API cost decision in 10 seconds

Solar Pro 4 vs GPT-5.6 Luna Pro (batch)

Pick Solar Pro 4 for lower cost; pick GPT-5.6 Luna Pro (batch) only if the larger context window matters more.

Page updated:  Data confirmed:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Solar Pro 4 for lower cost; pick GPT-5.6 Luna Pro (batch) only if the larger context window matters more.

On the standard 1M input plus 500K output workload, Solar Pro 4 is estimated at $0.09 vs $0.4 for GPT-5.6 Luna Pro (batch), saving $0.31 (77.5% lower).

Cost-first pickSolar Pro 4
Context-first pickGPT-5.6 Luna Pro (batch)
Sample savings$0.3177.5%
10x traffic gap$3.1

GPT-5.6 Luna Pro (batch) has more context, but Solar Pro 4 saves $0.31 on the standard workload. At 10x that traffic, the same price gap is about $3.1. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Solar Pro 4 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickSolar Pro 4GPT-5.6 Luna Pro (batch)
Input-heavy / RAG5M input + 500K outputSolar Pro 4$0.21$0.8
Balanced workload1M input + 1M outputSolar Pro 4$0.15$0.7
Output-heavy chatbot1M input + 5M outputSolar Pro 4$0.63$3.1
Cheaper input Solar Pro 4 $0.03 vs $0.1 / 1M

Solar Pro 4 is $0.07 cheaper per 1M input tokens (70% lower; 3.33x difference).

Cheaper output Solar Pro 4 $0.12 vs $0.6 / 1M

Solar Pro 4 is $0.48 cheaper per 1M output tokens (80% lower; 5x difference).

Larger context GPT-5.6 Luna Pro (batch) 524.29K vs 1.05M

GPT-5.6 Luna Pro (batch) has 525.71K more context (2x larger).

Sample workload Solar Pro 4 $0.09 vs $0.4

Solar Pro 4 is $0.31 cheaper on the standard workload (77.5% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Solar Pro 4 Calculating… Estimated API cost
GPT-5.6 Luna Pro (batch) Calculating… Estimated API cost
Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

Solar Pro 4 has the lower input price; Solar Pro 4 has the lower output price; GPT-5.6 Luna Pro (batch) offers the larger context window. For the 1M input plus 500K output sample, Solar Pro 4 is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.09 for Solar Pro 4 and $0.4 for GPT-5.6 Luna Pro (batch).

Best Fit

Choose Solar Pro 4 when you care most about lower input-token price, and lower output-token price.

Choose GPT-5.6 Luna Pro (batch) when you care most about larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, Solar Pro 4 is estimated at $0.09 vs $0.4 for GPT-5.6 Luna Pro (batch), saving $0.31 (77.5% lower).
  • Solar Pro 4 is $0.31 cheaper on the standard workload (77.5% lower).
  • Solar Pro 4 is $0.07 cheaper per 1M input tokens (70% lower; 3.33x difference).
  • Solar Pro 4 is $0.48 cheaper per 1M output tokens (80% lower; 5x difference).
  • GPT-5.6 Luna Pro (batch) has 525.71K more context (2x larger).
Head-to-Head Specs
FeatureSolar Pro 4
(Upstage)		GPT-5.6 Luna Pro (batch)
(OpenAI)
Input Price
prompt tokens per 1M		$0.03$0.1
Completion Price
per 1M tokens		$0.12$0.6
Sample Workload Cost
1M input + 500K output		$0.09$0.4
Context Window524.29K1.05M
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionSolar Pro 4On the standard 1M input plus 500K output workload, Solar Pro 4 is estimated at $0.09 vs $0.4 for GPT-5.6 Luna Pro (batch), saving $0.31 (77.5% lower).
High-volume input processingSolar Pro 4Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsSolar Pro 4Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workGPT-5.6 Luna Pro (batch)A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps
  • gpt-oss-120b (free) can replace GPT-5.6 Luna Pro (batch) when lower sample workload cost matters most: $0.
  • gpt-oss-20b (free) can replace GPT-5.6 Luna Pro (batch) when lower sample workload cost matters most: $0.
  • gpt-oss-20b can replace GPT-5.6 Luna Pro (batch) when lower sample workload cost matters most: $0.1.
  • gpt-oss-120b can replace GPT-5.6 Luna Pro (batch) when lower sample workload cost matters most: $0.12.

Cheaper alternatives

Review low-cost models sorted by a standard 1M input plus 500K output workload.

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Larger context alternatives

Find models with larger context windows for RAG, long documents, and codebase review.

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Provider catalogs

Compare models within provider hubs before choosing a final API vendor.

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Upstage catalog

Review all tracked Upstage models before deciding whether this matchup is the right shortlist.

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OpenAI catalog

Check other OpenAI models with comparable pricing, context, or release timing.

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Solar Pro 4

Solar Pro 4 is Upstage's cost-efficient large language model, featuring a 524K context window. It is built for long-horizon tasks and agentic workflows, with strong capabilities in office productivity, document-intensive...

GPT-5.6 Luna Pro (batch)

GPT-5.6 Luna Pro is the same underlying model as [GPT-5.6 Luna](https://openrouter.ai/openai/gpt-5.6-luna), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode