Claude Sonnet 5.5 vs GPT-6.1 Sol: Which Should You Pick?

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Claude Sonnet 5.5 and GPT-6.1 Sol launched one day apart at identical list prices. Here is where each one wins on quality, cost, and speed.

Claude Sonnet 5.5 is the stronger model when you pay for maximum effort, and GPT-6.1 Sol is the cheaper model almost everywhere else. Anthropic released Sonnet 5.5 on September 28, 2026. OpenAI followed with GPT-6.1 Sol one day later, Artificial Analysis reports.

Both models list at $2 per million input tokens and $10 per million output tokens. That makes the choice about workload, not sticker price. For anyone who builds software with AI, including the non-technical founders and operators who use Emergent, the real questions are what a finished task costs and how often it works.

This Claude Sonnet 5.5 vs GPT-6.1 Sol comparison uses both makers' announcements, their API documentation, and independent testing from Artificial Analysis. When a number comes from a maker's own testing, we say so.

What are Claude Sonnet 5.5 and GPT-6.1 Sol?

Claude Sonnet 5.5 is Anthropic's faster, lower-cost model for everyday coding, documents, slides, and spreadsheets. GPT-6.1 Sol is OpenAI's balanced model for complex coding, computer use, and professional work. Each sits one step below its maker's top model, and both list at $2 and $10 per million tokens.

Anthropic calls Sonnet 5.5 a faster, lower-cost complement to Claude Opus 5.5. Its announcement says the model runs more than 30% faster than Sonnet 5 and costs up to 30% less for most work.

OpenAI says GPT-6.1 Sol nearly matches its flagship, GPT-6 Astra, on agentic coding, computer use, and professional work. It charges one-fifth of Astra's price to do so, according to OpenAI’s announcement.

Claude Sonnet 5.5 vs GPT-6.1 Sol at a glance

The specs differ in small ways. The behavior differs in large ones.

Pricing and specifications as of October 2026. Sources: Anthropic and OpenAI announcements, Claude Platform comparison page, and OpenRouter’s comparison page.

Which model scores higher?

Sonnet 5.5 scores higher overall, but it leads only at the top effort settings. Artificial Analysis, an independent benchmarking firm, runs both models through the same 10-test suite. At max effort, its Intelligence Index gives Sonnet 5.5 a 56 and GPT-6.1 Sol a 52.

Scores at max effort. Higher is better. Source: Artificial Analysis comparison page.

Sonnet 5.5 leads six of the 10 tests, GPT-6.1 Sol leads two, and two are effectively tied. Each tied pair sits within 0.3 points.

1. Coding and agents

Sonnet 5.5 leads Terminal-Bench 4.0 (63.6% vs 56.1%) and AutomationBench-AA (71.8% vs 64.9%) in Artificial Analysis's runs. Anthropic reports a higher Terminal-Bench 4.0 score of 70.6% from its own setup. Same test, different harness, different number, so compare scores only within one source.

Each maker also publishes claims against older models. Anthropic says Sonnet 5.5 at High effort matches GPT-6 Sol's best FrontierCode score for about one-fifth of the cost per task. OpenAI says GPT-6.1 Sol matches its flagship on DeepSWE v1.1 at about one-fifth of the flagship's cost. We found no maker-published test that pits the two models against each other.

For a real-world signal, DataCamp ran a hands-on test in which both models built a Dijkstra visualizer. GPT-6.1 Sol refused a graph with a negative edge weight, while Sonnet 5.5 warned and still answered. Sonnet 5.5 finished faster and in fewer turns. Treat one test as an anecdote, not a verdict.

2. Knowledge work and documents

Sonnet 5.5 leads GDPval-AA (1840 vs 1575) and AA-Briefcase (1824 vs 1564), two tests of real professional work. Anthropic says the model is strongest at polished documents, slides, and spreadsheets, and it scores two points below Opus 5.5 on GDPval-AA. GPT-6.1 Sol wins GDP.pdf, 31.0% to 25.8%.

3. Factual reliability

GPT-6.1 Sol scores 42 on AA-Omniscience, against 32 for Sonnet 5.5 at max effort. The gap widens below max. Sonnet 5.5 scores 19 to 21 from low through high effort, while GPT-6.1 Sol holds between 38 and 41. For fact-heavy work, verify either model's output.

4. Long context

On AA-LCR v1.1, the two models are tied: 82.7% for Sonnet 5.5 and 83.0% for GPT-6.1 Sol. Both offer a window of about one million tokens. The real difference is price, which we cover next.

What these numbers cannot tell you

Benchmarks are a starting point, and three limits apply here. Each one can change which model wins for you.

First, neither model is the ceiling. Anthropic says Claude Opus 5.5 remains clearly stronger than Sonnet 5.5 at complex, open-ended work that needs sustained judgment. OpenAI says GPT-6 Astra still posts the top Terminal-Bench Science score (68.1%) and recommends it for the hardest research tasks.

Second, test conditions shift the numbers. Anthropic notes that Artificial Analysis ran GDPval-AA and AA-Briefcase on a pre-release Sonnet 5.5 deployment with a bug that could have understated its scores. Anthropic says the bug has been fixed and expects any effect to be small. Check Artificial Analysis for refreshed figures before you publish or buy.

Third, public tests are not your prompts. A model that wins on average can still lose on your task. That is why the test plan later in this guide matters more than any table above.

For the wider field, read our GPT-6.1 Sol alternatives guide.

Which model delivers better benchmark performance per dollar?

GPT-6.1 Sol delivers better benchmark performance per dollar at every effort setting, while Sonnet 5.5 achieves the higher peak Intelligence Index score. Artificial Analysis measures cost per task, which blends token prices with how many tokens a model uses. That makes it a better guide than list price.

Intelligence Index and weighted average cost per index task. Sonnet 5.5 results use its default fallback setting. Source: Artificial Analysis.

At low, medium, and high effort, GPT-6.1 Sol scores three to seven points higher and costs about one-third as much. At xhigh, Sonnet 5.5 edges ahead by one point and costs about seven times more. At max, it leads by four points and costs about 11 times more.

Anthropic's own charts make a different point. Sonnet 5.5 at Low or Medium effort beats Sonnet 5's best score for about a tenth of the cost per task on several benchmarks. That compares the model with its predecessor, not with GPT-6.1 Sol.

The takeaway is simple. If a four-point lead matters for your task, Sonnet 5.5 at max effort buys it. If it does not, GPT-6.1 Sol delivers close to the same quality for a fraction of the price.

Claude Sonnet 5.5 pricing vs GPT-6.1 Sol pricing

The list prices match, and two details separate them.

Pricing as of October 2026. Standard API rates. Sources: Anthropic and OPENAI official documentation.

The first difference is caching. Cached input is text the model already processed in an earlier request, such as a project brief or codebase. Take an agent that reuses a 200,000-token context across 50 requests, which is 10 million cached tokens. For example, 10 million cached input tokens would cost $2.00 with Sonnet 5.5 and $1.00 with GPT-6.1 Sol, based on the vendors' published cache-read rates. This is an illustrative calculation rather than a quoted vendor example.

The second difference is long prompts. Sonnet 5.5 maintains its standard per-token pricing across its 1-million-token context window, while GPT-6.1 Sol applies higher rates above 272,000 input tokens, according to the respective vendors' pricing documentation. Check the latest provider pricing before budgeting for long-context workloads.

Per-token price is only half of the cost. Anthropic notes that Sonnet 5.5 costs the same per token as Sonnet 5 but typically needs far fewer tokens for the same work. Cost per task captures both effects.

Which model is faster?

Sonnet 5.5 streams text faster, but the faster streamer does not always finish the task first. At max effort, Artificial Analysis measures 132 output tokens per second for Sonnet 5.5 and 51 for GPT-6.1 Sol. OpenRouter's median figures agree in direction: 96.0 against 49.0 tokens per second.

Latency is the wait before the first token appears. OpenRouter's median latency is 1.98 seconds for Sonnet 5.5 and 6.07 seconds for GPT-6.1 Sol. For chat-style products, that gap is easy to feel.

Speed per token is not speed per task. On Artificial Analysis's time-per-task measure, Sonnet 5.5 finishes sooner at medium and high effort, and GPT-6.1 Sol finishes sooner at low and max. At max effort, the time-per-task figures are 932 seconds for Sonnet 5.5 and 756 seconds for GPT-6.1 Sol, because Sonnet 5.5 works through more tokens at that setting. OpenAI has also said a faster GPT -6.1 Sol Ultrafast tier is coming, so the gap may narrow.

For the GPT side of the cost question in full, read our GPT-6.1 Sol pricing guide.

What changes in your code when you switch

Moving between these models means different settings in each direction. Neither swap is a one-line change.

1. Thinking controls

If you run Sonnet with thinking off, Anthropic says you must switch to the new between_tools setting before moving to Sonnet 5.5. Its migration guide has the details.

GPT-6.1 Sol has the opposite quirk: it always reasons. OpenAI's model page says the none and minimal settings are not supported, so use low instead.

2. Tools and platforms

Tool calling on GPT-6.1 Sol requires OpenAI's Responses API. Chat Completions still works, but without tools, per OpenAI’s migration guidance..

Anthropic lists Sonnet 5.5 on the Claude Platform, Amazon Web Services, Google Cloud, and Microsoft Azure. OpenAI lists GPT-6.1 Sol in the OpenAI API, ChatGPT Work, and Codex.

3. Safeguards and knowledge dates

Sonnet 5.5 is the first Sonnet model with cyber safeguards. Higher-risk security tasks visibly fall back to Sonnet 5, while routine bug fixing is unaffected, according to Anthropic.

The Claude Platform docs list a June 2026 knowledge cutoff for Sonnet 5.5. OpenAI's model page lists April 30, 2026 for GPT-6.1 Sol. Pair either model with search for newer facts.

Which model should you choose?

Choose by workload shape, not by headline score. This table maps common jobs to a starting point.

A reasonable default: start cost-sensitive work on GPT-6.1 Sol at medium or high effort. Move to Sonnet 5.5 where speed, polish, or peak quality justify the extra cost.

What this means if you build apps with AI

Cost per finished task matters more than price per token. Many builders never call a model API themselves, yet they still feel these trade-offs as builds that cost more, run slower, or fail more often.

A platform such as Emergent, where Claude Sonnet 5.5 is available as a model option, uses a multi-agent architecture to produce full-stack apps with backends, databases, auth, and deployment. Your job is to judge the result: does the app work, and what did it cost to get there?

Suggested read: Claude Sonnet 5.5 pricing.

A one-afternoon test plan

Benchmarks cannot see your prompts. Run this plan to decide with your own data.

• Choose 20 tasks from real work, mixing easy and hard ones.
• Run every task on both models at medium and high effort.
• Score each result as pass or fail, using the same person and checklist for both models.
• Record cost and time per task from the API usage data.
• Add one long-context job and one cached agent loop, since pricing differs most there.
• Compare cost per passed task, not cost per run.

If your numbers disagree with a leaderboard, trust your numbers.

Match the model to the job, then test it

The Claude Sonnet 5.5 vs GPT-6.1 Sol decision comes down to effort level, budget, and the shape of your work. Sonnet 5.5 earns its premium at max effort, in fast interactive use, and on very long uncached prompts. GPT-6.1 Sol earns its place on cost, caching, and factual reliability.

Start small. Pick one workload, run it on both models, and compare cost per passed task. Fix the thinking settings and tool-calling path first, because those changes break code.

If you would rather describe the business you want to run than compare models, start building on Emergent.