API cost decision in 10 seconds

NewGemini 3.7 Flash (batch) vs GPT-5.6 Sol Pro

Pick Gemini 3.7 Flash (batch) for lower cost; pick GPT-5.6 Sol Pro only if the larger context window matters more.

Page updated: 2026-08-21T22:07:53Z Data confirmed: 2026-08-23T12:07:48Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Gemini 3.7 Flash (batch) for lower cost; pick GPT-5.6 Sol Pro only if the larger context window matters more.

On the standard 1M input plus 500K output workload, Gemini 3.7 Flash (batch) is estimated at $0.66 vs $7 for GPT-5.6 Sol Pro, saving $6.34 (90.6% lower).

Cost-first pickGemini 3.7 Flash (batch)

Context-first pickGPT-5.6 Sol Pro

Sample savings$6.3490.6%

10x traffic gap$63.44

GPT-5.6 Sol Pro has more context, but Gemini 3.7 Flash (batch) saves $6.34 on the standard workload. At 10x that traffic, the same price gap is about $63.44. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Gemini 3.7 Flash (batch) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shape	Token mix	Better pick	Gemini 3.7 Flash (batch)	GPT-5.6 Sol Pro
Input-heavy / RAG	5M input + 500K output	Gemini 3.7 Flash (batch)	$1.41	$15
Balanced workload	1M input + 1M output	Gemini 3.7 Flash (batch)	$1.12	$12
Output-heavy chatbot	1M input + 5M output	Gemini 3.7 Flash (batch)	$4.88	$52

Cheaper input Gemini 3.7 Flash (batch) $0.1875 vs $2 / 1M

Gemini 3.7 Flash (batch) is $1.81 cheaper per 1M input tokens (90.6% lower; 10.7x difference).

Cheaper output Gemini 3.7 Flash (batch) $0.9375 vs $10 / 1M

Gemini 3.7 Flash (batch) is $9.06 cheaper per 1M output tokens (90.6% lower; 10.7x difference).

Larger context GPT-5.6 Sol Pro 1.05M vs 1.05M

GPT-5.6 Sol Pro has 1.42K more context (1x larger).

Sample workload Gemini 3.7 Flash (batch) $0.66 vs $7

Gemini 3.7 Flash (batch) is $6.34 cheaper on the standard workload (90.6% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

Gemini 3.7 Flash (batch) Calculating… Estimated API cost

GPT-5.6 Sol Pro 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

Gemini 3.7 Flash (batch) has the lower input price; Gemini 3.7 Flash (batch) has the lower output price; GPT-5.6 Sol Pro offers the larger context window. For the 1M input plus 500K output sample, Gemini 3.7 Flash (batch) is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.66 for Gemini 3.7 Flash (batch) and $7 for GPT-5.6 Sol Pro.

Best Fit

Choose Gemini 3.7 Flash (batch) when you care most about lower input-token price, and lower output-token price.

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

Decision Notes

On the standard 1M input plus 500K output workload, Gemini 3.7 Flash (batch) is estimated at $0.66 vs $7 for GPT-5.6 Sol Pro, saving $6.34 (90.6% lower).
Gemini 3.7 Flash (batch) is $6.34 cheaper on the standard workload (90.6% lower).
Gemini 3.7 Flash (batch) is $1.81 cheaper per 1M input tokens (90.6% lower; 10.7x difference).
Gemini 3.7 Flash (batch) is $9.06 cheaper per 1M output tokens (90.6% lower; 10.7x difference).
GPT-5.6 Sol Pro has 1.42K more context (1x larger).

Head-to-Head Specs

Feature	NewGemini 3.7 Flash (batch) (Google)	GPT-5.6 Sol Pro (OpenAI)
Input Price prompt tokens per 1M	$0.1875	$2
Completion Price per 1M tokens	$0.9375	$10
Sample Workload Cost 1M input + 500K output	$0.66	$7
Context Window	1.05M	1.05M
Release Date	2026-08-13	2026-07-09

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Gemini 3.7 Flash (batch)	On the standard 1M input plus 500K output workload, Gemini 3.7 Flash (batch) is estimated at $0.66 vs $7 for GPT-5.6 Sol Pro, saving $6.34 (90.6% lower).
High-volume input processing	Gemini 3.7 Flash (batch)	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Gemini 3.7 Flash (batch)	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	GPT-5.6 Sol Pro	A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps

Gemma 4 26B A4B (free) can replace Gemini 3.7 Flash (batch) when lower sample workload cost matters most: $0.
Gemma 4 31B (free) can replace Gemini 3.7 Flash (batch) when lower sample workload cost matters most: $0.
Lyria 3 Pro Preview can replace Gemini 3.7 Flash (batch) when lower sample workload cost matters most: $0.
Lyria 3 Clip Preview can replace Gemini 3.7 Flash (batch) when lower sample workload cost matters most: $0.

Larger context near this budget

Grok 4.20 Multi-Agent offers 2M context with $2.5 sample workload cost.
Grok 4.20 offers 2M context with $2.5 sample workload cost.
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.

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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Google catalog

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OpenAI catalog

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

Open OpenAI models

Gemini 3.7 Flash (batch)

Gemini 3.7 Flash is a multimodal model from Google for fast agentic workflows, coding, and complex multi-step reasoning. It is designed for tasks that require responsive performance and reliable multi-step...

GPT-5.6 Sol Pro

GPT-5.6 Sol Pro is the same underlying model as [GPT-5.6 Sol](https://openrouter.ai/openai/gpt-5.6-sol), 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