--- title: "Grok 4.5: xAI's coding model, reviewed honestly" canonical_url: "https://tryiro.com/blog/grok-4-5" site: "Iro AI" site_url: "https://tryiro.com" app_store: "https://apps.apple.com/app/id6759628066" language: en-US keywords: ["Grok 4.5", "Grok 4.5 benchmarks", "Grok 4.5 pricing", "xAI Grok", "Grok for coding", "Grok 4.5 vs GPT-5.6"] date_published: "2026-07-26" date_modified: "2026-07-26" reading_time_minutes: 6 author: "Alex Furukawa" license: "© 2026 Iro AI" canonical_llm_reference: "https://tryiro.com/llms-full.txt" pillar: "ai-tools" --- # Grok 4.5: xAI's coding model, reviewed honestly > Fourth place on the intelligence leaderboard, a fifth of the price, and trained on real developer sessions. Here's what Grok 4.5 is genuinely good at. **Canonical:** https://tryiro.com/blog/grok-4-5 **Published:** 2026-07-26 **Reading time:** ~6 min **Author:** Alex Furukawa — Founder of Iro AI ## Key takeaways - Grok 4.5 launched on 8 July 2026 at $2 per million input tokens and $6 per million output — roughly a fifth of what the top-ranked models cost. - It is xAI's first model built specifically for coding and agentic work, trained using real developer session data rather than general web text. - Reported results: 83.3% on Terminal-Bench 2.1, 64.7% on SWE-Bench Pro, and 54 on the Artificial Analysis Intelligence Index — fourth place at launch, behind Claude Fable 5, GPT-5.5, and Claude Opus 4.8. - Its real advantage is token efficiency: it reportedly uses 3–4x fewer tokens per task than the priciest rivals, which compounds the price gap in long agent runs. ## The short answer **Grok 4.5 is xAI's first model built specifically for coding and agentic work, released on 8 July 2026 at $2 per million input tokens and $6 per million output.** It is not the most capable model available — it landed fourth on the Artificial Analysis Intelligence Index at launch with a score of 54 — but it costs roughly a fifth of what the models above it charge. That trade is the entire pitch, and for a specific kind of work it is a good one: long agent runs where token consumption compounds, and high-volume coding tasks where a small capability gap costs less than a large price gap. ## What makes it different Grok 4.5 is a mixture-of-experts model trained on trillions of tokens of real Cursor developer session data — actual people working in actual codebases, rather than general web text and public repositories. The bet is that watching how developers iterate teaches a model something that reading finished code does not: what a half-broken change looks like, and what people do next. xAI leaned on evaluations built to measure what a model can do inside a real repository over an extended session, rather than one-shot puzzle solving. That mirrors the wider 2026 shift — every lab has moved from knowledge quizzes toward agentic benchmarks, because agentic work is where the money is and where models still visibly fail. The most under-discussed number: Grok 4.5 reportedly uses 3–4x fewer tokens per task than the most expensive rivals while matching GPT-5.5 in the Codex harness on the Coding Agent Index (76). Combine that with a per-token price a fifth of theirs and the effective cost difference on a long agent run is large — this is a bigger deal than the headline price alone suggests. ## The numbers, in context For comparison, OpenAI reported Sol Ultra at 91.9% and base Sol at 88.8% on that same Terminal-Bench 2.1 benchmark. So Grok 4.5 is meaningfully behind the frontier on agentic coding — roughly five points behind base Sol — while costing $2/$6 against Sol's $5/$30. Whether that trade is good depends entirely on your failure tolerance. Five percentage points on a benchmark means something different when you are generating throwaway scripts than when you are running an unattended agent against production code. ## When Grok 4.5 is the right call **Use it when:** you are running high-volume coding or agentic tasks where per-task cost is the binding constraint; your workflow reviews output before it lands anywhere important; or you are running long agent sessions where the token-efficiency advantage compounds. **Use something else when:** the task is a one-off where a few dollars of tokens is irrelevant and you just want the best answer — use GPT-5.6 Sol or Claude Fable 5. Or when you need very long context, where Claude Opus 5's 1M-token window is the differentiator. **If you are not a developer:** Grok 4.5 is not aimed at you. It is a coding and agent model, and its strengths show up in tooling rather than chat. For general everyday use, the assistant you already know well will out-perform a new model you don't — the skill gap between users is consistently larger than the capability gap between the top few models. ## FAQ **What is Grok 4.5?** Grok 4.5 is xAI's coding and agentic model, released on 8 July 2026. It is a mixture-of-experts model trained on real developer session data, priced at $2 per million input tokens and $6 per million output. **Is Grok 4.5 good for coding?** It is competitive but not leading. It reports 83.3% on Terminal-Bench 2.1 and 64.7% on SWE-Bench Pro, and matches GPT-5.5 in the Codex harness on the Coding Agent Index. GPT-5.6 Sol scores higher on the same agentic coding benchmark, but costs substantially more per token. **How much does Grok 4.5 cost?** $2 per million input tokens and $6 per million output tokens — roughly a fifth of the cost of the top-ranked models at its launch. It also reportedly uses 3–4x fewer tokens per task than the most expensive rivals, which widens the effective saving on long tasks. **How does Grok 4.5 compare to GPT-5.6?** GPT-5.6 Sol is stronger on agentic coding benchmarks (88.8% vs 83.3% on Terminal-Bench 2.1) but costs $5/$30 per million tokens against Grok 4.5's $2/$6. GPT-5.6 Luna is the closer price competitor at $1/$6. Grok 4.5 sits between them on both price and reported capability. ## Read next - [Every 2026 AI model release, tracked](https://tryiro.com/blog/new-ai-models-2026) - [GPT-5.6: Luna vs Terra vs Sol](https://tryiro.com/blog/gpt-5-6) - [The best AI coding tools](https://tryiro.com/blog/best-ai-coding-tools) ## About the author Alex Furukawa — Founder of Iro AI. Alex Furukawa is the founder of Iro AI, the gamified app for learning to use AI well. He writes about practical AI fluency — prompting, AI tools, and the daily habits that turn AI from a novelty into real leverage.