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GPT-6.1 Sol vs Gemini 4 Argon: API Cost Comparison

OpenAI's mid-tier workhorse against Google's new flagship while Argon's introductory pricing lasts.

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Updated 7 Nov 2026

GPT-6.1 Sol and Gemini 4 Argon pricing side by side
Side by side	GPT-6.1 Sol OpenAI	Gemini 4 Argon Google
Input / 1M	$2	$2
Output / 1M	$10	$10
Cached input / 1M	$0.10	$0.10
Batch discount	50% off	50% off
Context window	1.05M tokens	1.05M tokens
Long-prompt surcharge	Above 272K input	None
Tier	Mid-tier	Frontier

Workload

Requests per day

Avg input tokens

tok

Avg output tokens

tok

Cached input

Repeated system prompt or docs

Batched requests

Jobs that can wait hours

Models

Anthropic

OpenAI

Google

Mistral

DeepSeek

$ per 1M tokens, input / output

Monthly cost · 30 days

Cheapest: $2,100; GPT-6.1 Sol
Priciest: $2,100; Gemini 4 Argon
Spread: 1.0×; priciest vs cheapest

	Per request		Per 1K users / mo
GPT-6.1 Sol	$0.00700	$2,100	$1,050
Gemini 4 ArgonIntro price	$0.00700	$2,100	$1,050

Per 1K users assumesrequests per user per day.

Where the money is

Caching half your input on Gemini 4 Argon (a shared system prompt or document) would cut about $570/month.

You're looking at ~$2,100/month.

Most AI products I audit can cut that 30–60% with routing, caching and shorter prompts.

Get a cost-cutting audit

Cost at three traffic levels

Same request on both: 2,000 input tokens and 300 output tokens, no caching, no batch, 30-day month.

Monthly cost of GPT-6.1 Sol vs Gemini 4 Argon
Requests / day	GPT-6.1 Sol	Gemini 4 Argon	Difference
1,000	$210	$210	$0
10,000	$2,100	$2,100	$0
100,000	$21,000	$21,000	$0

By request type:

Cost per 1,000 calls by request type, GPT-6.1 Sol vs Gemini 4 Argon
Per 1K calls	GPT-6.1 Sol	Gemini 4 Argon
Classification or routing call	$0.9000	$0.9000
Support chat reply	$5.50	$5.50
RAG answer over your docs	$16.00	$16.00
Long document summary	$90.00	$90.00

When to pick which

Input tokens cost the same on both ($2 per 1M).
Output tokens cost the same on both ($10 per 1M).
Cache reads cost the same on both ($0.10 per 1M).
Both offer 50% off for batch processing.
GPT-6.1 Sol has the larger context window (1.05M tokens vs 1.05M tokens).
GPT-6.1 Sol bills the whole request at a higher rate once input passes 272,000 tokens.
Gemini 4 Argon's prices here are introductory until 30 Nov 2026; after that, input is $4 and output $20 per 1M.

GPT-6.1 Sol: General-purpose production workloads: chat, tools and RAG at a mid-tier price with cheap cache reads.

Gemini 4 Argon: Google's newest flagship. Large-context multimodal work, at an introductory price until the end of November 2026.

Verdict

It's a wash on price

On list price they are a wash for a typical request. Decide on quality for your task, latency, and which caching model fits your prompts. Then run both on 50 of your real prompts and compare answers and billed tokens side by side.

How the math works

Every provider bills input tokens (your prompt, system prompt and retrieved documents) and output tokens (the reply) separately, per million. Output is usually 4–5× the input price, so chatty apps are output-heavy and RAG apps are input-heavy.

cost per request = (fresh_in × input_price

+ cached_in × cached_price

+ out × output_price) / 1,000,000

× (1 − batched_share × batch_discount)

monthly = cost per request × requests per day × 30

Two adjustments are applied automatically. Introductory prices (currently on some Gemini models) are used until their end date. Long-prompt surcharges kick in when your average input crosses the provider's threshold: 272K tokens on current OpenAI models, 100K on Claude Haiku 5.5.

Not modelled: cache-write premiums, priority or fast tiers, regional surcharges, image and audio tokens, and reasoning tokens a model spends before answering (they bill as output, so add them to your output estimate if you use extended thinking).

Questions

Which is cheaper, GPT-6.1 Sol or Gemini 4 Argon?

For a typical request of 2,000 input and 300 output tokens they cost about the same: $0.00700 on GPT-6.1 Sol and $0.00700 on Gemini 4 Argon. Caching and output length decide which is cheaper for your workload.

Can I use both GPT-6.1 Sol and Gemini 4 Argon?

Yes, and many teams do. Put a thin routing layer in front of both: send the requests that need the stronger or larger-context model to it, and everything else to the cheaper one. Keep prompts provider-neutral so you can move traffic when prices change.

How often do OpenAI and Google change prices?

Often enough that a comparison older than a few months is suspect. The prices on this page were verified on 7 Nov 2026 from each provider's own documentation, linked in the Sources section.

Sources

All prices are list prices from each provider's own documentation, standard tier, in USD, last verified on 7 Nov 2026. Providers change prices often; if a number here disagrees with the source, the source wins.

GPT-6.1 Soldevelopers.openai.com
Gemini 4 Argonai.google.dev

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Fine print

Tools: on the house.
Engineer: by the hour.

Knowing your AI bill was free. Cutting it in half isn't, but I'm cheaper than the overspend.

I'm Himanshu, an AI and full-stack engineer. I build MVPs, AI agents and the growth plumbing around them for early-stage startups.

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