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GPT-6.1 Sol on 59API: rates, setup, API relay guide

The problem: you want GPT-6.1 Sol without wrestling with billing

Here is the situation most busy developers end up in. You want to run a strong GPT model in your own tooling, but the accounting gets in the way before the code does. You look at list prices, you try to forecast usage, and you wonder whether a burst of experiments is going to cost more than you planned. Multiply that by the models you actually touch during a week and the admin work starts to eat the fun parts of building.

59API exists to remove that friction. It is an independent third-party AI API relay: one account, one API key, and one API host at https://api.59api.com for GPT, Claude, Gemini, DeepSeek and other models. You keep a prepaid balance, and each request is charged by real token usage. There is no monthly fee, and the balance never expires, so a quiet month costs you nothing extra. Monthly and weekly cards exist as an option, not an obligation.

That model of billing is a good fit for anyone who ships in bursts. You top up, you test, you deploy, and you only pay for what you actually consumed. This article focuses on one model in particular, GPT-6.1 Sol, and walks through what it costs on 59API, how to point your client at the host, and the situations where reaching for it makes sense.

GPT-6.1 Sol rates on 59API

Let us get straight to the numbers. On 59API, the model id is gpt-6.1-sol, and prices are quoted per 1 million tokens. Billing is in CNY, with USD figures shown at the rate of ¥7.2 = $1. For GPT-6.1 Sol, input costs $0.1847 (¥1.33), output costs $0.9264 (¥6.67), and cache read costs $0.0375 (¥0.27). The official list price for reference is $2 / $10.

That cache read rate deserves a second look. If your workload reuses long system prompts or repeated context across calls, cache reads are billed at a fraction of fresh input, so the effective cost of a repeated prompt drops quickly. It is the kind of detail that matters once you move past a demo and into a loop that runs all day.

For context, it helps to know where GPT-6.1 Sol sits among its siblings. GPT-5.6 Sol, model id gpt-5.6-sol, is $0.3472 (¥2.5) input and $1.94 (¥14) output. GPT-6 Astra, model id gpt-6-astra, is $0.6944 (¥5) input and $3.47 (¥25) output. GPT-6.1 Sol lands below both on input and output, which is exactly what makes it interesting for volume work. You are not choosing between capability tiers so much as deciding where to spend your budget across a pipeline.

A worked example: what a real batch costs

Numbers on a rate card are useful, but a concrete run is easier to reason about. Consider a hypothetical job that pushes 5M input tokens and 1M output tokens through gpt-6.1-sol with no cache involved. On 59API that run comes to $1.85 (¥13.32). At official list price the same usage works out to $20 (about ¥144). In other words, 59API comes to about 9% of list price for this pattern.

Now scale that pattern mentally. A nightly batch, a CI step that summarizes diffs, a support tool that drafts replies, a research loop that reads long documents and writes short notes: these all share the same shape, heavy input with comparatively light output. That is the shape where GPT-6.1 Sol's input rate does the most work for you, because input is the cheaper side of the ledger and it is the side these jobs spend most of their tokens on.

It is worth comparing against a sibling to see the trade. A hypothetical run of 2M input and 0.5M output on GPT-5.6 Sol costs $1.67 (¥12) on 59API against $25 (about ¥180) at official list price, about 7% of list price. Both are strong values; the choice comes down to which model suits the task. The point of prepaid, per-token billing on 59API is that you can make that call per job rather than committing up front.

Setup: point your client at the 59API host

Connecting GPT-6.1 Sol is a two-line change if you already use an OpenAI-compatible client. Codex, OpenAI SDKs, cURL, and OpenAI-compatible clients such as Cursor, Cherry Studio, Cline and OpenCode all work with GPT, DeepSeek and other non-Claude, non-Gemini models. Set your base URL to https://api.59api.com/v1 and send chat requests to the endpoint https://api.59api.com/v1/chat/completions. Authenticate with your 59API key, written here as YOUR_59API_KEY.

Then just pass the model id. In your request body, set the model to gpt-6.1-sol and you are done. The same key and the same host cover the rest of the catalog, so switching a job from GPT-6.1 Sol to GPT-6 Astra or DeepSeek V4 Pro is a one-field change rather than a new integration.

One boundary is worth stating plainly, because it saves support tickets later. Claude models work only through the genuine Claude Code or Claude Desktop client, version 2.1.285 or newer, and never through the OpenAI SDK, cURL or other clients. Gemini models use Google's native protocol only and are not OpenAI-compatible, so they do not run on /v1/chat/completions. Keep those two families in their own lanes and everything else in the OpenAI-compatible lane behaves predictably.

When GPT-6.1 Sol is the right call

So when should you reach for gpt-6.1-sol? Think in terms of workload shape. If you are running long-context tasks where the input dominates, the input rate of $0.1847 (¥1.33) per 1 million tokens keeps unit economics comfortable even at high volume. If you are building something that repeats context, the cache read rate of $0.0375 (¥0.27) rewards that pattern directly. And if you want a model that sits in the middle of the GPT lineup without pushing you into the higher input and output rates of GPT-6 Astra, this is the one to benchmark first.

It is also a reasonable default for prototyping across a team. Because 59API charges per request by real token usage and the balance never expires, two engineers can spike on an idea on Monday, shelve it for a month, and pick it up again without the meter running in between. Top-ups are flexible too: ¥10, ¥50, ¥100, ¥200, ¥500 and ¥1000, paid by WeChat Pay or bank card, with invoices available when finance asks.

If your usage turns out to be heavy and predictable, optional cards are worth a look. A GPT card such as G-PRO Starter (入门版) runs 30 days for $83.19 (¥599) with a $3250 quota and a $1250 weekly cap, draining at official price times 2.4, which works out to about $1354.17 of usage at official list prices. A card has its own key, only calls that family's models, and is paid only from the card, so it never falls back to wallet balance and a balance key never draws on a card. Unused quota does not roll over, and quota and caps are stated in official-price USD.

What to do next

Getting started takes about as long as reading this far. Create your 59API account, top up whatever amount matches your current experiment, and grab a key. Point your client at https://api.59api.com/v1, send a chat completion to https://api.59api.com/v1/chat/completions with gpt-6.1-sol as the model, and watch the first response come back. Then run your real workload once and check the token accounting against the rates above.

What you will notice is that the mental overhead disappears. There is one host to remember, one key to rotate, and one balance to watch. Because 59API is a relay covering GPT, Claude, Gemini, DeepSeek and other models, the same setup carries you into the rest of the catalog when a project needs a different flavor, whether that is GPT-5.6 Sol for a lighter job or DeepSeek V4 Flash for a lighter-tier option in the lineup.

If the run you just did looks like your normal traffic, you have your answer on GPT-6.1 Sol. If it looks like a one-off, nothing is lost, since the balance sits there until you need it. Either way you spent real tokens on a real task and found out exactly what it costs, which is the whole point. Try gpt-6.1-sol on 59API on your next build and see how the numbers land for your own workload.

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