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Gemini 2.5 Ultra vs Mistral X-Large

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

Verdict

Gemini 2.5 Ultra leads on LMSYS ELO (1385 vs 1318). Mistral X-Large is ~3.5× cheaper on a 3:1 input:output blend. Mistral X-Large is open-weights, the other is proprietary.

Google DeepMind

Gemini 2.5 Ultra

2M-token context, native video understanding, and Google’s deepest multimodal stack. The long-context king.

2M context windowNative videoBest multimodal reasoning

Mistral

Mistral X-Large

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

EU data residencyMultilingual strengthOpen license

Pricing

Input / 1M$7.00$2.00

Output / 1M$21.00$6.00

Context2.0M256K

Max output64K16K

LicenseProprietaryOpen weights

Released2026-02-052026-01-28

Benchmarks

LMSYS ELO1385.01318.0

MMLU Pro90.483.5

HumanEval90.288.0

SWE-Bench58.3—

MATH92.078.2

MMMU82.1—

IFEval89.786.5

Per-task cost

Summarize a 1-hour meeting transcript$0.115$0.033

Review a 500-line pull request$0.098$0.028

Answer a customer support ticket$0.038$0.011

Extract structured data from a resume$0.056$0.016

Debug a stack trace with context$0.084$0.024

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

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