API cost decision in 10 seconds

🔥GPT-5.6 Luna vs Step 3.7 Flash

Pick Step 3.7 Flash for lower cost; pick GPT-5.6 Luna only if the larger context window matters more.

Page updated: 2026-08-17T15:08:04Z Data confirmed: 2026-08-23T11:07:50Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Step 3.7 Flash for lower cost; pick GPT-5.6 Luna only if the larger context window matters more.

On the standard 1M input plus 500K output workload, Step 3.7 Flash is estimated at $0.77 vs $0.8 for GPT-5.6 Luna, saving $0.03 (3.1% lower).

Cost-first pickStep 3.7 Flash

Context-first pickGPT-5.6 Luna

Sample savings$0.033.1%

10x traffic gap$0.25

GPT-5.6 Luna has more context, but Step 3.7 Flash saves $0.03 on the standard workload. At 10x that traffic, the same price gap is about $0.25. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Step 3.7 Flash stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shape	Token mix	Better pick	GPT-5.6 Luna	Step 3.7 Flash
Input-heavy / RAG	5M input + 500K output	Step 3.7 Flash	$1.6	$1.57
Balanced workload	1M input + 1M output	Step 3.7 Flash	$1.4	$1.35
Output-heavy chatbot	1M input + 5M output	Step 3.7 Flash	$6.2	$5.95

Cheaper input Tie $0.2 vs $0.2 / 1M

Both models report the same input price at $0.2 per 1M tokens.

Cheaper output Step 3.7 Flash $1.2 vs $1.15 / 1M

Step 3.7 Flash is $0.05 cheaper per 1M output tokens (4.2% lower; 1.04x difference).

Larger context GPT-5.6 Luna 1.05M vs 262.14K

GPT-5.6 Luna has 787.86K more context (4.01x larger).

Sample workload Step 3.7 Flash $0.8 vs $0.77

Step 3.7 Flash is $0.03 cheaper on the standard workload (3.1% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

GPT-5.6 Luna Calculating… Estimated API cost

Step 3.7 Flash 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

both models tie on input price; Step 3.7 Flash has the lower output price; GPT-5.6 Luna offers the larger context window. For the 1M input plus 500K output sample, Step 3.7 Flash is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.8 for GPT-5.6 Luna and $0.77 for Step 3.7 Flash.

Best Fit

Choose GPT-5.6 Luna when you care most about larger context window.

Choose Step 3.7 Flash when you care most about lower output-token price.

Decision Notes

On the standard 1M input plus 500K output workload, Step 3.7 Flash is estimated at $0.77 vs $0.8 for GPT-5.6 Luna, saving $0.03 (3.1% lower).
Step 3.7 Flash is $0.03 cheaper on the standard workload (3.1% lower).
Both models report the same input price at $0.2 per 1M tokens.
Step 3.7 Flash is $0.05 cheaper per 1M output tokens (4.2% lower; 1.04x difference).
GPT-5.6 Luna has 787.86K more context (4.01x larger).

Head-to-Head Specs

Feature	🔥GPT-5.6 Luna (OpenAI)	Step 3.7 Flash (StepFun)
Input Price prompt tokens per 1M	$0.2	$0.2
Completion Price per 1M tokens	$1.2	$1.15
Sample Workload Cost 1M input + 500K output	$0.8	$0.77
Context Window	1.05M	262.14K
Release Date	2026-07-09	2026-05-28
Popularity	#6

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Step 3.7 Flash	On the standard 1M input plus 500K output workload, Step 3.7 Flash is estimated at $0.77 vs $0.8 for GPT-5.6 Luna, saving $0.03 (3.1% lower).
High-volume input processing	Tie	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Step 3.7 Flash	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	GPT-5.6 Luna	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 when lower sample workload cost matters most: $0.
gpt-oss-20b (free) can replace GPT-5.6 Luna when lower sample workload cost matters most: $0.
gpt-oss-20b can replace GPT-5.6 Luna when lower sample workload cost matters most: $0.1.
gpt-oss-120b can replace GPT-5.6 Luna when lower sample workload cost matters most: $0.12.

Larger context near this budget

DeepSeek V4 Flash 0731 offers 1.31M context with $0.17 sample workload cost.
DeepSeek V4 Flash Latest offers 1.31M context with $0.11 sample workload cost.
Llama 4 Scout offers 1.31M context with $0.25 sample workload cost.

Popular competitors

DeepSeek V4 Flash 0731 · DeepSeek · #1
MiMo-V2.5 · Xiaomi · #2
Hy3 · Tencent · #3
Ox Alpha · stealth · #4

Cheaper alternatives

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Larger context alternatives

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Provider catalogs

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OpenAI catalog

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StepFun catalog

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

Open StepFun models

GPT-5.6 Luna

GPT-5.6 Luna is a fast, cost-efficient model in OpenAI's GPT-5.6 series. It is suited for high-volume, latency-sensitive tasks such as chat, classification, and lightweight agentic workflows, providing capable reasoning for...

Step 3.7 Flash

Step 3.7 Flash is StepFun's latest high-efficiency multimodal Mixture-of-Experts model. It pairs a 196B-parameter language backbone with a vision encoder for native image and video understanding, activating roughly 11B parameters...