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Model comparison · Updated May 2026

DeepSeek R1 vs Mistral Large: Price, Context, Benchmarks (2026)

A direct, dated comparison of DeepSeek R1 (DeepSeek) and Mistral Large (Mistral). Every number below is sourced from official provider docs and public benchmarks. If you need to make this decision today, the verdict is at the top.

30-second verdict

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Specs side-by-side

SpecDeepSeek R1Mistral Large
VendorDeepSeekMistral
Input price (per 1M tokens)$0.55$2.00
Output price$2.19$6.00
Context window128K128K
Release date2025-01-202025-02-01
SWE-bench Verified~52%~45%
HumanEval~93%~88%
LMArena (approx)14181380
Open weightsYesYes
Capabilitiesreasoning, code, cheapcode

Pricing from official DeepSeek and Mistral docs. Benchmark numbers from SWE-bench Verified, HumanEval, and LMArena public leaderboards as of May 2026.

DeepSeek R1 — strengths and weaknesses

Strengths. Best price-to-quality, open weights, strong math + code, self-hostable.

Weaknesses. Weaker tool calling, smaller context, China-hosted official API.

Best for. Cost-sensitive production, batch jobs, self-hosted privacy use.

Mistral Large — strengths and weaknesses

Strengths. EU-hosted, Apache-licensed open variants, solid tool use, predictable.

Weaknesses. Behind frontier on reasoning benchmarks.

Best for. EU compliance, on-prem deployments, mid-range workloads.

Which one should you pick?

Pick DeepSeek R1 if: cost-sensitive production, batch jobs, self-hosted privacy use.

Pick Mistral Large if: eu compliance, on-prem deployments, mid-range workloads.

Use both if: you're building an agent or content pipeline. Route the high-stakes / hard-reasoning calls to whichever scores higher on the axis you care about, and the bulk / cheap calls to the other. Most production AI products run a 2-3 model router rather than betting on one.

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