Pixtral Large vs GPT-5.4 Pro

Benchmark Performance

Available Benchmarks

No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.
FieldAt a Glance
Mistral AI · deprecatedPixtral LargeVerified Aug 29, 2026
OpenAI · activeGPT-5.4 ProVerified Sep 3, 2026

Technical Differences

Side-by-Side Facts

Indexable
FieldPixtral LargeGPT-5.4 Pro
DeveloperMistral AIOpenAI
FamilyPixtral LargeGpt 5 4
ModelPixtral LargeGPT-5.4 Pro
VersionPixtral LargeGPT-5.4 Pro
Lifecycledeprecatedactive
Released2024-11-182026-03-05
Knowledge cutoffUnknown2025-08-31
Input modalitiesText, Image, DocumentText, Image
Output modalitiesTextText
Context window131,0721,050,000
Total parametersUnknownUnknown
Active parametersUnknownUnknown
LicenseUnknownUnknown
Open weightsNoNo
API availableNoYes
Self-hostableNoNo
Provider accessUnknownOpenai (Standard), Openrouter (Standard)
Capabilitieschat, generation, structured_outputs, tools, visionchat, generation, reasoning, structured_outputs, tools

13 comparable fields · 10 material differences · Pair passes the primary-source comparison gate

Pixtral Large Capabilities

chatgenerationstructured outputstoolsvision
Input price
Output price
Serving providers0
Canonical IDmistralai/pixtral-large-2411

GPT-5.4 Pro Capabilities

chatgenerationreasoningstructured outputstools
Input price$30.00
Output price$180.00
Serving providers2
Canonical IDopenai/gpt-5.4-pro

Internal Comparison Graph

Related Comparisons

All image comparisons →
APairBContext
vsfamily variantsimage, text
vsfamily variantsimage, text
vsdeveloper peersimage, text
vscross-developer peersimage, text
vscross-developer peersimage, text
vscross-developer peersimage, text
vscross-developer peersimage, text
vscross-developer peersimage, text
vsfamily variantsimage, text
vsfamily variantsimage, text
vscross-developer peersimage, text
vscross-developer peersimage, text

Primary Evidence

Sources and Freshness

Questions

Pixtral Large vs GPT-5.4 Pro FAQs

Is Pixtral Large or GPT-5.4 Pro better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Pixtral Large and GPT-5.4 Pro, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Pixtral Large or GPT-5.4 Pro?+

Only GPT-5.4 Pro has a directly sourced input price: $30.00 per million tokens. Only GPT-5.4 Pro has a directly sourced output price: $180.00 per million tokens.

Which has a larger context window, Pixtral Large or GPT-5.4 Pro?+

GPT-5.4 Pro has the larger sourced context window. Pixtral Large supports 131,072 and GPT-5.4 Pro supports 1,050,000.

Which performs better in benchmarks, Pixtral Large or GPT-5.4 Pro?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can Pixtral Large or GPT-5.4 Pro be self-hosted?+

Both models have the same recorded self-hosting status: unsupported. Pixtral Large is not marked open weight; GPT-5.4 Pro is not marked open weight.

Can Pixtral Large and GPT-5.4 Pro understand images?+

Pixtral Large is documented with image input; GPT-5.4 Pro is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Pixtral Large or GPT-5.4 Pro?+

Neither has a larger sourced maximum output. Pixtral Large is — and GPT-5.4 Pro is 128,000.

Do Pixtral Large and GPT-5.4 Pro support reasoning and tool use?+

Pixtral Large: tool calling and image input. GPT-5.4 Pro: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Pixtral Large or GPT-5.4 Pro?+

Pixtral Large has 0 sourced provider routes; GPT-5.4 Pro has 2, so GPT-5.4 Pro has broader tracked availability.

Which offers better value, Pixtral Large or GPT-5.4 Pro?+

There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.

Send Feedback