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Model comparison - Similar price, same tier

GPT-5.4 Mini vs Mistral Large 4

GPT-5.4 Mini is from OpenAI and Mistral Large 4 is from Mistral AI. On list price, Mistral Large 4 charges 1.8x GPT-5.4 Mini's input price ($1.36 vs $0.75 per 1M tokens), and Mistral Large 4 charges 7% less than GPT-5.4 Mini for output ($4.18 vs $4.50 per 1M tokens). GPT-5.4 Mini has a 400,000-token context window and Mistral Large 4 1,000,000 tokens; GPT-5.4 Mini returns up to 128,000 output tokens per response, and no primary source states a max output for Mistral Large 4. GPT-5.4 Mini was released on March 17, 2026 and Mistral Large 4 on October 5, 2026. Both are closed-weights models, available only through an API.

Last verified from each provider's pricing page. All sources

OpenAI - Closed

GPT-5.4 Mini
Input / 1M
$0.75
Output / 1M
$4.50
Context
400K

Mistral AI - Closed

Mistral Large 4
Input / 1M
$1.36
Output / 1M
$4.18
Context
1M

Side-by-side specs

SpecGPT-5.4 MiniMistral Large 4
ProviderOpenAIMistral AI
Input / 1M tokens$0.75$1.36
Output / 1M tokens$4.50$4.18
Cache read / 1M$0.075$0.14
Batch input / 1M$0.375$0.68
Batch output / 1M$2.25$2.09
Context window400,0001,000,000
Max output128,000-
Release date
WeightsClosedClosed
API model idgpt-5.4-minimistral-large-4
AI Gateway idopenai/gpt-5.4-minimistral/mistral-large-4
Last verified

Prices in USD per 1M tokens at each provider's standard first-party rate. A dash means the provider does not bill that item separately or no primary page states it.

What each costs in practice

The same three workloads every model page uses, worked from each model's standard list rates. Swap in your own token counts with the math on each model's page.

WorkloadGPT-5.4 MiniMistral Large 4
One agent session1M input tokens and 100K output tokens, no caching.$1.20$1.78
A chat app10,000 requests a day at 2K input and 500 output tokens each.$37.50$1,125.00 per 30-day month$48.10$1,443.00 per 30-day month
The same session at a 90% cache hit90% of the input is read from the prompt cache. The one-time cache write premium is not included.$0.5925$0.68
Show the math

GPT-5.4 Mini

  • One agent sessionInput: 1M x $0.75 = $0.75Output: 0.1M x $4.50 = $0.45
  • A chat appInput: 20M x $0.75 = $15.00Output: 5M x $4.50 = $22.50
  • The same session at a 90% cache hitCached input: 0.9M x $0.075 = $0.0675Uncached input: 0.1M x $0.75 = $0.075Output: 0.1M x $4.50 = $0.45

Mistral Large 4

  • One agent sessionInput: 1M x $1.36 = $1.36Output: 0.1M x $4.18 = $0.418
  • A chat appInput: 20M x $1.36 = $27.20Output: 5M x $4.18 = $20.90
  • The same session at a 90% cache hitCached input: 0.9M x $0.14 = $0.126Uncached input: 0.1M x $1.36 = $0.136Output: 0.1M x $4.18 = $0.418

Benchmarks under the same setting

No board in the benchmark directory lists both GPT-5.4 Mini and Mistral Large 4 under the same setting, so there is no like-for-like score to show here.

Model pages

FAQ

How do GPT-5.4 Mini and Mistral Large 4 compare on price?

On list price, Mistral Large 4 charges 1.8x GPT-5.4 Mini's input price ($1.36 vs $0.75 per 1M tokens), and Mistral Large 4 charges 7% less than GPT-5.4 Mini for output ($4.18 vs $4.50 per 1M tokens). For one agent session of 1M input and 100K output tokens with no caching, that is $1.20 on GPT-5.4 Mini and $1.78 on Mistral Large 4. Prices are each provider's first-party list rates, verified October 17, 2026 and October 17, 2026.

What are the context windows of GPT-5.4 Mini and Mistral Large 4?

GPT-5.4 Mini has a 400,000-token context window and Mistral Large 4 1,000,000 tokens; GPT-5.4 Mini returns up to 128,000 output tokens per response, and no primary source states a max output for Mistral Large 4.

Are GPT-5.4 Mini and Mistral Large 4 open weights?

GPT-5.4 Mini is closed-weights and is called through OpenAI's API as gpt-5.4-mini. Mistral Large 4 is closed-weights and is called through Mistral AI's API as mistral-large-4.

More comparisons

Sources

GPT-5.4 Mini verified from developers.openai.com; Mistral Large 4 verified from docs.mistral.ai. This page is as current as the older of the two: .

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