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Mistral X-Large vs Gemini 2.5 Flash

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

Verdict

Mistral X-Large leads on LMSYS ELO (1318 vs 1312). Gemini 2.5 Flash is ~5.7× cheaper on a 3:1 input:output blend. Mistral X-Large is open-weights, the other is proprietary.

Mistral

Mistral X-Large

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

EU data residencyMultilingual strengthOpen license

Google DeepMind

Gemini 2.5 Flash

Google’s price/performance darling. 1M context at $0.30/M input — nobody comes close on throughput-per-dollar.

Absurd cost-to-context ratioFast multimodalFree tier via AI Studio

Pricing

Input / 1M$2.00$0.30

Output / 1M$6.00$1.20

Context256K1.0M

Max output16K32K

LicenseOpen weightsProprietary

Released2026-01-282026-02-05

Benchmarks

LMSYS ELO1318.01312.0

MMLU Pro83.582.1

HumanEval88.085.8

MATH78.284.2

MMMU—74.6

IFEval86.586.1

Per-task cost

Summarize a 1-hour meeting transcript$0.033$0.0051

Review a 500-line pull request$0.028$0.0048

Answer a customer support ticket$0.011$0.0019

Extract structured data from a resume$0.016$0.0027

Debug a stack trace with context$0.024$0.0042

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

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