GPT-5.6 Sol vs Grok 3 mini Reasoning
Head-to-head specifications
| Metric | GPT-5.6 Sol | Grok 3 mini Reasoning | Difference |
|---|---|---|---|
| Intelligence Index | 59.0 | 27.0 | +118.5% |
| Context window | 1M tokens | 1M tokens | — |
| Blended price ($/1M tokens) | $1.54 | $0.16 | +862.5% |
| Output speed (tokens/s) | 57 | 66 | -13.6% |
| Access | Proprietary API | Proprietary API | — |
- GPT-5.6 Sol leads overall capability (Intelligence Index 59.0 vs 27.0).
- Grok 3 mini Reasoning is the cheaper model to run at $0.16/1M blended tokens — about 9.6× cheaper.
Verdict: GPT-5.6 Sol or Grok 3 mini Reasoning?
GPT-5.6 Sol advantages
- General intelligence (+54%)
Grok 3 mini Reasoning advantages
- Affordability (+90%)
- Output speed (+14%)
Which should you choose?
- Choose the GPT-5.6 Sol if you need the strongest overall reasoning and accuracy.
- Choose the Grok 3 mini Reasoning if you want the lowest cost per token at scale.
Value for money
Grok 3 mini Reasoning offers more intelligence per dollar (4.4× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
GPT-5.6 Sol vs Grok 3 mini Reasoning: which should you choose?
GPT-5.6 Sol — OpenAI multimodal model with an Intelligence Index of 59, a 1M-token context window and a blended price of $1.54/1M tokens.
Grok 3 mini Reasoning — xAI multimodal model with an Intelligence Index of 27, a 1M-token context window and a blended price of $0.16/1M tokens.
GPT-5.6 Sol vs Grok 3 mini Reasoning: GPT-5.6 Sol scores higher on the Intelligence Index. GPT-5.6 Sol leads overall capability (Intelligence Index 59.0 vs 27.0). Grok 3 mini Reasoning is the cheaper model to run at $0.16/1M blended tokens — about 9.6× cheaper.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the GPT-5.6 Sol scores 59.0 versus 27.0. Composite indices summarize many evaluations, but always test on your own workload before committing.
Context window and speed
The GPT-5.6 Sol accepts up to 1 million tokens per request, which sets how much documentation, transcript or code it can reason over at once. In measured throughput, Grok 3 mini Reasoning generates faster (66 vs 57 tokens/s), which matters for interactive apps and high-volume pipelines.
Pricing and access
At blended per-token rates, Grok 3 mini Reasoning is the cheaper model to run ($0.16 vs $1.54 per 1M tokens). GPT-5.6 Sol is proprietary api and Grok 3 mini Reasoning is proprietary api. Open-weight models can be self-hosted, trading per-call cost for infrastructure you manage; for production also weigh rate limits, throughput and data-residency requirements.
The verdict
Both are credible choices in the ai model comparison space; the specification table above lays out every metric so you can weigh the trade-offs that matter to you. Pick the one whose strengths line up with how you will actually use it.
Frequently asked questions
Is the GPT-5.6 Sol better than the Grok 3 mini Reasoning?
These two are closely matched — the right pick comes down to which specific strengths you value and the price you actually pay. GPT-5.6 Sol leads overall capability (Intelligence Index 59.0 vs 27.0).
What is the main difference between the GPT-5.6 Sol and the Grok 3 mini Reasoning?
GPT-5.6 Sol leads overall capability (Intelligence Index 59.0 vs 27.0). Grok 3 mini Reasoning is the cheaper model to run at $0.16/1M blended tokens — about 9.6× cheaper.
Which is better value?
Grok 3 mini Reasoning offers more intelligence per dollar (4.4× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
Which should I choose?
Choose the GPT-5.6 Sol if you need the strongest overall reasoning and accuracy. Choose the Grok 3 mini Reasoning if you want the lowest cost per token at scale.
Methodology
Large language models are compared on independent leaderboard metrics: an Intelligence Index (a composite of reasoning and knowledge evaluations), Coding and Agentic indices where measured, community arena Elo, maximum context window, a blended API price per million tokens (weighted across cache-hit, input and output rates), and measured output speed in tokens per second. Where a model ships multiple reasoning-effort variants, we report its strongest variant. Benchmarks capture only part of real-world quality, which also depends on tool use, latency, safety and task fit — and this space moves quickly, so figures reflect the leaderboard snapshot on the page date.