GPT-5.6 Sol or Claude Sonnet 5? Same price on Zukko, how to choose

GPT-5.6 Sol or Claude Sonnet 5: on Zukko both models cost the same, $0.30 per 1M input and $0.30 per 1M output tokens. Both can be called in either OpenAI or Anthropic format; the gateway converts requests. So the choice comes down to one question: which model handles your tasks better. Below are reference prices, code for both formats and a comparison method.

Prices: official and on Zukko

Example: 10M input and 2M output tokens a month (volumes in millions, prices per 1M).

At the vendors, the difference between the models at this volume would be $110 − $40 = $70. On Zukko there is none. The final bill can still differ if one model consistently writes longer answers and spends more output tokens.

For agents with a large repeated context, keep the caveat in mind: at the vendors, prompt cache reads cost about 10% of the input price, while Zukko bills cached tokens at the regular input price. In such scenarios the real difference from the official API is smaller than the calculation above.

The API format is not tied to the model

A common misconception: "GPT means the OpenAI SDK, Claude means the Anthropic SDK". On Zukko any model can be called in any format. Choose the format by your stack and the model by test results.

OpenAI SDK: both models through one client:

from openai import OpenAI

client = OpenAI(
    base_url="https://api.zukko.pro/v1",
    api_key="fetch_your_key",
)

for model in ["gpt-5.6-sol", "claude-sonnet-5"]:
    r = client.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": "Explain idempotency in two sentences"}],
    )
    print(model, "→", r.choices[0].message.content)

Anthropic SDK: also both models (address without /v1; the SDK adds it):

import anthropic

client = anthropic.Anthropic(
    base_url="https://api.zukko.pro",
    api_key="fetch_your_key",
)

for model in ["claude-sonnet-5", "gpt-5.6-sol"]:
    r = client.messages.create(
        model=model,
        max_tokens=1024,
        messages=[{"role": "user", "content": "Explain idempotency in two sentences"}],
    )
    print(model, "→", "".join(b.text for b in r.content if b.type == "text"))

More on format differences: Anthropic or OpenAI format↗.

Environment variables for tools

Tools built on the OpenAI SDK (Cursor, Cline, Kilo Code, LangChain and others) are configured like this:

export OPENAI_BASE_URL=https://api.zukko.pro/v1
export OPENAI_API_KEY=fetch_your_key

Claude Code works in Anthropic format:

export ANTHROPIC_BASE_URL=https://api.zukko.pro
export ANTHROPIC_AUTH_TOKEN=fetch_your_key
export ANTHROPIC_MODEL=claude-sonnet-5

In both cases the model is set separately, in the tool's settings or in code. To change it without editing code, add your own variable:

import os
from openai import OpenAI

client = OpenAI(base_url="https://api.zukko.pro/v1", api_key=os.environ["OPENAI_API_KEY"])
MODEL = os.getenv("LLM_MODEL", "claude-sonnet-5")

Changing LLM_MODEL=claude-sonnet-5 to LLM_MODEL=gpt-5.6-sol in .env switches the model; no SDK rewrite needed.

How to compare the models on your tasks

We do not publish our own quality or speed measurements, so we will not claim that one model is "better at code" or "faster". Test it yourself:

1. Collect 20–30 real tasks, including hard ones.
2. Define a success criterion: a reference answer, tests, valid JSON or a checklist.
3. Run both models with the same prompt.
4. Grade blind: shuffle the answers and hide the model name.
5. Compare pass rate, output tokens per answer and median response time.

A run of 30 tasks × 2 models at 1,000 input and 1,000 output tokens costs: 60 × 2,000 × $0.30 / 1,000,000 = $0.036.

Checklist for coding tasks

Give one point per item (6 max) and compare the models' average score on the same task set. The first two items are best checked automatically, by running the code and the tests.

Error handling is the same

Gateway error codes do not depend on the model or the format: 401 invalid key, 402 insufficient balance, 403 model not allowed for the key, 429 too many requests, 503 provider unavailable. The official SDKs retry by default (up to two times) on connection errors, 408, 409, 429 and 5xx responses.

import openai

try:
    r = client.chat.completions.create(model=MODEL, messages=[{"role": "user", "content": "..."}])
except openai.AuthenticationError:
    print("Invalid key")
except openai.APIStatusError as e:
    if e.status_code == 402:
        print("Insufficient balance")
    elif e.status_code == 403:
        print("Model not allowed for this key")
    else:
        raise

The Anthropic SDK has the same structure: anthropic.AuthenticationError and anthropic.APIStatusError with a status_code field.

Context

Both models have a 1M-token context, so there is no difference here. You can find out how much your prompt takes in advance with count_tokens↗. The model set changes: the current list is at GET https://api.zukko.pro/v1/models or on the "Models" page in the dashboard. To run the comparison, create a key in the dashboard↗.

FAQ

Which model is better?

There is no general answer; test on your tasks using the method above. With 20–30 tasks and blind grading it usually becomes clear whether there is a difference for you.

I use Claude Code. Which model will it use?

The one you set in ANTHROPIC_MODEL or pick inside Claude Code. Details are in the Claude Code guide↗.

Is it hard to move from Sol to Sonnet or back?

Not via Zukko: the SDK and address stay the same, only the model string changes. Before switching in production, run your test set on the new model.

Is there a price difference?

Not on Zukko: both are $0.30 / $0.30. Only the final bill can differ if the models spend different numbers of output tokens on your tasks.