Grok 4.3 vs GPT-5.6 Terra
Head-to-head specifications
| Metric | Grok 4.3 | GPT-5.6 Terra | Difference |
|---|---|---|---|
| Intelligence Index | 38.0 | 55.0 | -30.9% |
| Coding Index | 42.2 | 76.7 | -45.0% |
| Agentic Index | 24.1 | 47.4 | — |
| Context window | 1M tokens | 1M tokens | — |
| Blended price ($/1M tokens) | $0.52 | $1.14 | -54.4% |
| Output speed (tokens/s) | 112 | 138 | -18.8% |
| Access | Proprietary API | Proprietary API | — |
- GPT-5.6 Terra leads overall capability (Intelligence Index 55.0 vs 38.0).
- Grok 4.3 is the cheaper model to run at $0.52/1M blended tokens — about 2.2× cheaper.
Verdict: Grok 4.3 or GPT-5.6 Terra?
Grok 4.3 advantages
- Affordability (+54%)
GPT-5.6 Terra advantages
- General intelligence (+31%)
- Coding ability (+45%)
- Agentic task performance (+49%)
- Output speed (+19%)
Which should you choose?
- Choose the Grok 4.3 if you want the lowest cost per token at scale.
- Choose the GPT-5.6 Terra if you need the strongest overall reasoning and accuracy.
Value for money
Grok 4.3 offers more intelligence per dollar (1.5× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
Grok 4.3 vs GPT-5.6 Terra: which should you choose?
Grok 4.3 — xAI multimodal model with an Intelligence Index of 38, a 1M-token context window and a blended price of $0.52/1M tokens.
GPT-5.6 Terra — OpenAI multimodal model with an Intelligence Index of 55, a 1M-token context window and a blended price of $1.14/1M tokens.
Grok 4.3 vs GPT-5.6 Terra: GPT-5.6 Terra scores higher on the Intelligence Index. GPT-5.6 Terra leads overall capability (Intelligence Index 55.0 vs 38.0). Grok 4.3 is the cheaper model to run at $0.52/1M blended tokens — about 2.2× cheaper.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the GPT-5.6 Terra scores 55.0 versus 38.0. For software development, the Coding Index puts GPT-5.6 Terra ahead (76.7 vs 42.2). On agentic, multi-step tool-use tasks, GPT-5.6 Terra measures stronger. Composite indices summarize many evaluations, but always test on your own workload before committing.
Context window and speed
The Grok 4.3 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, GPT-5.6 Terra generates faster (138 vs 112 tokens/s), which matters for interactive apps and high-volume pipelines.
Pricing and access
At blended per-token rates, Grok 4.3 is the cheaper model to run ($0.52 vs $1.14 per 1M tokens). Grok 4.3 is proprietary api and GPT-5.6 Terra 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 Grok 4.3 better than the GPT-5.6 Terra?
GPT-5.6 Terra takes the overall edge, though Grok 4.3 wins in specific areas worth weighing. GPT-5.6 Terra leads overall capability (Intelligence Index 55.0 vs 38.0).
What is the main difference between the Grok 4.3 and the GPT-5.6 Terra?
GPT-5.6 Terra leads overall capability (Intelligence Index 55.0 vs 38.0). Grok 4.3 is the cheaper model to run at $0.52/1M blended tokens — about 2.2× cheaper.
Which is better value?
Grok 4.3 offers more intelligence per dollar (1.5× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
Which should I choose?
Choose the Grok 4.3 if you want the lowest cost per token at scale. Choose the GPT-5.6 Terra if you need the strongest overall reasoning and accuracy.
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.