Claude Opus 5.5 leads GPT-6.1 Sol on intelligence, coding and output speed. GPT-6.1 Sol delivers each task for a fraction of the cost and starts answering sooner. This guide compares the two on benchmarks, cost per task, coding and real user feedback, then shows how to run the same prompt on both in 1min.AI so you can judge the difference on your own work.

Key takeaways

• Opus 5.5 scores 58 and Sol scores 52 on the Artificial Analysis Intelligence Index at max effort.
• Sol averages $0.72 per task at max effort. Opus 5.5 averages $5.98.
• Opus 5.5 streams at 96 tokens per second. Sol streams at 55 but returns its first token sooner.
• Developers split by task: Sol for debugging and review, Opus for UI and architecture.

6.1 Sol vs Opus 5.5 at a Glance

OpenAI released GPT-6.1 Sol on September 29, one week after Anthropic released Claude Opus 5.5. Both aim to deliver near-flagship results at a lower price. This table shows how they compare at max effort.

Sources: Artificial Analysis, BenchLM, official model documentation.

Benchmarks: Which Model Scores Higher?

Intelligence Index and Industry Scores

Opus 5.5 leads every index Artificial Analysis publishes for these two models at max effort.

The gap depends on the effort setting. At low effort both models score 42. At medium effort it is 51 for Opus 5.5 and 48 for Sol, so the lead grows as you ask for more thinking.

What Independent Scoreboards Add

BenchLM reaches the same direction with a useful caveat. Opus 5.5 scores 86.69 overall against 84.19 for Sol, but the 90% score intervals overlap, so BenchLM treats it as a lead, not a settled win. Opus 5.5 is ahead on knowledge (90.3 vs 86.1). Sol is ahead on some reasoning and math rows, including ARC-AGI-2 (94.2% vs 91.7%) and FrontierMath Tier 4 (100% vs 95%).

Speed and Latency

Opus 5.5 generates text faster once it starts: 96 vs 55 tokens per second at max effort, and 81 vs 48 at medium. Sol starts sooner. At medium effort its time to first token is 4.41 seconds against 12.99 for Opus 5.5. Many short prompts feel snappier on Sol. Long outputs finish sooner on Opus 5.5.

Coding: Opus 5.5 vs GPT 6.1 Sol

On BenchLM’s coding score, Opus 5.5 leads 82.7 to 71.0. Its Engineering Index lead (60 vs 54) points the same way. Benchmarks measure set tasks, though, so here is how each model tends to behave in daily work.

Debugging and Code Review

Developers on r/codex describe Sol as slow but steady and strong at taking code apart, debugging and reviewing. One user said it did not burn through usage quickly. If most of your day goes to finding faults in existing code, Sol earns a test.

UI Design and Long Agentic Tasks

Several users report that Opus 5.5 produces better interface designs and feels faster and more pleasant to work with. Anthropic positions it for long-running agentic coding, including large code migrations. One user cautioned that it sometimes makes choices you did not request, so check its output on edge cases.

GPT 6.1 Sol vs Opus 5.5 Cost: What a Task Really Takes

API Token Rates

Sol’s listed rates are exactly half of Opus 5.5’s. BenchLM’s sample workloads confirm it: a repository review costs about $0.13 on Sol and $0.26 on Opus 5.5.

Cost per Task by Effort Level

Token rates miss one thing. Reasoning models spend tokens thinking, so the real cost depends on how much each model thinks. Artificial Analysis measures the average cost per task:

Where Sol Is the Smarter Choice

Sol at max effort scores 52 for $0.72 per task. Opus 5.5 at medium effort scores 51 for $1.34. That means similar intelligence for about half the cost. For repeatable, high-volume work such as batch summaries, document translation or structured extraction, Sol stretches your credits much further. The same pattern holds in 1min.AI, where Sol uses roughly half the credits of Opus 5.5 per page of text.

What Reddit Users Say

The opus 5.5 vs gpt 6.1 sol reddit threads agree on a pattern, not a winner:

• Opus 5.5: faster, more pleasant to work with, stronger UI results and good for setting up a project’s foundations.
• Sol 6.1: methodical, strong at debugging and review and light on usage, but slower.
• Common workflow: several developers keep both models and assign each to different stages of a project.

These are personal experiences, not measurements. They show why a side-by-side test beats any single score.

Which Should You Choose?

Choose GPT-6.1 Sol if you:

• run repeatable, high-volume tasks where cost per task adds up
• spend most of your time debugging and reviewing code
• want answers to begin quickly on short prompts
• need the larger 1.05M-token context window

Choose Claude Opus 5.5 if you:

• tackle complex reasoning, architecture or multi-file engineering
• work in finance, strategy or legal analysis, where its scores are higher
• care about UI and front-end quality
• need faster streaming on long outputs

Not sure? Use both. Splitting work by task is the most common approach, and it is easy to do in one workspace.

How to Test Both Models in 1min.AI

You do not need separate tools to settle the sol 6.1 vs opus 5.5 question. Both models are ready in one place:

1. Open Multi AI Chat in 1min.AI.
2. Select GPT-6.1 Sol and paste a real prompt from your work, such as a bug report, a contract clause or a feature spec.
3. Switch to Claude Opus 5.5 and send the identical prompt.
4. Compare accuracy, tone, speed and how much editing each answer needs.

Both models also work in Content Generator, Rewriter, Summarizer, Grammar Checker, Document Translator, Presentation Generator and Code Generator, so you can test them on the exact task you care about.

FAQs

Is GPT Sol better than Opus?

It depends on the job. Opus 5.5 scores higher on intelligence, coding and industry benchmarks. GPT-6.1 Sol completes each task at a much lower cost and is praised for debugging and review.

How much cheaper is GPT-6.1 Sol than Opus 5.5?

Its API rates are half ($2 / $10 vs $4 / $20 per 1M tokens). Per task at max effort, Sol averages $0.72 against $5.98 for Opus 5.5.

Which is better for coding, Opus 5.5 or GPT 6.1 Sol?

Opus 5.5 has the higher coding score (82.7 vs 71.0 on BenchLM) and is favored for architecture and UI. Sol is favored for debugging and code review.

Which model is faster?

Opus 5.5 generates text faster (96 vs 55 tokens per second at max effort). Sol returns its first token sooner at the same effort levels.

Can I use both models in one place?

Yes. In 1min.AI you can run the same prompt on both models in Multi AI Chat and compare the results.

Data sources: Artificial Analysis, BenchLM, official OpenAI and Anthropic model documentation, and community discussion on r/codex.