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Mistral Large 4 vs GPT-6.1 Sol: API Cost Comparison

An open-weight 1M-context model against OpenAI's mid-tier default.

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Updated 7 Nov 2026

Mistral Large 4 and GPT-6.1 Sol pricing side by side
Side by side	Mistral Large 4 Mistral	GPT-6.1 Sol OpenAI
Input / 1M	$0.70	$2
Output / 1M	$2.10	$10
Cached input / 1M	$0.07	$0.10
Batch discount	50% off	50% off
Context window	1M tokens	1.05M tokens
Long-prompt surcharge	None	Above 272K input
Tier	Mid-tier	Mid-tier

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: $609; Mistral Large 4
Priciest: $2,100; GPT-6.1 Sol
Spread: 3.4×; priciest vs cheapest

	Per request		Per 1K users / mo
Mistral Large 4Cheapest	$0.00203	$609	$305
GPT-6.1 Sol	$0.00700	$2,100	$1,050

Per 1K users assumesrequests per user per day.

Where the money is

If 60% of your traffic is simple enough for Mistral Large 4, routing it there instead of GPT-6.1 Sol saves about $895/month.

Caching half your input on GPT-6.1 Sol (a shared system prompt or document) would cut about $570/month.

You're looking at $609–$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 Mistral Large 4 vs GPT-6.1 Sol
Requests / day	Mistral Large 4	GPT-6.1 Sol	Difference
1,000	$60.90	$210	$149
10,000	$609	$2,100	$1,491
100,000	$6,090	$21,000	$14,910

By request type:

Cost per 1,000 calls by request type, Mistral Large 4 vs GPT-6.1 Sol
Per 1K calls	Mistral Large 4	GPT-6.1 Sol
Classification or routing call	$0.3010	$0.9000
Support chat reply	$1.58	$5.50
RAG answer over your docs	$5.04	$16.00
Long document summary	$30.10	$90.00

When to pick which

Mistral Large 4 is 2.9× cheaper on input tokens, which matters most for RAG and long prompts.
Mistral Large 4 is 4.8× cheaper on output tokens, which matters most for long answers, code generation and reasoning.
Cache reads are 1.4× cheaper on Mistral Large 4 ($0.07 vs $0.10 per 1M), so it pulls ahead when your prompts share a long fixed prefix.
Both offer 50% off for batch processing.
GPT-6.1 Sol has the larger context window (1.05M tokens vs 1M tokens).
Mistral Large 4 is open-weight, so you can move to self-hosting later without changing models.
GPT-6.1 Sol bills the whole request at a higher rate once input passes 272,000 tokens.

Mistral Large 4: Open-weight multimodal model with a 1M window. A cheap mid-tier option, and you can self-host the same weights later.

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

Verdict

Mistral Large 4 wins on price

3.4× cheaper

On price alone, Mistral Large 4 wins: about 3.4× cheaper than GPT-6.1 Sol for a typical request. Price is one input. Run both on 50 of your real prompts, compare the answers and the billed tokens, and route by difficulty if the quality gap only shows up on hard requests.

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, Mistral Large 4 or GPT-6.1 Sol?

For a typical request of 2,000 input and 300 output tokens, Mistral Large 4 is about 3.4× cheaper: $0.00203 per call on Mistral Large 4 vs $0.00700 on GPT-6.1 Sol. At 10,000 requests a day that is $609 vs $2,100 a month.

Can I use both Mistral Large 4 and GPT-6.1 Sol?

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 Mistral and OpenAI 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
Mistral Large 4docs.mistral.ai

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Fine print

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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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