GPT-5.6 vs Grok 4.5
OpenAI's new flagship family against SpaceXAI's value workhorse — a near-exact tie on SWE-bench Pro sits next to one of the widest price gaps on this site.
GPT-5.6 vs Grok 4.5: side-by-side
| GPT-5.6 (Sol) | Grok 4.5 | |
|---|---|---|
| Maker | OpenAI | SpaceXAI (formerly xAI) |
| Released | Preview 26 Jun 2026 · GA 9 Jul 2026 | Announced 8 Jul · public 9 Jul 2026 |
| Tier | Flagship (Terra/Luna below) | Workhorse ("Opus-class" positioning) |
| Context window | 1,050,000 tokens | 500,000 tokens |
| API price (per 1M) | $5 / $30 (Sol) | $2 / $6 |
| Cheaper tiers | Terra $2.50/$15 · Luna $1/$6 | None — single rate card |
| Speed | Up to ~750 tokens/sec (Sol, on Cerebras) | ~80 output tokens/second |
| Access | ChatGPT, ChatGPT Work, Codex, API | xAI API console, Grok Build, Cursor, OpenRouter · EU pending |
| Standout | 54% more token-efficient on agentic coding per OpenAI; cybersecurity leader | Token efficiency — ~2x fewer tokens claimed vs leading models |
Price comparison
| Model | Input (per 1M) | Output (per 1M) |
|---|---|---|
| GPT-5.6 Luna | $1.00 | $6.00 |
| Grok 4.5 | $2.00 | $6.00 |
| GPT-5.6 Terra | $2.50 | $15.00 |
| GPT-5.6 Sol | $5.00 | $30.00 |
Estimate your monthly API cost for GPT-5.6 vs Grok 4.5 with the LLM API pricing calculator →
Published benchmark figures
Each figure is the model's own published score as listed on its AI Model Hub page. As always, vendor-published benchmarks favour the vendor's chosen suite and configuration (Sol's figures use "max" reasoning effort where noted).
| Model | Benchmark | Published score |
|---|---|---|
| GPT-5.6 Sol | Terminal-Bench 2.1 | 91.9% |
| GPT-5.6 Sol | SWE-bench Pro | 64.6% |
| GPT-5.6 Sol | Agents' Last Exam | 53.6 |
| Grok 4.5 | Terminal-Bench 2.1 | 83.3% |
| Grok 4.5 | SWE-bench Pro | 64.7% |
| Grok 4.5 | DeepSWE 1.1 | 53% |
What the table says
- Benchmarks. SWE-bench Pro is a virtual dead heat — 64.6% vs 64.7%, a 0.1-point gap that is noise, not signal. Terminal-Bench 2.1 is where Sol pulls ahead clearly: 91.9% vs 83.3%, an 8.6-point margin.
- Pricing. Sol costs 2.5x Grok 4.5's input rate and 5x its output rate. The closer match is GPT-5.6's own Luna tier: $1 input undercuts Grok 4.5's $2, while the $6 output rate is identical.
- Context. GPT-5.6 more than doubles Grok 4.5's window — 1.05M vs 500K tokens — across all three of its variants, not just Sol.
- Efficiency claims. Both vendors lead with token-efficiency marketing: OpenAI says Sol is 54% more token-efficient on agentic coding than the next-highest scorer; SpaceXAI says Grok 4.5 uses roughly half the tokens of leading models on the same class of task. Neither claim is directly comparable to the other since they're measured on different indices.
Key takeaway
If SWE-bench-style coding is your workload, Grok 4.5's near-identical score at less than half of Sol's price is hard to beat — and GPT-5.6's own Luna tier gets closer to that price point than Sol does. If your workload leans on longer agentic/terminal tasks or needs the larger context window, Sol's Terminal-Bench lead and 1.05M-token window are the deciding factors. Run both scenarios through the pricing calculator before committing.
Full GPT-5.6 overview Full Grok 4.5 overview
Frequently asked questions
Which is cheaper, GPT-5.6 or Grok 4.5?
Grok 4.5 — $2/$6 per 1M tokens versus GPT-5.6 Sol's $5/$30. GPT-5.6's Luna tier ($1/$6) actually undercuts Grok 4.5 on input while matching its output price exactly.
How close are GPT-5.6 and Grok 4.5 on benchmarks?
On SWE-bench Pro they are nearly tied — 64.6% (Sol) vs 64.7% (Grok 4.5). On Terminal-Bench 2.1, Sol leads more clearly at 91.9% vs 83.3%.
Which has the bigger context window?
GPT-5.6 — 1,050,000 tokens across all three variants, versus 500,000 for Grok 4.5.
Should I use Luna or Grok 4.5 for cost-sensitive work?
Both are candidates. Luna's $1 input rate is half of Grok 4.5's $2, with an identical $6 output rate — but Grok 4.5 claims roughly 2x the token efficiency of leading models, which can offset the sticker-price gap.