GPT-5.1 vs Grok 4.3
Head-to-head specifications
| Metric | GPT-5.1 | Grok 4.3 | Difference |
|---|---|---|---|
| Intelligence Index | 37.0 | 38.0 | -2.6% |
| Coding Index | 49.4 | 42.2 | +17.1% |
| Agentic Index | 21.0 | 24.1 | — |
| Context window | 512K tokens | 1M tokens | — |
| Blended price ($/1M tokens) | $0.77 | $0.52 | +48.1% |
| Output speed (tokens/s) | 106 | 112 | -5.4% |
| Access | Proprietary API | Proprietary API | — |
- Grok 4.3 leads overall capability (Intelligence Index 38.0 vs 37.0).
- Grok 4.3 is the cheaper model to run at $0.52/1M blended tokens — about 1.5× cheaper.
- Grok 4.3 offers the larger context window (1M tokens), useful for long documents and codebases.
Verdict: GPT-5.1 or Grok 4.3?
GPT-5.1 advantages
- Coding ability (+15%)
Grok 4.3 advantages
- Agentic task performance (+13%)
- Context window (+49%)
- Affordability (+32%)
- Output speed (+5%)
Which should you choose?
- Choose the GPT-5.1 if coding and software development are your main workload.
- Choose the Grok 4.3 if you build agents or multi-step tool-use workflows.
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.
GPT-5.1 vs Grok 4.3: which should you choose?
GPT-5.1 — OpenAI multimodal model with an Intelligence Index of 37, a 512K-token context window and a blended price of $0.77/1M tokens.
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-5.1 vs Grok 4.3: Grok 4.3 scores higher on the Intelligence Index. Grok 4.3 leads overall capability (Intelligence Index 38.0 vs 37.0). Grok 4.3 is the cheaper model to run at $0.52/1M blended tokens — about 1.5× cheaper.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the Grok 4.3 scores 38.0 versus 37.0. For software development, the Coding Index puts GPT-5.1 ahead (49.4 vs 42.2). On agentic, multi-step tool-use tasks, Grok 4.3 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, Grok 4.3 generates faster (112 vs 106 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 $0.77 per 1M tokens). GPT-5.1 is proprietary api and Grok 4.3 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-5.1 better than the Grok 4.3?
Grok 4.3 takes the overall edge, though GPT-5.1 wins in specific areas worth weighing. Grok 4.3 leads overall capability (Intelligence Index 38.0 vs 37.0).
What is the main difference between the GPT-5.1 and the Grok 4.3?
Grok 4.3 leads overall capability (Intelligence Index 38.0 vs 37.0). Grok 4.3 is the cheaper model to run at $0.52/1M blended tokens — about 1.5× 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 GPT-5.1 if coding and software development are your main workload. Choose the Grok 4.3 if you build agents or multi-step tool-use workflows.
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.