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o4 vs Mistral X-Large

OpenAI vs Mistral. Specs, benchmarks, and real per-task cost — all in one page.

Verdict

Mistral X-Large is ~8.8× cheaper on a 3:1 input:output blend. Mistral X-Large is open-weights, the other is proprietary.

OpenAI

Deep-reasoning model. Spends more tokens thinking to crush math, science, and hard coding problems.

State-of-the-art math and scienceExtremely high-ceiling reasoning

Mistral

European frontier model. EU-hosted inference, strong European language coverage, Apache-licensed weights.

EU data residencyMultilingual strengthOpen license

Pricing

Input / 1M$15.00$2.00

Output / 1M$60.00$6.00

Context200K256K

Max output100K16K

LicenseProprietaryOpen weights

Released2026-02-182026-01-28

Benchmarks

LMSYS ELO—1318.0

MMLU Pro93.883.5

HumanEval92.388.0

SWE-Bench68.0—

MATH96.278.2

GPQA82.5—

IFEval—86.5

Per-task cost

Summarize a 1-hour meeting transcript$0.255$0.033

Review a 500-line pull request$0.240$0.028

Answer a customer support ticket$0.093$0.011

Extract structured data from a resume$0.135$0.016

Debug a stack trace with context$0.210$0.024

Per-call cost using published token counts for each task. Real-world prompts vary.

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