Model comparison

Mistral Large 4 vs GPT-5.5

Mistral AI's Mistral Large 4 against OpenAI's GPT-5.5: vendor list prices, limits, abilities and the Artificial Analysis indexes side by side - and what OpenSmartRoute does when both are available.

CheaperMistral Large 4

Mistral Large 4 lists at $2.06 per million tokens blended against $11 for GPT-5.5 - 5.4x less.

Intelligence: levelEven

Intelligence index 38 against 38: within a point of each other.

Longer contextGPT-5.5

GPT-5.5 reads 1.1M tokens at once, Mistral Large 4 1.0M.

NewerMistral Large 4

Mistral Large 4 was released about 5 months later.

Side by side

Vendor list prices per million tokens and published limits; indexes are Artificial Analysis composites (0-100).

Specification	Mistral Large 4	GPT-5.5
Input price / 1M tokens	$1.36	$5.00
Output price / 1M tokens	$4.18	$30.0
Blended (3 in : 1 out)	$2.06	$11.3
Cached input / 1M	$0.14	$0.50
Context window	1.0M	1.1M
Max output	262K	128K
Input	text, image	file, image, text
Output	text	text
Tool calls
Structured output
Reasoning
Open weights
Intelligence index	38	38
Coding index	-	75
Agentic index	-	36
Released	Oct 6, 2026	Apr 24, 2026
Available on this deployment

What a month costs

List price times tokens for three typical workloads; your mix of input and output decides which model's pricing suits you.

Workload	Mistral Large 4	GPT-5.5	Difference
Support chat20M tokens in, 5M out a month - a help desk answering a few thousand conversations.	$48.10	$250	$202 less on Mistral Large 4
Document summaries100M in, 5M out - long inputs, short answers.	$157	$650	$493 less on Mistral Large 4
Coding assistant60M in, 20M out - a team's editor assistant, output-heavy.	$165	$900	$735 less on Mistral Large 4

What the router does with the pair

The two measure the same on the intelligence index, so the router treats them as peers and lets price, observed latency and your outcomes decide: Mistral Large 4 wins on cost, and a few bad outcomes on either move the next requests to the other.

Price a request Playground

yaml

# targets.yaml - both models as routing targets (metadata.model links each to the catalogue entry)
targets:
  - { id: mistral-large-4-0, kind: llm, metadata: { model: mistralai/mistral-large-4-0 } }
  - { id: gpt-5.5, kind: llm, metadata: { model: openai/gpt-5.5 } }

# rules.yaml - the cheaper model by default, the stronger one when the request is hard
rules:
  - name: simple-requests-stay-cheap
    when: { max_complexity: 0.45 }
    prefer: [mistral-large-4-0]
    weight: 0.8
  - name: hard-requests-escalate
    when: { min_complexity: 0.45 }
    prefer: [gpt-5.5]
    weight: 0.8

Frequently asked

Is Mistral Large 4 cheaper than GPT-5.5?: Yes. Mistral Large 4 lists at $1.36 in / $4.18 out per million tokens, GPT-5.5 at $5.00 in / $30.0 out; blended, Mistral Large 4 is the cheaper one.
Which is better, Mistral Large 4 or GPT-5.5?: The two measure the same on the intelligence index, so the task, the price and the abilities decide.
Which has the longer context window?: GPT-5.5 - 1.1M tokens against 1.0M.
Can I use Mistral Large 4 and GPT-5.5 together?: Yes. Declare both as targets and OpenSmartRoute picks one per request on quality for the task, price and your rules - the cheaper model for the requests it can answer, the stronger one for the rest - and records why in the trace.

Also compared

Every Mistral AI and OpenAI model, with prices, is on the vendor pages; the rankings show what the router actually picks.

For the business

What it means for which models you pay for.

Catalogue of every vendor
The right model, not the famous one
Price, context, abilities and benchmark indexes side by side, with the model that fits each task named.
The rankings
89% less
Lower cost per request
On the 150-prompt benchmark the router spent 89% less than sending every prompt to the reference model, and the judged quality went up, not down.
Read the benchmark
Per million tokens, every model
Prices you can compare
The catalogue prints input and output prices and what three typical monthly workloads cost on each.
The model catalogue

Which LLM is the cheapest for our workload?: The best-for pages rank the live catalogue per task by the index that measures it, and the router picks the cheapest model that meets your quality rule for each request.
How much can we save on our LLM bill?: On the public benchmark the router saved 89% against sending everything to the reference model. Import last month's provider bill on the bill page and the estimate is computed on your own traffic before you change a line of code.
How often do model prices change?: The catalogue is refreshed from the vendors' price lists; each model page shows the date of its data.

Stop choosing between Mistral Large 4 and GPT-5.5. Route to both.

Declare the pair as targets and OpenSmartRoute picks per request - the cheaper one where it holds up, the stronger one where it matters - with the comparison in every trace.

Create a free account Try a request

Free plan, no card. Fifteen thousand decisions a month with the full trace.

Specification

Mistral Large 4

GPT-5.5

Input price / 1M tokens

$1.36

$5.00

Output price / 1M tokens

$4.18

$30.0

Blended (3 in : 1 out)

$2.06

$11.3

Cached input / 1M

$0.14

$0.50

Context window

1.0M

1.1M

Max output

262K

128K

Input

text, image

file, image, text

Output

text

Tool calls

Structured output

Reasoning

Open weights

Intelligence index

Coding index

Agentic index

Released

Oct 6, 2026

Apr 24, 2026

Available on this deployment

Workload

Mistral Large 4

GPT-5.5

Difference

Support chat20M tokens in, 5M out a month - a help desk answering a few thousand conversations.

$48.10

$250

$202 less on Mistral Large 4

Document summaries100M in, 5M out - long inputs, short answers.

$157

$650

$493 less on Mistral Large 4

Coding assistant60M in, 20M out - a team's editor assistant, output-heavy.

$165

$900

$735 less on Mistral Large 4

# targets.yaml - both models as routing targets (metadata.model links each to the catalogue entry) targets: - { id: mistral-large-4-0, kind: llm, metadata: { model: mistralai/mistral-large-4-0 } } - { id: gpt-5.5, kind: llm, metadata: { model: openai/gpt-5.5 } } # rules.yaml - the cheaper model by default, the stronger one when the request is hard rules: - name: simple-requests-stay-cheap when: { max_complexity: 0.45 } prefer: [mistral-large-4-0] weight: 0.8 - name: hard-requests-escalate when: { min_complexity: 0.45 } prefer: [gpt-5.5] weight: 0.8

Frequently asked

Is Mistral Large 4 cheaper than GPT-5.5?

Yes. Mistral Large 4 lists at $1.36 in / $4.18 out per million tokens, GPT-5.5 at $5.00 in / $30.0 out; blended, Mistral Large 4 is the cheaper one.

Which is better, Mistral Large 4 or GPT-5.5?

The two measure the same on the intelligence index, so the task, the price and the abilities decide.

Which has the longer context window?

GPT-5.5 - 1.1M tokens against 1.0M.

Can I use Mistral Large 4 and GPT-5.5 together?

Yes. Declare both as targets and OpenSmartRoute picks one per request on quality for the task, price and your rules - the cheaper model for the requests it can answer, the stronger one for the rest - and records why in the trace.

Mistral Large 4 vs GPT-5.5

Side by side

What a month costs

What the router does with the pair

Frequently asked

Also compared

What it means for which models you pay for.

The right model, not the famous one

Lower cost per request

Prices you can compare

Stop choosing between Mistral Large 4 and GPT-5.5. Route to both.

Mistral Large 4 vs GPT-5.5

Side by side

What a month costs

What the router does with the pair

Frequently asked

Also compared

What it means for which models you pay for.

The right model, not the famous one

Lower cost per request

Prices you can compare

Stop choosing between Mistral Large 4 and GPT-5.5. Route to both.