67% vs. 53%), so the choice depends on which tasks you prioritize.
- vs. Claude Opus 4.8: Broadly competitive, with the xAI model beating Opus on Terminal Bench 2.1 and trailing slightly on SWE Bench Pro (64.7% vs. 69.2%). The 4.2x token efficiency advantage strongly favors the xAI model for high-volume use cases.
- vs. Gemini 3.5 Pro: Gemini 3.5 Pro is not yet publicly available (expected July 17, 2026). It is expected to offer a 2-million-token context window and Deep Think reasoning mode. A proper head-to-head comparison will be possible after that launch.
The Cursor Connection: Why It Matters
The partnership between xAI and Cursor is more than a co-marketing announcement. Cursor is one of the most widely used AI coding editors in the industry, relied on by hundreds of thousands of professional software engineers every day.
The supervised fine-tuning data derived from real developer interactions — actual edits, refactors, debugging sessions, and code reviews — represents an extremely high-quality training signal. This is the kind of data that is nearly impossible to replicate synthetically, and it is a key reason why the model performs so well on realistic coding benchmarks.
Notably, the compute capacity used to train the model is the same infrastructure xAI leases to competitors like Anthropic and Google. The Cursor acquisition, valued at $60 billion, thus gives xAI a proprietary data flywheel that its compute-sharing partners cannot access. This structural advantage is likely to compound over time as more Cursor users interact with the model.
Grok 4.5 Use Cases
Based on its benchmark profile and design goals, the model is best suited for the following use cases:
- Software engineering and coding agents: Excels at autonomously resolving real GitHub issues, writing production-ready code, and navigating large software repositories via agentic frameworks like Claude Code or similar tools.
- Legal and professional knowledge work: The number-one ranking on Harvey’s Legal Agent Benchmark indicates strong capability for document analysis, contract review, due diligence workflows, and structured professional reasoning.
- Cost-sensitive API deployments: At $2/$6 per million tokens combined with outstanding token efficiency, it offers a compelling price-performance ratio for teams running high-volume inference at scale.
- Multi-step agentic pipelines: The ability to complete complex tasks in fewer steps makes it especially well-suited for orchestration workflows where every extra step adds latency and cost.
- Enterprise knowledge work: Its strong general-purpose foundation combined with professional benchmark performance makes it viable for structured tasks like data extraction, report generation, and process automation.
Limitations to Keep in Mind
No model is without weaknesses, and it is worth being honest about where this one falls short. On pure coding benchmark performance, Claude Fable 5 remains the clear leader at the frontier. The 500K-token context window, while large by historical standards, is expected to be significantly outclassed by Gemini 3.5 Pro’s 2-million-token context when that model launches.
EU availability is pending, which limits access for European developers and enterprises. And because the Cursor training data was added during supplemental rather than pre-training, some coding-specific gains may not generalize as broadly as they would if the data had been present from the beginning of the training run.
xAI’s benchmark reporting also uses some proprietary harnesses for comparison, and full independent third-party replication of all numbers has not yet been completed at the time of writing. Take the specific percentages as directionally informative rather than definitive.
Who Should Use Grok 4.5?
The model is an excellent fit for development teams and enterprises that are price-sensitive and run high-volume agentic workflows. If you are currently using Claude Opus 4.8 and find the cost significant, the xAI model deserves serious evaluation — the token efficiency alone could cut your inference costs by 50-75%.
It is also a natural fit for anyone already embedded in the Cursor ecosystem. The Cursor integration is deep and first-party, and the free introductory access makes it easy to test without commitment.
If you need the absolute best performance on coding benchmarks and cost is a secondary concern, Claude Fable 5 or GPT-5.5 remain the stronger choices for now. But for the majority of real-world production use cases — where “good enough plus cheap” beats “best but expensive” — the new xAI model is a compelling proposition.
Final Verdict
Grok 4.5 is a genuinely impressive model that represents a meaningful step forward in the competitive AI landscape. Its standout qualities are token efficiency, competitive pricing, and strong performance across coding and professional knowledge benchmarks. It may not be the single best model on every leaderboard, but it offers one of the best value propositions among frontier-tier AI models available today.
For developers and enterprises who want frontier-level capability without frontier-level API costs, the xAI model launched on July 8 is worth serious attention. It is available right now in Cursor and Grok Build, making it accessible with zero setup friction.
As xAI continues building toward its 2T V-series model expected later in 2026, the competitive pressure on Anthropic, OpenAI, and Google is only going to increase. Grok 4.5 is a clear signal that xAI has arrived as a top-tier AI lab — not just in raw model capability, but in the engineering discipline needed to ship models that are fast, efficient, and cost-effective at scale.