GPT-6 Sol and Luna Are Live: Half the Price, Cut the Same Day as Claude

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Key Takeaways

• Prices dropped again: gpt-6-sol is $2 input / $10 output and gpt-6-luna is $0.10 / $0.50 per 1M tokens, about half of the previous gpt-5.6-sol / gpt-5.6-luna. OpenAI says this is permanent pricing, not a limited-time promotion
• Clear division of labor: Sol is for everyday complex work such as building features, reviewing code, debugging and data analysis; Luna is for high-volume tasks such as summarization, extraction and simple Q&A
• Flagship-class specs: both have a 1.05M context window, 128K max output and six reasoning effort levels (none to max), defaulting to medium
• Live on APIYI: available in the default / svip / CodexResponses groups with all four billing items matching the provider; /v1/chat/completions and /v1/responses, including function calling, all passed our tests
• Same-day price cut as Claude: on the same day, Anthropic released Claude Opus 5.5 at a lower price. When both leading providers cut prices at once, developers and end users benefit most directly

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Background

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In Detail

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Which One to Use

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Benchmarks

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Technical Specs

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APIYI Endpoint Tests (23 September 2026)

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Using It

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Code Examples

from openai import OpenAI

client = OpenAI(api_key="YOUR_API_KEY", base_url="https://api.apiyi.com/v1")

response = client.chat.completions.create(
    model="gpt-6-sol",
    reasoning_effort="medium",   # none / low / medium / high / xhigh / max
    messages=[
        {"role": "user", "content": "Review this code, point out likely bugs and suggest fixes"}
    ]
)
print(response.choices[0].message.content)

from openai import OpenAI

client = OpenAI(api_key="YOUR_API_KEY", base_url="https://api.apiyi.com/v1")

response = client.responses.create(
    model="gpt-6-luna",
    reasoning={"effort": "low"},
    input="Summarize this support conversation in three bullet points: ...",
)
print(response.output_text)

curl https://api.apiyi.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-6-sol",
    "reasoning_effort": "medium",
    "messages": [{"role": "user", "content": "In one sentence, how do GPT-6 Sol and Luna differ?"}]
  }'

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Best Practices

• Migrating from 5.6 is a model-name change: gpt-5.6-sol → gpt-6-sol, gpt-5.6-luna → gpt-6-luna; request shapes on both endpoints stay the same
• Pick reasoning effort per task: the default is medium. Raise coding and agent work to high or xhigh; run Luna batch summarization and extraction at low or none for more speed and fewer reasoning tokens
• Use caching: cache reads cost a tenth of standard input. Put stable content such as system prompts and tool definitions at the start of the messages so every turn hits the cache
• Keep context under 272K where you can: above that, the whole request moves to a higher pricing tier (see the tier table below)

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Pricing and Availability

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Pricing

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Long-Context Tier

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Groups and Endpoints

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Stack with Top-Up Promotions

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Summary

1. gpt-5.6-sol / gpt-5.6-luna users: change the model name to roughly halve the cost; no code changes on either the Chat or Responses endpoint
2. Cost-sensitive batch work: Luna output is only $0.50 per 1M tokens; pair it with low reasoning effort and caching for large-scale summarization and extraction
3. Not sure which provider to use: on APIYI one key calls both GPT-6 and Claude, so run your own tasks through each and compare