API cost decision in 10 seconds

NewStep 3.7 Flash vs GPT-5.4 Nano

Pick Step 3.7 Flash for lower cost; pick GPT-5.4 Nano only if the larger context window matters more.

Page updated: 2026-05-29T00:07:14Z Data confirmed: 2026-05-31T01:07:53Z 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-5.4 Nano 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 $0.82 for GPT-5.4 Nano, saving $0.05 (6.1% lower).

Cost-first pickStep 3.7 Flash

Context-first pickGPT-5.4 Nano

Sample savings$0.056.1%

10x traffic gap$0.5

GPT-5.4 Nano has more context, but Step 3.7 Flash saves $0.05 on the standard workload. At 10x that traffic, the same price gap is about $0.5. 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	Step 3.7 Flash	GPT-5.4 Nano
Input-heavy / RAG	5M input + 500K output	Step 3.7 Flash	$1.57	$1.62
Balanced workload	1M input + 1M output	Step 3.7 Flash	$1.35	$1.45
Output-heavy chatbot	1M input + 5M output	Step 3.7 Flash	$5.95	$6.45

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 $1.15 vs $1.25 / 1M

Step 3.7 Flash is $0.1 cheaper per 1M output tokens (8% lower; 1.09x difference).

Larger context GPT-5.4 Nano 256K vs 400K

GPT-5.4 Nano has 144K more context (1.56x larger).

Sample workload Step 3.7 Flash $0.77 vs $0.82

Step 3.7 Flash is $0.05 cheaper on the standard workload (6.1% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

Step 3.7 Flash Calculating… Estimated API cost

GPT-5.4 Nano 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-5.4 Nano 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 $0.77 for Step 3.7 Flash and $0.82 for GPT-5.4 Nano.

Best Fit

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

Choose GPT-5.4 Nano when you care most about larger context window.

Decision Notes

On the standard 1M input plus 500K output workload, Step 3.7 Flash is estimated at $0.77 vs $0.82 for GPT-5.4 Nano, saving $0.05 (6.1% lower).
Step 3.7 Flash is $0.05 cheaper on the standard workload (6.1% lower).
Both models report the same input price at $0.2 per 1M tokens.
Step 3.7 Flash is $0.1 cheaper per 1M output tokens (8% lower; 1.09x difference).
GPT-5.4 Nano has 144K more context (1.56x larger).

Head-to-Head Specs

Feature	NewStep 3.7 Flash (StepFun)	GPT-5.4 Nano (OpenAI)
Input Price prompt tokens per 1M	$0.2	$0.2
Completion Price per 1M tokens	$1.15	$1.25
Sample Workload Cost 1M input + 500K output	$0.77	$0.82
Context Window	256K	400K
Release Date	2026-05-28	2026-03-17
Popularity	#37	#44

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 $0.82 for GPT-5.4 Nano, saving $0.05 (6.1% 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-5.4 Nano	A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps

Step 3.5 Flash can replace Step 3.7 Flash when lower sample workload cost matters most: $0.24.
gpt-oss-120b (free) can replace GPT-5.4 Nano when lower sample workload cost matters most: $0.
gpt-oss-20b (free) can replace GPT-5.4 Nano when lower sample workload cost matters most: $0.
gpt-oss-20b can replace GPT-5.4 Nano when lower sample workload cost matters most: $0.1.

Larger context near this budget

Llama 4 Scout offers 10M context with $0.23 sample workload cost.
Owl Alpha offers 1.05M context with $0 sample workload cost.
MiMo-V2.5 offers 1.05M context with $0.28 sample workload cost.
DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.

Popular competitors

Hy3 preview · Tencent · #1
MiMo-V2.5 · Xiaomi · #2
DeepSeek V4 Flash · DeepSeek · #3
Owl Alpha · OpenRouter · #4

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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StepFun catalog

Review all tracked StepFun 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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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...

GPT-5.4 Nano

GPT-5.4 nano is the most lightweight and cost-efficient variant of the GPT-5.4 family, optimized for speed-critical and high-volume tasks. It supports text and image inputs and is designed for low-latency...