AI Model Comparison

GPT-5.1 vs GPT-5.6 Sol

Verdict
GPT-5.1 vs GPT-5.6 Sol: GPT-5.6 Sol scores higher on the Intelligence Index

Head-to-head specifications

MetricGPT-5.1GPT-5.6 SolDifference
Intelligence Index37.059.0-37.3%
Coding Index49.477.4-36.2%
Agentic Index21.054.0
Context window512K tokens1M tokens
Blended price ($/1M tokens)$0.77$1.54-50.0%
Output speed (tokens/s)10657+86.0%
AccessProprietary APIProprietary API
  • GPT-5.6 Sol leads overall capability (Intelligence Index 59.0 vs 37.0).
  • GPT-5.1 is the cheaper model to run at $0.77/1M blended tokens — about 2.0× cheaper.
  • GPT-5.6 Sol offers the larger context window (1M tokens), useful for long documents and codebases.

Verdict: GPT-5.1 or GPT-5.6 Sol?

Our recommendation
GPT-5.6 Sol takes the overall edge, though GPT-5.1 wins in specific areas worth weighing.

GPT-5.1 advantages

  • Affordability (+50%)
  • Output speed (+46%)

GPT-5.6 Sol advantages

  • General intelligence (+37%)
  • Coding ability (+36%)
  • Agentic task performance (+61%)
  • Context window (+49%)

Which should you choose?

  • Choose the GPT-5.1 if you want the lowest cost per token at scale.
  • Choose the GPT-5.6 Sol if you need the strongest overall reasoning and accuracy.
  • Choose the GPT-5.1 if low latency and fast generation matter for your application.

Value for money

GPT-5.1 offers more intelligence per dollar (1.3× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.

GPT-5.1 vs GPT-5.6 Sol: 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.

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.

GPT-5.1 vs GPT-5.6 Sol: GPT-5.6 Sol scores higher on the Intelligence Index. GPT-5.6 Sol leads overall capability (Intelligence Index 59.0 vs 37.0). GPT-5.1 is the cheaper model to run at $0.77/1M blended tokens — about 2.0× cheaper.

Capability: intelligence, coding and agentic work

On the composite Intelligence Index the GPT-5.6 Sol scores 59.0 versus 37.0. For software development, the Coding Index puts GPT-5.6 Sol ahead (77.4 vs 49.4). On agentic, multi-step tool-use tasks, GPT-5.6 Sol measures stronger. 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, GPT-5.1 generates faster (106 vs 57 tokens/s), which matters for interactive apps and high-volume pipelines.

Pricing and access

At blended per-token rates, GPT-5.1 is the cheaper model to run ($0.77 vs $1.54 per 1M tokens). GPT-5.1 is proprietary api and GPT-5.6 Sol 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 GPT-5.6 Sol?

GPT-5.6 Sol takes the overall edge, though GPT-5.1 wins in specific areas worth weighing. GPT-5.6 Sol leads overall capability (Intelligence Index 59.0 vs 37.0).

What is the main difference between the GPT-5.1 and the GPT-5.6 Sol?

GPT-5.6 Sol leads overall capability (Intelligence Index 59.0 vs 37.0). GPT-5.1 is the cheaper model to run at $0.77/1M blended tokens — about 2.0× cheaper.

Which is better value?

GPT-5.1 offers more intelligence per dollar (1.3× 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 you want the lowest cost per token at scale. Choose the GPT-5.6 Sol 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.

MC
Marcus Chen
Hardware & Product Analyst

Marcus benchmarks processors, GPUs, phones and vehicles and maintains normalized performance databases.

MSc Computer Engineering10+ years review experience
✓ Reviewed by Priya Nair, Data Quality Reviewer.
Last updated 2026-07-01
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